**Meet the editor**

Dr Yasuhiro Honda is a Clinical Associate Professor of Medicine and a faculty member at the Center for Cardiovascular Technology, Stanford University School of Medicine. He received his MD from Kyoto University Faculty of Medicine. After completing cardiology training in Japan, he joined the Division of Cardiovascular Medicine at Stanford University in 1995, and has been

serving as Co-Director of the Cardiovascular Core Analysis Laboratory (CCAL) since 2005.

Contents

**Preface IX** 

Gaël Y. Rochefort

Chapter 2 **Plaque Regression and Stability** 

and Atsushi Hirayama

Masanori Kawasaki

Chapter 4 **IVUS Role in Studies Assessing** 

Chapter 6 **Intravascular Ultrasound (IVUS) and Clinical Applications 87** 

**Part 2 Interventional Applications 93** 

T. Kovarnik and J. Horak

Chapter 5 **IVUS in the Assessment of** 

T. Ozcan

Chapter 8 **IVUS Guided PCI 107** 

**Part 1 Principles and Diagnostic Applications 1** 

**Evaluated by Intravascular Ultrasound and Coronary Angioscopy: A Review 23**  Satoshi Saito, Takafumi Hiro, Tadateru Takayama

Chapter 3 **Integrated Backscatter Intravascular Ultrasound 41** 

T. Kovarnik, A. Wahle, R.W. Downe and M. Sonka

**Atherosclerosis Development 53** 

**Coronary Allograft Vasculopathy 69**  Sudhir S. Kushwaha and Eugenia Raichlin

Chapter 7 **Clinical Applications of Intravascular Ultrasound 95**  Dermot Phelan, Sajjad Matiullah and Faisal Sharif

**Intravascular Ultrasound: Principles and Applicability 3** 

Chapter 1 **Non-Coronary Vessel Exploration Under** 

## Contents

#### **Preface XI**

	- **Part 2 Interventional Applications 93**
	- **Part 3 Technical Developments 159**

## Preface

In 1971, Bom et al. developed one of the first catheter-based real-time imaging techniques for use in the cardiac system. By placing a set of phased array ultrasound transducers within the cardiac chambers, it was shown that higher frequencies could be used to produce high-resolution images of cardiac structures without interference from bony structures that occurs with transthoracic ultrasound imaging. By the late 1980s, Yock et al. had successfully miniaturized a single-transducer system to enable the transducer placement within coronary arteries. Since then, intravascular ultrasound (IVUS) has become pivotal catheter-based imaging technology, having provided practical guidance for percutaneous interventions as well as scientific insights into vascular biology in clinical settings.

Recent advancements in noninvasive cardiovascular imaging now allow rapid and detailed visualization of cardiovascular structures. However, clinical demand for catheter-based imaging is also growing, largely driven by evolving percutaneous treatment technologies that require precise procedural guidance or real-time assessment of the treatment effects. These technologies include not only a variety of coronary or peripheral vascular interventions, but also percutaneous treatment devices for structural heart disease or heart failure. As illustrated by the late thrombosis issue in drug-eluting stents, the consequences of new treatment may also benefit from indepth examination of the treated site. Furthermore, the attempt to identify vulnerable plaques significantly stimulates the technical advancements of imaging modalities beyond anatomy.

This book is intended to serve as an up-to-date resource relating to IVUS, not only for practising cardiologists, residents and students, but also for researchers and engineers with aspirations to apply or advance this sophisticated imaging technology. The first section discusses the basic principles and diagnostic applications of the IVUS technology, including the detailed descriptions of advanced tissue characterization and vascular profiling techniques. The second section summarizes the current use of IVUS in interventional applications such as the guidance of complex percutaneous procedures or the assessment of vascular response to new treatments. The third section is dedicated to ongoing technical efforts to further enhance the utility of this imaging technology. It is our hope that this book will prove useful to the medical and

#### X Preface

engineering community as a comprehensive guide to understanding this rapidly evolving technology and its role in cardiovascular research and patient care.

Being asked to serve as the editor of this book has been a great privilege. However, the successful production has required the support and co-operation of a number of individuals. I would like to express my deep appreciation to all the contributing authors, as well as the staff of the open access publisher InTech, in particular Ms Petra Nenadic, Ms Petra Zobic, and Ms Viktorija Zgela, for their tireless efforts and ongoing encouragement throughout this endeavor. Without their expertise, dedication and time commitment, this book would not have been possible.

#### **Yasuhiro Honda, MD, FACC, FAHA**

Clinical Associate Professor of Medicine Co-Director, Cardiovascular Core Analysis Laboratory Division of Cardiovascular Medicine Stanford University School of Medicine USA

X Preface

engineering community as a comprehensive guide to understanding this rapidly

Being asked to serve as the editor of this book has been a great privilege. However, the successful production has required the support and co-operation of a number of individuals. I would like to express my deep appreciation to all the contributing authors, as well as the staff of the open access publisher InTech, in particular Ms Petra Nenadic, Ms Petra Zobic, and Ms Viktorija Zgela, for their tireless efforts and ongoing encouragement throughout this endeavor. Without their expertise, dedication and

> **Yasuhiro Honda, MD, FACC, FAHA**  Clinical Associate Professor of Medicine

Division of Cardiovascular Medicine Stanford University School of Medicine

USA

Co-Director, Cardiovascular Core Analysis Laboratory

evolving technology and its role in cardiovascular research and patient care.

time commitment, this book would not have been possible.

**Part 1** 

**Principles and Diagnostic Applications** 

## **Part 1**

## **Principles and Diagnostic Applications**

**1** 

**Non-Coronary Vessel** 

*Inserm U658 Ipros Chro, Orleans* 

Gaël Y. Rochefort

*France* 

**Exploration Under Intravascular** 

**Ultrasound: Principles and Applicability** 

Intravascular Ultrasound (IVUS) has become rapidly one of the gold technologies for the endovascular exploration. Next to angiography, which only gives information about the lumen of the investigated vessels, IVUS describes both the luminal and trans-mural anatomy of vascular structures. Actual devices offer several configurations and transducers mounted at the end of an intra-luminal catheter to produce real-time grayscale or color images of blood vessels and cardiac structures. The ultrasound probes miniaturization has permitted closer imaging and magnified details of the vessel wall and plaque. Recent IVUS catheters use phased array imaging where the micro-transducers are enveloped around a catheter tip. Typically, IVUS images show the vessel wall in histological detail: the intima reflects ultrasound brightly and is white, the media is echolucent and dark, and the

IVUS has thus become a safe and valuable tool in exploring the disease severity and the treatment completeness during surgical endovascular procedures (Jinzaki et al., 1993; Nishanian et al., 1999), such as assessing the severity of an arterial disease before treatment (Scoccianti et al., 1994), determining the plaque morphology and localization or checking the completeness of stent deployment (Diethrich, 1993; Laskey et al., 1993). Very recently, color flow IVUS and three-dimensional (3D) reconstruction have both introduced significant advances in the understanding of IVUS images (Irshad et al., 2001; Reid et al., 1995; White et al., 1994). The very latest advance, called virtual histology IVUS, provides a color-coded map of the plaque components, thus providing a better understanding of the arterial plaque

IVUS gives series of tomographic images of the explored vessel wall. During acquisition, an IVUS catheter is entered into a vessel and then withdrawn through a given vessel segment during simultaneous and continuous imaging, resulting in series of cross section images. Current catheters have frequencies from 30 to 40 MHz, planar resolutions from 50 to 150

µm, and a typical sampling rate of 30 images per second (Di Mario et al., 1995).

structure and morphology (Nair et al., 2001; Vince & Davies, 2004).

**1. Introduction** 

surrounding adventitia is white.

**2. IVUS principle** 

## **Non-Coronary Vessel Exploration Under Intravascular Ultrasound: Principles and Applicability**

Gaël Y. Rochefort *Inserm U658 Ipros Chro, Orleans France* 

#### **1. Introduction**

Intravascular Ultrasound (IVUS) has become rapidly one of the gold technologies for the endovascular exploration. Next to angiography, which only gives information about the lumen of the investigated vessels, IVUS describes both the luminal and trans-mural anatomy of vascular structures. Actual devices offer several configurations and transducers mounted at the end of an intra-luminal catheter to produce real-time grayscale or color images of blood vessels and cardiac structures. The ultrasound probes miniaturization has permitted closer imaging and magnified details of the vessel wall and plaque. Recent IVUS catheters use phased array imaging where the micro-transducers are enveloped around a catheter tip. Typically, IVUS images show the vessel wall in histological detail: the intima reflects ultrasound brightly and is white, the media is echolucent and dark, and the surrounding adventitia is white.

IVUS has thus become a safe and valuable tool in exploring the disease severity and the treatment completeness during surgical endovascular procedures (Jinzaki et al., 1993; Nishanian et al., 1999), such as assessing the severity of an arterial disease before treatment (Scoccianti et al., 1994), determining the plaque morphology and localization or checking the completeness of stent deployment (Diethrich, 1993; Laskey et al., 1993). Very recently, color flow IVUS and three-dimensional (3D) reconstruction have both introduced significant advances in the understanding of IVUS images (Irshad et al., 2001; Reid et al., 1995; White et al., 1994). The very latest advance, called virtual histology IVUS, provides a color-coded map of the plaque components, thus providing a better understanding of the arterial plaque structure and morphology (Nair et al., 2001; Vince & Davies, 2004).

#### **2. IVUS principle**

IVUS gives series of tomographic images of the explored vessel wall. During acquisition, an IVUS catheter is entered into a vessel and then withdrawn through a given vessel segment during simultaneous and continuous imaging, resulting in series of cross section images. Current catheters have frequencies from 30 to 40 MHz, planar resolutions from 50 to 150 µm, and a typical sampling rate of 30 images per second (Di Mario et al., 1995).

Non-Coronary Vessel Exploration Under Intravascular Ultrasound: Principles and Applicability 5

transfer in digital format, and may provide radiofrequency outputs composed of raw IVUS acoustic signals. This signal processing approach is particularly adapted for a computerized image analysis, since it allows traditional measurements but also radiofrequency-based

Typical mechanical IVUS transducers produce cross-sectional images by rotating at the tip of the catheter using a flexible, high-torque cable. These transducers are creating a coneshaped ultrasound beam that allows the vessel to be imaged slightly forward or in front of

An optimized visualization is obtained when using IVUS catheter having appropriate size and frequency. Thus, the clinician has to make a compromise between the highest frequency *vs.* depth of penetration *vs.* catheter size. He also has to consider the wire guide diameter and the guide-wire exchanges utility. IVUS catheters used for most aortic and iliac procedures can be advanced over a 0.035-inch guide wire and range in size and frequency from 6 to 8 Fr and 8 to 20 MHz, respectively. An IVUS probe, ranging between 8 to 15 MHz is commonly used for aortic procedures, allowing an adequate circumferential imaging. The following Table 1 is presenting the current available catheters applicable for peripheral

**(Fr)**

Visions PV 8.2F IVUS Imaging 8.2 0.038 8.3 Aorta iliac

 Atlantis PV Peripheral Imaging 8 0.035 15 Aorta iliac Sonicath Ultra Ultrasound 9 0.035 9 Aorta iliac Sonicath Ultra Ultrasound 3.2 0.018 20 Femoral popliteal

 Sonicath Ultra Ultrasound 6 0.035 12.5 Iliac femoral Sonicath Ultra Ultrasound 6 0.035 20 Femoral popliteal

Table 1. Specifications of commonly used intravascular ultrasound (IVUS) catheters in

Atlantis SR Pro 3.2 0.014 40 Femoral popliteal

Atlantis SR Plus 3 0.014 40 Femoral popliteal

Atlantis SR 3.2 0.014 40 Femoral popliteal

**Guide Wire (in)** **Frequency (MHz)**

3.5 0.014 20 Carotid renal iliac

3.5 0.018 20 Femoral popliteal

**Target vessel** 

Femoral

tibial

tibial

tibial

tibial

tibial

tibial

tissue characterization (Nair et al., 2001; Nair et al., 2002).

**3. Devices, recording methods and techniques** 

**3.1 Devices** 

the transducer assembly.

vascular and coronary interventions.

 Eagle Eye Gold IVUS Imaging (color-flow and virtual histology)

(color-flow)

Visions PV 0.018 F/X IVUS Imaging

peripheral occlusive interventions.

**Intravascular Ultrasound Catheters Size**

Volcano Corporation catheters (phase array)

Boston Scientific catheters (rotating crystal)

#### **2.1 Acquisition using pullback devices**

The current methods used to quantify a volumetric IVUS analysis are usually achieved by a simple summation of a targeted subsample of the 2-D images into a volumetric dataset (Chandrasekaran et al., 1994; Rosenfield et al., 1992; Rosenfield et al., 1991). In that case, the accurate volume calculations need the precise localization of each 2-D cross-sectional image used in the longitudinal axis of the vessel segment (Di Mario et al., 1995; Roelandt et al., 1994). To do so, a manual pullback was firstly performed, with recording of the time and length of the acquisition, and the image location was estimated from the pullback start point and the average pullback velocity. Alternatively, displacement sensors were used to record the IVUS catheter translation during the manual pullback procedure (Hagenaars et al., 2000). Since it is obviously difficult to maintain a consistent speed during manual pullback, most current systems have introduced a motorized pullback device with a constant speed (usually around 0.5 mm/s) (Cavaye et al., 1992; Liu et al., 1999; Matar et al., 1994).

#### **2.2 Cardiac synchronization and frame selection**

Since images are recorded at 30 frames per second, with a pullback speed of 0.5 mm/s, 60 frames are recorded for each 1-mm vessel segment. Since, a coronary segment of 3 to 10 cm is typically explored, 1800 to 6000 individual frames are usually recorded. Therefore, these large datasets are often sub-sampled using constant intervals (0.5 - 1.0 mm) or using an electrocardiogram gating: the 1-mm interval without respect to the cardiac cycle is often used for manual analysis, whereas computerized algorithms require different sampling intervals (Klingensmith et al., 2000a; von Birgelen et al., 1996a). Therefore, consecutive frames sub-sampled with a 1-mm interval are corresponding to changes in the lumen and vessel areas during the different phases of the cardiac cycle.

A typical "sawtooth" artifact can be seen on longitudinal 2-D pullback displays when the sub-sampling is performed without synchronization to the cardiac cycle. This sawtooth artifact is less marked when the explored vessel exhibit a reduced compliance (such as stented vessels or stenotic vessels). Nevertheless, it is recommended to get the cardiac cycle synchronization since it allows the cyclic cycle artifacts to be eliminated (von Birgelen et al., 1996b; von Birgelen et al., 1997b). In fact, different physiologic, cyclic signals are commonly used to synchronize the IVUS images to the cardiac cycle, including the arterial blood pressure and the electrocardiogram signals (Allan et al., 1998; Sonka et al., 1998).

When operating a retrospective gating, IVUS images and electrocardiogram signals are acquired continuously, since the electrocardiogram signals are required to sort the images and to perform the analysis of the volumetric dataset (Klingensmith et al., 2000a; Kovalski et al., 2000). On the other hand, when operating a prospective gating, the IVUS images are only acquired at a given times of the cardiac cycle and the catheter is then moved to acquire the next gated image (Bruining et al., 1998; von Birgelen et al., 1997a; von Birgelen et al., 1995). This last gating method presents the advantage to not requiring additional steps to perform the analysis of the dataset, and a volumetric dataset is available immediately after the acquisition pullback.

#### **2.3 Transferring the IVUS dataset to an analysis system**

The whole raw IVUS data, composed of the reflected acoustic signals, are displayed on IVUS consoles. This dataset could also be stored on S-VHS videotape, on CD-ROM or magnetooptical disks. Recent IVUS consoles have digital output capabilities that allow direct data transfer in digital format, and may provide radiofrequency outputs composed of raw IVUS acoustic signals. This signal processing approach is particularly adapted for a computerized image analysis, since it allows traditional measurements but also radiofrequency-based tissue characterization (Nair et al., 2001; Nair et al., 2002).

#### **3. Devices, recording methods and techniques**

#### **3.1 Devices**

4 Intravascular Ultrasound

The current methods used to quantify a volumetric IVUS analysis are usually achieved by a simple summation of a targeted subsample of the 2-D images into a volumetric dataset (Chandrasekaran et al., 1994; Rosenfield et al., 1992; Rosenfield et al., 1991). In that case, the accurate volume calculations need the precise localization of each 2-D cross-sectional image used in the longitudinal axis of the vessel segment (Di Mario et al., 1995; Roelandt et al., 1994). To do so, a manual pullback was firstly performed, with recording of the time and length of the acquisition, and the image location was estimated from the pullback start point and the average pullback velocity. Alternatively, displacement sensors were used to record the IVUS catheter translation during the manual pullback procedure (Hagenaars et al., 2000). Since it is obviously difficult to maintain a consistent speed during manual pullback, most current systems have introduced a motorized pullback device with a constant speed

(usually around 0.5 mm/s) (Cavaye et al., 1992; Liu et al., 1999; Matar et al., 1994).

Since images are recorded at 30 frames per second, with a pullback speed of 0.5 mm/s, 60 frames are recorded for each 1-mm vessel segment. Since, a coronary segment of 3 to 10 cm is typically explored, 1800 to 6000 individual frames are usually recorded. Therefore, these large datasets are often sub-sampled using constant intervals (0.5 - 1.0 mm) or using an electrocardiogram gating: the 1-mm interval without respect to the cardiac cycle is often used for manual analysis, whereas computerized algorithms require different sampling intervals (Klingensmith et al., 2000a; von Birgelen et al., 1996a). Therefore, consecutive frames sub-sampled with a 1-mm interval are corresponding to changes in the lumen and

A typical "sawtooth" artifact can be seen on longitudinal 2-D pullback displays when the sub-sampling is performed without synchronization to the cardiac cycle. This sawtooth artifact is less marked when the explored vessel exhibit a reduced compliance (such as stented vessels or stenotic vessels). Nevertheless, it is recommended to get the cardiac cycle synchronization since it allows the cyclic cycle artifacts to be eliminated (von Birgelen et al., 1996b; von Birgelen et al., 1997b). In fact, different physiologic, cyclic signals are commonly used to synchronize the IVUS images to the cardiac cycle, including the arterial blood

When operating a retrospective gating, IVUS images and electrocardiogram signals are acquired continuously, since the electrocardiogram signals are required to sort the images and to perform the analysis of the volumetric dataset (Klingensmith et al., 2000a; Kovalski et al., 2000). On the other hand, when operating a prospective gating, the IVUS images are only acquired at a given times of the cardiac cycle and the catheter is then moved to acquire the next gated image (Bruining et al., 1998; von Birgelen et al., 1997a; von Birgelen et al., 1995). This last gating method presents the advantage to not requiring additional steps to perform the analysis of the dataset, and a volumetric dataset is available immediately after the

The whole raw IVUS data, composed of the reflected acoustic signals, are displayed on IVUS consoles. This dataset could also be stored on S-VHS videotape, on CD-ROM or magnetooptical disks. Recent IVUS consoles have digital output capabilities that allow direct data

pressure and the electrocardiogram signals (Allan et al., 1998; Sonka et al., 1998).

**2.1 Acquisition using pullback devices** 

**2.2 Cardiac synchronization and frame selection** 

vessel areas during the different phases of the cardiac cycle.

**2.3 Transferring the IVUS dataset to an analysis system** 

acquisition pullback.

Typical mechanical IVUS transducers produce cross-sectional images by rotating at the tip of the catheter using a flexible, high-torque cable. These transducers are creating a coneshaped ultrasound beam that allows the vessel to be imaged slightly forward or in front of the transducer assembly.

An optimized visualization is obtained when using IVUS catheter having appropriate size and frequency. Thus, the clinician has to make a compromise between the highest frequency *vs.* depth of penetration *vs.* catheter size. He also has to consider the wire guide diameter and the guide-wire exchanges utility. IVUS catheters used for most aortic and iliac procedures can be advanced over a 0.035-inch guide wire and range in size and frequency from 6 to 8 Fr and 8 to 20 MHz, respectively. An IVUS probe, ranging between 8 to 15 MHz is commonly used for aortic procedures, allowing an adequate circumferential imaging. The following Table 1 is presenting the current available catheters applicable for peripheral vascular and coronary interventions.


Table 1. Specifications of commonly used intravascular ultrasound (IVUS) catheters in peripheral occlusive interventions.

Non-Coronary Vessel Exploration Under Intravascular Ultrasound: Principles and Applicability 7

considering tortuous aortas and the thoracic arch. In such cases, the minimal diameter (minor axis) is the best accurate measurement to measure the vessel diameter in angled images and/or tortuous vessels (Roelandt et al., 1994). At last, withdrawing the catheter through the lumen, rather than advancing it, promotes the acquisition of the best-quality

During the procedure, real-time images of the investigated vessel are displayed on a monitor and are usually recorded digitally. The IVUS devices also allow the on-line and/or off-line measurements of vessel dimensions, luminal diameters, and cross-sectional areas. Recent IVUS units, comprising a motorized and/or automated withdrawing the catheter through the vessel at a controlled rate, may display a longitudinal gray-scale image of the investigated vessel with accurate reconstructed views (Hagenaars et al., 2000). These twodimensional longitudinal reconstructions allow distances to be measured from one point to another (Liu et al., 1999) and cross-sectional trans-mural wall morphology to be visualized (Di Mario et al., 1995). In fact, the discrimination of plaque, normal tissue, thrombus, dissections, and flaps is often much better appreciated on the two-dimensional longitudinal

IVUS reconstructions than on traditional angiographic images (Reid et al., 1995).

measurement for plaque cross-sectional area (Prati et al., 2002).

**4.1 Automated 2-D/3-D border-detection methods** 

processing techniques allows fast online analysis (Sanz-Requena et al., 2007).

The dataset for volumetric analysis is represented by image series composed of twodimensional sections from the investigated vessels. Typically, images are selected at 1-mm inter-slice spacing. Then, to perform a quantitative 3-D reconstruction, the first and most critical step is to precisely identify and trace the anatomical structures of the studied vessel. In fact, identifying the luminal border is essential to discriminate the blood-intima interface, whereas recognizing the external elastic membrane border is important to precisely distinguish the boundary between the media and the adventitia (Kovalski et al., 2000). The space between these 2 borders is the plaque-media complex and is classically used as the

In stented vessel segments, the lumen/intimal interface and the stent borders are both measured, and the area between these borders is representing the neointimal tissue. In these stented vessel segments, the external elastic membrane border is frequently not distinguished because of signal drop-out behind the stent. In current atherosclerosis research trials, the assessment of stent, luminal and external elastic membrane borders is often performed with manual planimetry using commercially or freely available computer programs. This provides the accurate discrimination of image artifacts and true border locations but this analysis requires the border detection in hundreds of images. Therefore, the use of automated image-

Different approaches have been described to detect the luminal and external elastic membrane borders from 2-D IVUS images, including texture-based methods (Papadogiorgaki et al., 2007), knowledge-based graph searching (Bovenkamp et al., 2009), region growing (Sanz-Requena et al., 2007), radial gradient searching (Luo et al., 2003), and active contours (Sanz-Requena et al., 2007; Takagi et al., 2000). These 2-D border-detection techniques are now used online in newer IVUS imaging consoles, allowing the quantitative evaluation of lumen and plaque measurements. Because the user provides his expertise to augment the algorithm or correct results, the semi-automated techniques typically require

images (Danilouchkine et al., 2009).

**4. Data processing and analysis** 

#### **3.2 Access to vessels**

Depending on the size of the considered vessel (see Table 1), IVUS catheters can be introduced percutaneously through a standard vascular access sheath (5 to 9 Fr). The 8.2 Fr, 10-MHz catheter is one of the most commonly used catheter for aorta-iliac intervention, since it requires a 0.035-inch guide wire and thus can be quickly prepared, introduced, and/or exchanged with other catheters. However, this specific catheter requires a 9 Fr sheath that can be disproportionate for lower extremity interventions.

Most current percutaneous trans-luminal angioplasty balloons and stents targeted for infrainguinal regions require only 6 Fr sheaths. The 3.4 Fr, 3.2 Fr, or 2.9 Fr catheters, using 0.018 inch and 0.014-inch guide wires, are more suitable for the typical retrograde common femoral artery puncture and access to the contra-lateral femoral-popliteal segments (Hiro et al., 1998; Saketkhoo et al., 2004). In some case, especially with tortuous vessels and when antegrade puncture of the common femoral vessel is required, the 3 Fr catheters are also useful.

Lengths of IVUS catheters are vary from 90 to 150 cm, thus allowing imaging of small tibial vessels from a contra-lateral up-and-over approach. The smaller catheters require 0.018-inch or 0.014-inch guide wires and are commonly used for infra-inguinal interventions, whereas the larger IVUS catheters need 0.035-inch guide wires and used for larger vessel interventions (Hiro et al., 1998).

#### **3.3 Image acquisition and quality**

An optimal visualization requires a careful positioning of the catheter tip within the vessel and an appropriate size matching of the device to the artery caliber, meaning that an IVUS intervention necessitates a pre-procedural estimation the target vessel diameters (Figure 1). The best image quality is obtained when the IVUS catheter is parallel to the vessel wall and when the ultrasound beam is perpendicular to the luminal surface. Some artificial differences in the wall thickness measurement may be obtained when the IVUS catheter has an eccentric position, leading to the vessel wall to appear more hyperechoic than the distant wall. Angulations may promote an elliptical image of the vessel lumen, especially when

Fig. 1. Illustration of quantitative measurements with IVUS. Examples show an *in vivo* IVUS image digitized from video (A) and the detected borders overlaid (B).

considering tortuous aortas and the thoracic arch. In such cases, the minimal diameter (minor axis) is the best accurate measurement to measure the vessel diameter in angled images and/or tortuous vessels (Roelandt et al., 1994). At last, withdrawing the catheter through the lumen, rather than advancing it, promotes the acquisition of the best-quality images (Danilouchkine et al., 2009).

During the procedure, real-time images of the investigated vessel are displayed on a monitor and are usually recorded digitally. The IVUS devices also allow the on-line and/or off-line measurements of vessel dimensions, luminal diameters, and cross-sectional areas. Recent IVUS units, comprising a motorized and/or automated withdrawing the catheter through the vessel at a controlled rate, may display a longitudinal gray-scale image of the investigated vessel with accurate reconstructed views (Hagenaars et al., 2000). These twodimensional longitudinal reconstructions allow distances to be measured from one point to another (Liu et al., 1999) and cross-sectional trans-mural wall morphology to be visualized (Di Mario et al., 1995). In fact, the discrimination of plaque, normal tissue, thrombus, dissections, and flaps is often much better appreciated on the two-dimensional longitudinal IVUS reconstructions than on traditional angiographic images (Reid et al., 1995).

#### **4. Data processing and analysis**

6 Intravascular Ultrasound

Depending on the size of the considered vessel (see Table 1), IVUS catheters can be introduced percutaneously through a standard vascular access sheath (5 to 9 Fr). The 8.2 Fr, 10-MHz catheter is one of the most commonly used catheter for aorta-iliac intervention, since it requires a 0.035-inch guide wire and thus can be quickly prepared, introduced, and/or exchanged with other catheters. However, this specific catheter requires a 9 Fr

Most current percutaneous trans-luminal angioplasty balloons and stents targeted for infrainguinal regions require only 6 Fr sheaths. The 3.4 Fr, 3.2 Fr, or 2.9 Fr catheters, using 0.018 inch and 0.014-inch guide wires, are more suitable for the typical retrograde common femoral artery puncture and access to the contra-lateral femoral-popliteal segments (Hiro et al., 1998; Saketkhoo et al., 2004). In some case, especially with tortuous vessels and when antegrade

Lengths of IVUS catheters are vary from 90 to 150 cm, thus allowing imaging of small tibial vessels from a contra-lateral up-and-over approach. The smaller catheters require 0.018-inch or 0.014-inch guide wires and are commonly used for infra-inguinal interventions, whereas the larger IVUS catheters need 0.035-inch guide wires and used for larger vessel

An optimal visualization requires a careful positioning of the catheter tip within the vessel and an appropriate size matching of the device to the artery caliber, meaning that an IVUS intervention necessitates a pre-procedural estimation the target vessel diameters (Figure 1). The best image quality is obtained when the IVUS catheter is parallel to the vessel wall and when the ultrasound beam is perpendicular to the luminal surface. Some artificial differences in the wall thickness measurement may be obtained when the IVUS catheter has an eccentric position, leading to the vessel wall to appear more hyperechoic than the distant wall. Angulations may promote an elliptical image of the vessel lumen, especially when

Fig. 1. Illustration of quantitative measurements with IVUS. Examples show an *in vivo* IVUS

puncture of the common femoral vessel is required, the 3 Fr catheters are also useful.

sheath that can be disproportionate for lower extremity interventions.

**3.2 Access to vessels** 

interventions (Hiro et al., 1998).

**3.3 Image acquisition and quality** 

A. B.

image digitized from video (A) and the detected borders overlaid (B).

The dataset for volumetric analysis is represented by image series composed of twodimensional sections from the investigated vessels. Typically, images are selected at 1-mm inter-slice spacing. Then, to perform a quantitative 3-D reconstruction, the first and most critical step is to precisely identify and trace the anatomical structures of the studied vessel. In fact, identifying the luminal border is essential to discriminate the blood-intima interface, whereas recognizing the external elastic membrane border is important to precisely distinguish the boundary between the media and the adventitia (Kovalski et al., 2000). The space between these 2 borders is the plaque-media complex and is classically used as the measurement for plaque cross-sectional area (Prati et al., 2002).

In stented vessel segments, the lumen/intimal interface and the stent borders are both measured, and the area between these borders is representing the neointimal tissue. In these stented vessel segments, the external elastic membrane border is frequently not distinguished because of signal drop-out behind the stent. In current atherosclerosis research trials, the assessment of stent, luminal and external elastic membrane borders is often performed with manual planimetry using commercially or freely available computer programs. This provides the accurate discrimination of image artifacts and true border locations but this analysis requires the border detection in hundreds of images. Therefore, the use of automated imageprocessing techniques allows fast online analysis (Sanz-Requena et al., 2007).

#### **4.1 Automated 2-D/3-D border-detection methods**

Different approaches have been described to detect the luminal and external elastic membrane borders from 2-D IVUS images, including texture-based methods (Papadogiorgaki et al., 2007), knowledge-based graph searching (Bovenkamp et al., 2009), region growing (Sanz-Requena et al., 2007), radial gradient searching (Luo et al., 2003), and active contours (Sanz-Requena et al., 2007; Takagi et al., 2000). These 2-D border-detection techniques are now used online in newer IVUS imaging consoles, allowing the quantitative evaluation of lumen and plaque measurements. Because the user provides his expertise to augment the algorithm or correct results, the semi-automated techniques typically require

Non-Coronary Vessel Exploration Under Intravascular Ultrasound: Principles and Applicability 9

short and straight vessel segments, such as coronary stented lesions, but it does not allow

The volumetric approach using 3-D border-detection techniques is currently applied in serial IVUS studies examining atherosclerotic disease progression or regression, allowing the assessment of plaque burden in an entire vessel segment through fast analysis of large image sequences. New interventional approaches also use a volumetric IVUS imaging approach to provide new mechanistic insights, such as innovative techniques aimed at the prevention and treatment of in-stent restenosis correlated with histomorphometry measurements (Mehran et al., 1998; Murata et al., 2002); approaches in understanding the effects of radiation therapy and the arterial remodeling on a stented segment (brachytherapy) (Lekston et al., 2008; Weichert et al., 2003; Zimarino et al., 2002; Zimmermann et al., 2005); or using drug-eluting stents on the neointimal hyperplasia

Since the curvature of vessels is not taken into account with these straight 3-D IVUS methods, this limitation can be overcome by fusing the curvature information provided by biplane angiography or other techniques with the IVUS border information (Schuurbiers et al., 2009; Sherknies et al., 2005; Tu et al., 2010; Wahle et al., 2006). To do so, one common method is to acquire two separate angiographic images from different angles at the beginning of the ultrasound scanning imaging procedure and to use the catheter outline reconstructed from these images as a template for placement of the IVUS-derived contours (Bourantas et al., 2005; Klingensmith et al., 2000b; Sherknies et al., 2005; von Birgelen et al., 1995; Weichert et al., 2003). Another method consists in following the IVUS transducer in time and space throughout the IVUS pullback using biplane angiography, thus the precise locations of IVUS image acquisitions are recorded in sequence and are used as a reconstruction template (Klingensmith et al., 2000b; Miyazaki et al., 2010; Wallace et al., 2005). However, this method might be difficult because of the cardiac and respiratory

Next to the precise location in 3-D space, other geometric considerations of the IVUS probe during image acquisition are important to be taken in account for an accurate 3-D reconstruction (Roelandt et al., 1994; Thrush et al., 1997). For example, the geometry of the reconstructed vessel can be distorted by a rotation of the catheter during pullback. These changes in the angular orientation of the catheter can be corrected by using analytical calculation based on the Frenet-Serret rules and optimizing the fit after projecting the reconstructed lumen from different rotational angles onto the angiogram images (Briguori et al., 2001; Wahle et al., 1999). Axial movements of the catheter due to the cardiac contraction are another cause for 3-D reconstruction inaccuracies. This geometric artifact can be reduced using a cardiac-gating and spatiotemporal location of the IVUS transducer throughout the pullback (Arbab-Zadeh et al., 1999). However, even if some errors in generating 3-D images can potentially surround withy these geometric assumptions, these corrections help improve the interpretability, usefulness and accuracy of the 3-D reconstructions. Repeatability is also a really important consideration in the accuracy and usefulness of 3-D reconstruction techniques. This aspect is however closely related to the reproducibility of

Offline digitization of IVUS images and retrieval of biplane angiographic images, but also digitization and intense computer processing are both required to obtain a correct

the precise measurement of a longer and curved segment.

development (Jensen et al., 2008; Min et al., 2007; Sano et al., 2006).

**4.3 Geometrically correct 3-D IVUS and advanced data processing** 

motion and the higher radiation exposure during the whole procedure.

the 3-D border-detection process (von Birgelen et al., 1996a).

more time but are have a better accuracy. These 2-D border-detection methods are particularly used when the analysis of only a small number of images is required, e.g. during the guidance of interventional procedures (Sarno et al., 2011).

When a fast analysis of many images is required, highly automated techniques for border detection are used and do not require significant user intervention. For example, 3-D border-detection methods using the inter-slice information can provide fast border detection from a large number of images (Cardinal et al., 2010). A graph-searching approach researching the globally optimal contour path through the image data has been developed on the basis of associated cost values (Zhang et al., 1998). Furthermore, this 2-D frame analysis method allows the results to be propagated down the sequence by using the identified 2-D contours in order to limit the search region. Another 2-D border-detection method uses cost values to find longitudinal contours along the volumetric data. Then, these contours guide the cost function minimization in the transverse 2-D images (Koning et al., 2002). Alternatively, several useful approaches use deformable models to perform an active contour detection (Klingensmith et al., 2000a; Kovalski et al., 2000) (Shekhar et al., 1999). One of them uses a balloon force to inflate a model from the catheter outward toward the luminal and medial-adventitial borders (Kovalski et al., 2000). Another deformable model uses a cylindrical model to manually or automatically approximate the structure of the luminal or medial-adventitial surface, and a deformable model algorithm is then used in a 3- D process to attach the defined structure to the surface of interest (Klingensmith et al., 2000a; Shekhar et al., 1999). All these methods allowing the 3-D border-detection have clearly established their overall usefulness for fast border identification in a large sequence of images (Klingensmith et al., 2000a; Kovalski et al., 2000; Shekhar et al., 1999; von Birgelen et al., 1996a; Zhang et al., 1998).

A major limitation of all these 3-D border-detection methods is the lack of a true gold standard for comparison. Histology sections might represent the more powerful gold standard, but they are only available at autopsy, and the required fixation always induces the tissue to shrink (Siegel et al., 1985). Some researchers have tried to evaluate the accuracy of their methods using cylindrical phantoms, but they did not test accuracy in clinical IVUS images (von Birgelen et al., 1996a). Other studies have compared the detected borders with borders traced manually by a single expert, but the obtained inter-observer variability in manual identification of the luminal and medial-adventitial borders might greatly limit the value of these comparisons in IVUS images (Haas et al., 2000; Zhang et al., 1998). At last, some studies have used multiple expert observers for validation, but the number of analyzed images is seriously limited and not sufficient to assess the ability and accuracy of these algorithms (Klingensmith et al., 2000a; Kovalski et al., 2000; Shekhar et al., 1999). Therefore, there is a need of validation of these techniques in large datasets.

#### **4.2 3-D reconstructions of vessel segments**

All measurements and evaluations made in 2-D tomographic slices are useful for stent sizing or comparisons of lesions to a reference site, but fail to provide a volumetric perspective. To do such volumetric calculations, the border measurements obtained in consecutive 2-D slices of a vessel segment are integrated, the area enclosed by the luminal border and external elastic membrane border is considered for each slice, and the atheroma area is calculated. The 3-D measurement of lumen, plaque, and vessel volumes are usually calculated with Simpson's rule or trapezoidal integration by the multiplying 2-D area and slice thickness (Finet et al., 2003; von Birgelen et al., 1997a). This last method is suitable for

more time but are have a better accuracy. These 2-D border-detection methods are particularly used when the analysis of only a small number of images is required, e.g.

When a fast analysis of many images is required, highly automated techniques for border detection are used and do not require significant user intervention. For example, 3-D border-detection methods using the inter-slice information can provide fast border detection from a large number of images (Cardinal et al., 2010). A graph-searching approach researching the globally optimal contour path through the image data has been developed on the basis of associated cost values (Zhang et al., 1998). Furthermore, this 2-D frame analysis method allows the results to be propagated down the sequence by using the identified 2-D contours in order to limit the search region. Another 2-D border-detection method uses cost values to find longitudinal contours along the volumetric data. Then, these contours guide the cost function minimization in the transverse 2-D images (Koning et al., 2002). Alternatively, several useful approaches use deformable models to perform an active contour detection (Klingensmith et al., 2000a; Kovalski et al., 2000) (Shekhar et al., 1999). One of them uses a balloon force to inflate a model from the catheter outward toward the luminal and medial-adventitial borders (Kovalski et al., 2000). Another deformable model uses a cylindrical model to manually or automatically approximate the structure of the luminal or medial-adventitial surface, and a deformable model algorithm is then used in a 3- D process to attach the defined structure to the surface of interest (Klingensmith et al., 2000a; Shekhar et al., 1999). All these methods allowing the 3-D border-detection have clearly established their overall usefulness for fast border identification in a large sequence of images (Klingensmith et al., 2000a; Kovalski et al., 2000; Shekhar et al., 1999; von Birgelen

A major limitation of all these 3-D border-detection methods is the lack of a true gold standard for comparison. Histology sections might represent the more powerful gold standard, but they are only available at autopsy, and the required fixation always induces the tissue to shrink (Siegel et al., 1985). Some researchers have tried to evaluate the accuracy of their methods using cylindrical phantoms, but they did not test accuracy in clinical IVUS images (von Birgelen et al., 1996a). Other studies have compared the detected borders with borders traced manually by a single expert, but the obtained inter-observer variability in manual identification of the luminal and medial-adventitial borders might greatly limit the value of these comparisons in IVUS images (Haas et al., 2000; Zhang et al., 1998). At last, some studies have used multiple expert observers for validation, but the number of analyzed images is seriously limited and not sufficient to assess the ability and accuracy of these algorithms (Klingensmith et al., 2000a; Kovalski et al., 2000; Shekhar et al., 1999).

All measurements and evaluations made in 2-D tomographic slices are useful for stent sizing or comparisons of lesions to a reference site, but fail to provide a volumetric perspective. To do such volumetric calculations, the border measurements obtained in consecutive 2-D slices of a vessel segment are integrated, the area enclosed by the luminal border and external elastic membrane border is considered for each slice, and the atheroma area is calculated. The 3-D measurement of lumen, plaque, and vessel volumes are usually calculated with Simpson's rule or trapezoidal integration by the multiplying 2-D area and slice thickness (Finet et al., 2003; von Birgelen et al., 1997a). This last method is suitable for

Therefore, there is a need of validation of these techniques in large datasets.

**4.2 3-D reconstructions of vessel segments** 

during the guidance of interventional procedures (Sarno et al., 2011).

et al., 1996a; Zhang et al., 1998).

short and straight vessel segments, such as coronary stented lesions, but it does not allow the precise measurement of a longer and curved segment.

The volumetric approach using 3-D border-detection techniques is currently applied in serial IVUS studies examining atherosclerotic disease progression or regression, allowing the assessment of plaque burden in an entire vessel segment through fast analysis of large image sequences. New interventional approaches also use a volumetric IVUS imaging approach to provide new mechanistic insights, such as innovative techniques aimed at the prevention and treatment of in-stent restenosis correlated with histomorphometry measurements (Mehran et al., 1998; Murata et al., 2002); approaches in understanding the effects of radiation therapy and the arterial remodeling on a stented segment (brachytherapy) (Lekston et al., 2008; Weichert et al., 2003; Zimarino et al., 2002; Zimmermann et al., 2005); or using drug-eluting stents on the neointimal hyperplasia development (Jensen et al., 2008; Min et al., 2007; Sano et al., 2006).

#### **4.3 Geometrically correct 3-D IVUS and advanced data processing**

Since the curvature of vessels is not taken into account with these straight 3-D IVUS methods, this limitation can be overcome by fusing the curvature information provided by biplane angiography or other techniques with the IVUS border information (Schuurbiers et al., 2009; Sherknies et al., 2005; Tu et al., 2010; Wahle et al., 2006). To do so, one common method is to acquire two separate angiographic images from different angles at the beginning of the ultrasound scanning imaging procedure and to use the catheter outline reconstructed from these images as a template for placement of the IVUS-derived contours (Bourantas et al., 2005; Klingensmith et al., 2000b; Sherknies et al., 2005; von Birgelen et al., 1995; Weichert et al., 2003). Another method consists in following the IVUS transducer in time and space throughout the IVUS pullback using biplane angiography, thus the precise locations of IVUS image acquisitions are recorded in sequence and are used as a reconstruction template (Klingensmith et al., 2000b; Miyazaki et al., 2010; Wallace et al., 2005). However, this method might be difficult because of the cardiac and respiratory motion and the higher radiation exposure during the whole procedure.

Next to the precise location in 3-D space, other geometric considerations of the IVUS probe during image acquisition are important to be taken in account for an accurate 3-D reconstruction (Roelandt et al., 1994; Thrush et al., 1997). For example, the geometry of the reconstructed vessel can be distorted by a rotation of the catheter during pullback. These changes in the angular orientation of the catheter can be corrected by using analytical calculation based on the Frenet-Serret rules and optimizing the fit after projecting the reconstructed lumen from different rotational angles onto the angiogram images (Briguori et al., 2001; Wahle et al., 1999). Axial movements of the catheter due to the cardiac contraction are another cause for 3-D reconstruction inaccuracies. This geometric artifact can be reduced using a cardiac-gating and spatiotemporal location of the IVUS transducer throughout the pullback (Arbab-Zadeh et al., 1999). However, even if some errors in generating 3-D images can potentially surround withy these geometric assumptions, these corrections help improve the interpretability, usefulness and accuracy of the 3-D reconstructions. Repeatability is also a really important consideration in the accuracy and usefulness of 3-D reconstruction techniques. This aspect is however closely related to the reproducibility of the 3-D border-detection process (von Birgelen et al., 1996a).

Offline digitization of IVUS images and retrieval of biplane angiographic images, but also digitization and intense computer processing are both required to obtain a correct

Non-Coronary Vessel Exploration Under Intravascular Ultrasound: Principles and Applicability 11

images can be acquired along some body axes (e.g. axial, sagittal, or coronal planes or in a plane oblique to these orthogonal planes) and computed tomography images are typically only acquired in the axial plane, but these images can be reformatted to another orthogonal plane or an oblique plane with image processing techniques (McPherson et al., 2005). Therefore, these plane or oblique images allow only the measurement of relatively short portions of a vessel (only for images that are perpendicular to the vessel axis) and the curvature of the vessel introduces angulation errors in parameter measurement such as the

Color flow IVUS is produced by computer software that detects a difference between the movements of echogenic blood particles from two sequential adjacent frames. Then the blood flow is colored by the software in a red or bleu and is displayed as axial and 3D longitudinal renderings with a very high image resolution (McLeod et al., 2004; Nair et al., 2002). The rendering color of the flow may change from red to orange when there is very fast blood flow (e.g., a tight stenosis). However, the flow velocities cannot be calculated with this technique, image resolution is very high. The color flow IVUS is available on Eagle Eye Gold and the Visions PV 018 catheters (Volcano Corporation, Rancho Cordova, CA) (see Table 1 for specifications). During a color flow IVUS pull-back, the blood flow is displayed in the vessel lumen, pulsing with each cardiac cycle. Unfortunately, the color flow is not gated with the heart rate and cannot be performed when virtual histology images are being acquired. These color flow IVUS are the helpful in distinguishing echolucent disease from luminal blood flow and can also be used to perform peripheral interventions in patients with renal failure or

allergy, avoiding the use of contrast media (Goderie et al., 2010; Irshad et al., 2001).

Whereas conventional grayscale ultrasound images are generated from the intensity of the reflected signals that are collected by the probe, virtual histology IVUS images are obtained from the frequency and intensity of the returning signals and frequency varies depending on the tissues (Vince & Davies, 2004). An histological classification has then be realized by comparing the reflected virtual histology data with true histological sections of diseased vessels, and a color-coded map of the different components of the arterial disease has been established (dark green, fibrous; yellow/green, fibro-fatty; white, calcified; red, necrotic lipid core plaque) (McLeod et al., 2004; Nair et al., 2002). This color-coded map is of major importance since it allows the operator to have detailed information about the constituents and the nature of the plaque (Sarno et al., 2011). The virtual histology IVUS is available on Eagle Eye Gold catheter (Volcano Corporation, Rancho Cordova, CA) (see Table 1 for specifications) and is gated with the heartbeat. During the procedure using the "Volcano" setting, the segment length of the vessel to be examined is determined and the luminal border and the external elastic lamina border of the artery are automatically detected by the edge-tracking computer software but might require some manual adjustments. Then, virtual histology images of the delineated plaque can then be processed online with a few minutes, thus allowing clinical decisions to be made promptly, whereas some additional processing

The accurate measurement of the true luminal diameter, the assessment of the calcific nature of the plaque, the precise delineation of wall morphology, and the ability to carefully

wall thickness (Sherknies et al., 2005).

**4.5 Color IVUS and virtual histology IVUS** 

can be done offline (Vince & Davies, 2004).

**5.1 Percutaneous trans-luminal angioplasty** 

**5. Therapeutic interventions** 

geometrically 3-D reconstruction (Prati et al., 1998). Therefore, all these factors, in addition to the artifacts induced by the respiratory and cardiac motions, limit the *in vivo* applicability of the techniques. Other developments of real-time transducer tracking and online radiofrequency IVUS data acquisition can be integrated into the IVUS console to provide accurate 3-D models of investigated vessels within a few minutes after the acquisition (Nair et al., 2002). These add-ons seem really powerful since they could provide an interactive tool for assessing the diagnostic of the pathology, giving an assessment of luminal dimensions, but also vessel and plaque size from any viewing angle and position. Furthermore, these interactive models could allow rotation and manipulation of these virtual 3-D models on the console computer, authorizing the placement of a virtual stent inside the reconstructed artery, thus permitting a stent with the length and size to be appropriately chosen (Atary et al., 2009; Hong et al., 2010).

Other addendum could be integrated into the geometrically correct 3-D models, including analysis of hemodynamic forces, radiofrequency-derived histology, and 3-D stress maps. Therefore, a more precise morphologic plaque classification is possible with the analysis of radiofrequency data. In fact, the back-scattered radiofrequency IVUS data seems to permit the precise characterization of plaque composition, distinguishing the regions of calcified plaque *vs.* calcified necrosis *vs.* collagen (Nair et al., 2001). Another complement might consist on adding the mechanical properties of the investigated tissue. In fact, elastography represents the way a given tissue is responding to an applied force, as a function of its mechanical properties. Thus, the local mechanical properties of the tissue can be determined by comparing the images of a vessel acquired at 2 different levels of static compression (*e.g.* during systole and diastole steps of the cardiac cycle). This strain image (elastogram) may allow a better understanding of the relation between the progression of a disease and the *in vivo* mechanical properties of the vessel (Baldewsing et al., 2007; Cespedes et al., 1997; de Korte & van der Steen, 2002; Liang et al., 2008).

#### **4.4 Comparison of IVUS with other imaging modalities**

Even if IVUS might represent the most clinically established technique, other methodologies for vessel investigation are also available, such as angiography or tomographic imaging with magnetic resonance imaging (MRI) and computed tomography (CT). The current IVUS imaging plane resolution achieved in vessel cross sections is of 50 to 150 µm, whereas current frame rates (typically 30 frames/s), pullback speeds (usually 0.5 mm/s), and an ECG-gating or sub-sampling yield images at approximately 0.5- to 1.0-mm intervals (Gatta et al., 2009). On the other hand, the in-plane resolution of magnetic resonance imaging is around 1 mm and the through-plane resolution is between 3 to 5 mm with 2-D techniques (Escolar et al., 2006; Schaar et al., 2007), but the magnetic resonance imaging may allow, under several limitation in spatial resolution and signal-to-noise ratios, the atherosclerotic plaque components to be distinguished (Karmonik et al., 2006). At last, the in-plane resolution of computed tomography is less than 1 mm and the minimum through-plane resolution is approximately 1.25 to 1.50 mm. Some contrast-enhanced protocols are sometimes used to differentiate calcified and non-calcified plaque using contrast agents during computed tomography imaging of vessels (Nasir et al., 2010; Pundziute et al., 2008). Another important difference between IVUS and the other imaging modalities concerns the orientation of the imaging plane. In fact, since the IVUS probe is inside the vessel during the

acquisition, the IVUS imaging plane is oriented perpendicular to the vessel axis, which is optimal for assessing cross-sectional dimensions. On the other hand, magnetic resonance images can be acquired along some body axes (e.g. axial, sagittal, or coronal planes or in a plane oblique to these orthogonal planes) and computed tomography images are typically only acquired in the axial plane, but these images can be reformatted to another orthogonal plane or an oblique plane with image processing techniques (McPherson et al., 2005). Therefore, these plane or oblique images allow only the measurement of relatively short portions of a vessel (only for images that are perpendicular to the vessel axis) and the curvature of the vessel introduces angulation errors in parameter measurement such as the wall thickness (Sherknies et al., 2005).

#### **4.5 Color IVUS and virtual histology IVUS**

10 Intravascular Ultrasound

geometrically 3-D reconstruction (Prati et al., 1998). Therefore, all these factors, in addition to the artifacts induced by the respiratory and cardiac motions, limit the *in vivo* applicability of the techniques. Other developments of real-time transducer tracking and online radiofrequency IVUS data acquisition can be integrated into the IVUS console to provide accurate 3-D models of investigated vessels within a few minutes after the acquisition (Nair et al., 2002). These add-ons seem really powerful since they could provide an interactive tool for assessing the diagnostic of the pathology, giving an assessment of luminal dimensions, but also vessel and plaque size from any viewing angle and position. Furthermore, these interactive models could allow rotation and manipulation of these virtual 3-D models on the console computer, authorizing the placement of a virtual stent inside the reconstructed artery, thus permitting a stent with the length and size to be appropriately chosen (Atary et

Other addendum could be integrated into the geometrically correct 3-D models, including analysis of hemodynamic forces, radiofrequency-derived histology, and 3-D stress maps. Therefore, a more precise morphologic plaque classification is possible with the analysis of radiofrequency data. In fact, the back-scattered radiofrequency IVUS data seems to permit the precise characterization of plaque composition, distinguishing the regions of calcified plaque *vs.* calcified necrosis *vs.* collagen (Nair et al., 2001). Another complement might consist on adding the mechanical properties of the investigated tissue. In fact, elastography represents the way a given tissue is responding to an applied force, as a function of its mechanical properties. Thus, the local mechanical properties of the tissue can be determined by comparing the images of a vessel acquired at 2 different levels of static compression (*e.g.* during systole and diastole steps of the cardiac cycle). This strain image (elastogram) may allow a better understanding of the relation between the progression of a disease and the *in vivo* mechanical properties of the vessel (Baldewsing et al., 2007; Cespedes et al., 1997; de

Even if IVUS might represent the most clinically established technique, other methodologies for vessel investigation are also available, such as angiography or tomographic imaging with magnetic resonance imaging (MRI) and computed tomography (CT). The current IVUS imaging plane resolution achieved in vessel cross sections is of 50 to 150 µm, whereas current frame rates (typically 30 frames/s), pullback speeds (usually 0.5 mm/s), and an ECG-gating or sub-sampling yield images at approximately 0.5- to 1.0-mm intervals (Gatta et al., 2009). On the other hand, the in-plane resolution of magnetic resonance imaging is around 1 mm and the through-plane resolution is between 3 to 5 mm with 2-D techniques (Escolar et al., 2006; Schaar et al., 2007), but the magnetic resonance imaging may allow, under several limitation in spatial resolution and signal-to-noise ratios, the atherosclerotic plaque components to be distinguished (Karmonik et al., 2006). At last, the in-plane resolution of computed tomography is less than 1 mm and the minimum through-plane resolution is approximately 1.25 to 1.50 mm. Some contrast-enhanced protocols are sometimes used to differentiate calcified and non-calcified plaque using contrast agents during computed tomography imaging of vessels (Nasir et al., 2010; Pundziute et al., 2008). Another important difference between IVUS and the other imaging modalities concerns the orientation of the imaging plane. In fact, since the IVUS probe is inside the vessel during the acquisition, the IVUS imaging plane is oriented perpendicular to the vessel axis, which is optimal for assessing cross-sectional dimensions. On the other hand, magnetic resonance

al., 2009; Hong et al., 2010).

Korte & van der Steen, 2002; Liang et al., 2008).

**4.4 Comparison of IVUS with other imaging modalities** 

Color flow IVUS is produced by computer software that detects a difference between the movements of echogenic blood particles from two sequential adjacent frames. Then the blood flow is colored by the software in a red or bleu and is displayed as axial and 3D longitudinal renderings with a very high image resolution (McLeod et al., 2004; Nair et al., 2002). The rendering color of the flow may change from red to orange when there is very fast blood flow (e.g., a tight stenosis). However, the flow velocities cannot be calculated with this technique, image resolution is very high. The color flow IVUS is available on Eagle Eye Gold and the Visions PV 018 catheters (Volcano Corporation, Rancho Cordova, CA) (see Table 1 for specifications). During a color flow IVUS pull-back, the blood flow is displayed in the vessel lumen, pulsing with each cardiac cycle. Unfortunately, the color flow is not gated with the heart rate and cannot be performed when virtual histology images are being acquired. These color flow IVUS are the helpful in distinguishing echolucent disease from luminal blood flow and can also be used to perform peripheral interventions in patients with renal failure or allergy, avoiding the use of contrast media (Goderie et al., 2010; Irshad et al., 2001).

Whereas conventional grayscale ultrasound images are generated from the intensity of the reflected signals that are collected by the probe, virtual histology IVUS images are obtained from the frequency and intensity of the returning signals and frequency varies depending on the tissues (Vince & Davies, 2004). An histological classification has then be realized by comparing the reflected virtual histology data with true histological sections of diseased vessels, and a color-coded map of the different components of the arterial disease has been established (dark green, fibrous; yellow/green, fibro-fatty; white, calcified; red, necrotic lipid core plaque) (McLeod et al., 2004; Nair et al., 2002). This color-coded map is of major importance since it allows the operator to have detailed information about the constituents and the nature of the plaque (Sarno et al., 2011). The virtual histology IVUS is available on Eagle Eye Gold catheter (Volcano Corporation, Rancho Cordova, CA) (see Table 1 for specifications) and is gated with the heartbeat. During the procedure using the "Volcano" setting, the segment length of the vessel to be examined is determined and the luminal border and the external elastic lamina border of the artery are automatically detected by the edge-tracking computer software but might require some manual adjustments. Then, virtual histology images of the delineated plaque can then be processed online with a few minutes, thus allowing clinical decisions to be made promptly, whereas some additional processing can be done offline (Vince & Davies, 2004).

#### **5. Therapeutic interventions**

#### **5.1 Percutaneous trans-luminal angioplasty**

The accurate measurement of the true luminal diameter, the assessment of the calcific nature of the plaque, the precise delineation of wall morphology, and the ability to carefully

Non-Coronary Vessel Exploration Under Intravascular Ultrasound: Principles and Applicability 13

patency of arterial occlusive lesions that have undergone angioplasty by reducing technical failure and restenosis rates. However, placing stents is not without risk since ineffective stent expansion can lead to early thrombosis or a stent migration, whereas overexpansion can result in vessel perforation or excessive intimal hyperplasia (Adlakha et al., 2010). Establishing the need for stenting as well as the guiding of a stent deployment has been clearly helped by IVUS. Furthermore, defining the appropriate angioplasty diameter endpoint and confirming adequacy of stent deployment have been reported to clearly improve the long-term patency of a vessel undergoing balloon angioplasty and stenting

The requirement of IVUS in endovascular interventions of venous disease is not as well described as for arterial lesions, while there are many useful indications for IVUS use in venous obstructive lesions (Raju et al., 2010; Raju & Neglen, 2006). In fact, traditional venography for iliac vein obstruction has numerous limitations, and IVUS imaging yields findings not obvious on venography . In fact, intra-luminal webs or external compression and subsequent deformity represent abnormalities that might disturb the diagnostic. Thus, IVUS can provide an accurate assessment of the degree of vein stenosis whereas the venography can sometimes underestimates this stenosis degree by 30% (Nair et al., 2002). In the same way, IVUS allows more appropriately sized venous stents to be placed after venoplasty. Since more and more venous interventions are being performed for acute deep venous thromboses, effort thromboses, or congenital stenosis, the requirement IVUS might represent a powerful adjunct

to delineate the often unclear anatomy related to the venous system (Raju et al., 2010).

advanced endovascular surgeon and training programs.

IVUS requirement has moved rapidly from a purely diagnostic imaging modality to a useful adjunct for vessel endografting to playing an ever-increasing role in peripheral occlusive interventions. This shift has been mainly supported by the miniaturization of the elements, allowing the device and catheter to be as small-profile as the latest stents or balloons, and by the powerful helped that can give IVUS for the most optimal outcomes. While vascular interventions are becoming more and more complex and venture into smaller target vessels, success will be related to the degree of accuracy of the guidance system employed during the procedure. Thus, IVUS is representing an important component of current and future endovascular interventions and should be integrated into the routine practice of the

Adlakha, S., Sheikh, M., Wu, J., Burket, M.W., Pandya, U., Colyer, W., Eltahawy, E., &

Allan, J.J., Smith, R.S., DeJong, S.C., McKay, C.R., & Kerber, R.E. (1998). Intracardiac

(Publication date: 1998/11/06), pp. 921-928, I.S.S.N.: 0894-7317

Cooper, C.J. (2010). Stent fracture in the coronary and peripheral arteries. *J Interv Cardiol*, Vol. 23, No. 4, (Publication date: 2010/09/02), pp. 411-419, I.S.S.N.: 1540-

echocardiographic imaging of the left ventricle from the right ventricle: quantitative experimental evaluation. *J Am Soc Echocardiogr*, Vol. 11, No. 10,

(Waksman et al., 2009).

**6. Conclusion** 

**7. References** 

8183

**5.3 Venous interventions** 

visualize the post-balloon result are both required for a successful percutaneous transluminal angioplasty of peripheral arterial lesions. In that purpose, IVUS images can delineate the luminal and adventitial surfaces of vessel segments, can discriminate between normal and diseased components, can accurately localization and measurement of the thickness of plaque, and can also differentiate calcified and non-calcified vascular lesions (Pundziute et al., 2008; Rodriguez-Granillo et al., 2006). In fact, since the ultrasound energy is strongly reflected by calcified plaque, it appears as a very bright image with dense acoustic shadowing behind it. Not only luminal dimensions and wall thickness determined by IVUS are accurate to within 0.05 mm (Rodriguez-Granillo et al., 2006), the luminal crosssectional areas measured from IVUS correlate well with calculated from biplanar angiograms (Cooper et al., 2001; Irshad et al., 2001). Therefore, IVUS allows the sized balloon or stent to be appropriately chosen can whereas conventional angiography is somewhat limited in its ability to provide sensitive data regarding the effects of percutaneous trans-luminal angioplasty. The IVUS advantage is also to provide a precise evaluation of the lesion morphology, such as the luminal dimensions, the trans-mural lesion characteristics and the area of blood flow. Furthermore, the IVUS determination of plaque volume before and after the procedure offers a real quantitative method to estimate the amount of lesion debulking or displacement and a reference point from which to assess the lesion recurrence/restenosis (Kim et al., 2004; Takeda et al., 2003).

The adjunctive use of IVUS during percutaneous trans-luminal angioplasty has been reported on several studies. For example, in patients with lesions of the superficial femoral artery treated with percutaneous trans-luminal angioplasty, IVUS has been reported to accurately detect the presence of dissections, plaque fractures, internal elastic lamina ruptures, and thinning of the media that occurred during the balloon angioplasty (Oshima et al., 1998; Tang et al., 2010). IVUS has also showed that, after a percutaneous trans-luminal angioplasty, the luminal enlargement is mainly produced by stretching of the arterial wall while the volume of the lesion remains relatively constant (Tang et al., 2010).

After a percutaneous trans-luminal angioplasty the restenosis risk has also been correlated to IVUS findings during the initial procedure, providing important information regarding the post-procedural follow-up and surveillance (Montorsi et al., 2004; Xu et al., 1995). The percutaneous trans-luminal angioplasty of a calcific plaque leads to a higher incidence of dissection than a fibrous lesion, whereas fibrous plaques or concentric lesions without signs of fracture or dissection are prone to have late restenosis after a percutaneous trans-luminal angioplasty (Garcia-Garcia et al., 2009; Su et al., 2009). In the same way, IVUS is also able to readily identify that early restenosis following interventions is associated with luminal thrombus, extensive dissection, and oversized balloon dilatation, while late restenosis correlates with residual stenosis, lower residual lumen surface, undersized balloon use, concentric fibrous plaque, absence of dissection, and absence of calcification (Irshad et al., 2001). IVUS is thus able to enhance percutaneous trans-luminal angioplasty procedures by allowing peri-procedural decisions to be made regarding the need for additional interventions.

#### **5.2 Intravascular stents**

Dissections, elastic recoil, residual stenosis, a significant residual pressure gradient across the lesion, or plaque ulceration with local thrombus accumulation are common indications for an intravascular stent placement after percutaneous trans-luminal angioplasty. Primary stenting is also commonly used in the treatment of certain lesions, especially common iliac or renal disease (Moise et al., 2009). These intravascular stents are used to increase the patency of arterial occlusive lesions that have undergone angioplasty by reducing technical failure and restenosis rates. However, placing stents is not without risk since ineffective stent expansion can lead to early thrombosis or a stent migration, whereas overexpansion can result in vessel perforation or excessive intimal hyperplasia (Adlakha et al., 2010).

Establishing the need for stenting as well as the guiding of a stent deployment has been clearly helped by IVUS. Furthermore, defining the appropriate angioplasty diameter endpoint and confirming adequacy of stent deployment have been reported to clearly improve the long-term patency of a vessel undergoing balloon angioplasty and stenting (Waksman et al., 2009).

#### **5.3 Venous interventions**

12 Intravascular Ultrasound

visualize the post-balloon result are both required for a successful percutaneous transluminal angioplasty of peripheral arterial lesions. In that purpose, IVUS images can delineate the luminal and adventitial surfaces of vessel segments, can discriminate between normal and diseased components, can accurately localization and measurement of the thickness of plaque, and can also differentiate calcified and non-calcified vascular lesions (Pundziute et al., 2008; Rodriguez-Granillo et al., 2006). In fact, since the ultrasound energy is strongly reflected by calcified plaque, it appears as a very bright image with dense acoustic shadowing behind it. Not only luminal dimensions and wall thickness determined by IVUS are accurate to within 0.05 mm (Rodriguez-Granillo et al., 2006), the luminal crosssectional areas measured from IVUS correlate well with calculated from biplanar angiograms (Cooper et al., 2001; Irshad et al., 2001). Therefore, IVUS allows the sized balloon or stent to be appropriately chosen can whereas conventional angiography is somewhat limited in its ability to provide sensitive data regarding the effects of percutaneous trans-luminal angioplasty. The IVUS advantage is also to provide a precise evaluation of the lesion morphology, such as the luminal dimensions, the trans-mural lesion characteristics and the area of blood flow. Furthermore, the IVUS determination of plaque volume before and after the procedure offers a real quantitative method to estimate the amount of lesion debulking or displacement and a reference point from which to assess the

The adjunctive use of IVUS during percutaneous trans-luminal angioplasty has been reported on several studies. For example, in patients with lesions of the superficial femoral artery treated with percutaneous trans-luminal angioplasty, IVUS has been reported to accurately detect the presence of dissections, plaque fractures, internal elastic lamina ruptures, and thinning of the media that occurred during the balloon angioplasty (Oshima et al., 1998; Tang et al., 2010). IVUS has also showed that, after a percutaneous trans-luminal angioplasty, the luminal enlargement is mainly produced by stretching of the arterial wall

After a percutaneous trans-luminal angioplasty the restenosis risk has also been correlated to IVUS findings during the initial procedure, providing important information regarding the post-procedural follow-up and surveillance (Montorsi et al., 2004; Xu et al., 1995). The percutaneous trans-luminal angioplasty of a calcific plaque leads to a higher incidence of dissection than a fibrous lesion, whereas fibrous plaques or concentric lesions without signs of fracture or dissection are prone to have late restenosis after a percutaneous trans-luminal angioplasty (Garcia-Garcia et al., 2009; Su et al., 2009). In the same way, IVUS is also able to readily identify that early restenosis following interventions is associated with luminal thrombus, extensive dissection, and oversized balloon dilatation, while late restenosis correlates with residual stenosis, lower residual lumen surface, undersized balloon use, concentric fibrous plaque, absence of dissection, and absence of calcification (Irshad et al., 2001). IVUS is thus able to enhance percutaneous trans-luminal angioplasty procedures by allowing peri-procedural decisions to be made regarding the need for additional interventions.

Dissections, elastic recoil, residual stenosis, a significant residual pressure gradient across the lesion, or plaque ulceration with local thrombus accumulation are common indications for an intravascular stent placement after percutaneous trans-luminal angioplasty. Primary stenting is also commonly used in the treatment of certain lesions, especially common iliac or renal disease (Moise et al., 2009). These intravascular stents are used to increase the

lesion recurrence/restenosis (Kim et al., 2004; Takeda et al., 2003).

**5.2 Intravascular stents** 

while the volume of the lesion remains relatively constant (Tang et al., 2010).

The requirement of IVUS in endovascular interventions of venous disease is not as well described as for arterial lesions, while there are many useful indications for IVUS use in venous obstructive lesions (Raju et al., 2010; Raju & Neglen, 2006). In fact, traditional venography for iliac vein obstruction has numerous limitations, and IVUS imaging yields findings not obvious on venography . In fact, intra-luminal webs or external compression and subsequent deformity represent abnormalities that might disturb the diagnostic. Thus, IVUS can provide an accurate assessment of the degree of vein stenosis whereas the venography can sometimes underestimates this stenosis degree by 30% (Nair et al., 2002). In the same way, IVUS allows more appropriately sized venous stents to be placed after venoplasty. Since more and more venous interventions are being performed for acute deep venous thromboses, effort thromboses, or congenital stenosis, the requirement IVUS might represent a powerful adjunct to delineate the often unclear anatomy related to the venous system (Raju et al., 2010).

#### **6. Conclusion**

IVUS requirement has moved rapidly from a purely diagnostic imaging modality to a useful adjunct for vessel endografting to playing an ever-increasing role in peripheral occlusive interventions. This shift has been mainly supported by the miniaturization of the elements, allowing the device and catheter to be as small-profile as the latest stents or balloons, and by the powerful helped that can give IVUS for the most optimal outcomes. While vascular interventions are becoming more and more complex and venture into smaller target vessels, success will be related to the degree of accuracy of the guidance system employed during the procedure. Thus, IVUS is representing an important component of current and future endovascular interventions and should be integrated into the routine practice of the advanced endovascular surgeon and training programs.

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**2** 

*Japan* 

**Plaque Regression and Stability** 

Tadateru Takayama and Atsushi Hirayama

Satoshi Saito, Takafumi Hiro,

*Keiai Hospital & Nihon University* 

**Evaluated by Intravascular Ultrasound** 

Although atherosclerosis seems to be continuously progressive and irreversible, it has been being demonstrated that substantial regression or stabilization of atherosclerotic lesions can occur by some interventions improving its determinants. However, the concepts of plaque regression or stabilization are not so new. It has been reviewed that the first reported observation of plaque regression could be found in the 1920s (Wissler, 1976), in which switching cholesterol-fed rabbits to low-fat chow over 2–3 years resulted in arterial lesions becoming more fibrous with a reduced lipid content. Later on, as the earliest prospective studies, a couple of previous studies in the 1950s have shown distinctive facts of plaque shrinkage or favorable change of its tissue components due to special diet therapy or some specific medications. In 1957 Friedman M et al. documented a result from prospective, interventional study demonstrating substantial shrinkage of atherosclerotic lesions performed in cholesterol-fed rabbits (Friedman, 1957). The dietary regimen raised total plasma cholesterol to around 1,000 mg/dl, and then animals received intravenous injections of phosphatidylcholine. They reported that after less than a week or so the size of the plaques as well as cholesterol stores within the arterial wall were significantly reduced. This striking report with some following supportive studies and reviews (Wissler, 1976; Armstrong, 1976; Malinow, 1983) has been surprisingly ignored for long years because of some beliefs regarding distinctive persistent characteristics of atherosclerosis, the negative history of which was reviewed by Stein Y, et al (Stein , 2001). However, various additional facts of plaque regression by some interventions have been demonstrated in other type of animal studies (Maruffo , 1968; Armstrong , 1970) since then without strong interests among

The first prospective study demonstrating plaque regression in humans might be the one documented by Ost CR, et al. in 1967(Ost, 1967). In the study, approximately 10% of patients treated with niacin showed improved femoral angiograms. Numerous additional larger trials of lipid lowering have then shown angiographic evidence of regression. However, though statistically significant, the resulted effects were very small (Brown, 1993), in which the improvement of percent stenosis of lumen were at most 2%. Accumulations of clinical evidences demonstrating the benefits of lipid-lowering in clinical outcome therefore yield

**1. Introduction** 

general cardiologists.

**and Coronary Angioscopy: A Review** 

*Image Anal*, Vol. 10, No. 4, (Publication date: 2006/04/29), pp. 615-631, I.S.S.N.: 1361-8415


## **Plaque Regression and Stability Evaluated by Intravascular Ultrasound and Coronary Angioscopy: A Review**

 Satoshi Saito, Takafumi Hiro, Tadateru Takayama and Atsushi Hirayama *Keiai Hospital & Nihon University Japan* 

#### **1. Introduction**

22 Intravascular Ultrasound

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The first prospective study demonstrating plaque regression in humans might be the one documented by Ost CR, et al. in 1967(Ost, 1967). In the study, approximately 10% of patients treated with niacin showed improved femoral angiograms. Numerous additional larger trials of lipid lowering have then shown angiographic evidence of regression. However, though statistically significant, the resulted effects were very small (Brown, 1993), in which the improvement of percent stenosis of lumen were at most 2%. Accumulations of clinical evidences demonstrating the benefits of lipid-lowering in clinical outcome therefore yield

Plaque Regression and Stability Evaluated by

of these methods is as follows.

(Kawasaki , 2002).

Intravascular Ultrasound and Coronary Angioscopy: A Review 25

Volume: This is obtained from the absolute nominal change between the baseline and the follow-up period in percent value of plaque volume compared to EEM volume; 2) Percent Change in Plaque Volume: This is calculated from (follow-up plaque volume minus baseline plaque volume) divided by (follow-up plaque volume) times 100. It has been suggested that the former index might be more closely related to clinical outcome (Nicholls, 2010). However, this index would show "regression" even in case of increase in EEM volume (positive remodeling) without any change in plaque volume itself. The latter one may be more reflected to a particular change of a special plaque of interest. Although it has not yet been directly proved that these IVUS parameters are useful surrogate markers for clinical outcome, IVUS have demonstrated a remarkable change in plaque volume by use of statins. Furthermore, current technologies of IVUS can perform tissue characterization of plaque components with a color-coded image. In Japan, three color-IVUS systems are now commercially available. In addition, various other methods have been proposed with sophisticated mathematical models to detect tissue-specific acoustic properties. An overview

It was originally expected that tissue components within plaque could be identified from the video-intensity pattern of IVUS images. Subsequent studies, however, demonstrated significant limitations of tissue characterization by IVUS intensity patterns alone, especially in discriminating fibrous and fatty tissues or in assessing plaque vulnerability (Hiro, 1996; Hiro, 1997; Kimura, 1995; Jeremias, 1999). To overcome this limitation, special attempts to analyze the echo-signals including the raw radiofrequency (RF) ultrasound signal that comes from plaque segments. The echo signal, which is originally emitted as a pulse wave from the ultrasound catheter tip, is produced at the interface between the two materials having different acoustic impedances. There are several interfaces within plaque, so timeseries RF signal is then formed according to the degree of acoustic impedance mismatches and geometrical structure and distribution of each tissue components. Therefore, it can be expected that detection of special acoustic characteristics for each tissue component can allow us to visually identify it. Based upon this hypothesis, several successful studies have

This system visualizes the distribution of quantitative power or energy of echo for each segment of plaque using fast-Fourier transform of time-series RF signal. The total energy range is divided into four local ranges which correspond to four kinds of tissue components. This simple algorithm provides a high accuracy with a reliable sensitivity and specificity

The echo spectrum is first obtained by autoregressive spectral analysis for each portion of plaque. Autoregressive spectral analysis can obtain a spectrum of time-series signal, which has a different mathematical processing from fast-Fourier transform. Eight kinds of acoustic parameters are then measured for each spectrum. A classification tree which flows according to the values of the eight parameters makes the final diagnosis to discriminate four tissue types. The classification tree is already prepared with previous survey using

been reported, including the three commercially available machines.

**2.1.2 Autoregressive spectral analysis (Virtual histology®)** 

**2.1.1 Integrated backscatter analysis (IB-IVUS®)** 

tissue-known echo-samples (Nair, 2002). (Figure 1)

this kind of "angiographic paradox". This paradox suggested that the improvement of clinical outcome was not necessarily associated with the improvement of arterial lumen diameter. However, various pathological findings have resolved this enigma. First, the answer came from the recognition of a phenomenon called as vascular remodling (Glagov, 1987). The next answer was regarding the realization that lipid-rich, vulnerable plaques have a central role in acute coronary syndromes (Fuster, 1992; Libby, 1995). Vulnerable plaques are usually small in size and cause less than 50% occlusion. The vulnerable plaques are generally filled with intracellular and extracellular lipid, rich in macrophages and tissue factor, having low concentrations of smooth muscle cells as well as a thin fibrous cap (Shah, 2003; Falk, 1995). Rupture of a vulnerable plaque provokes the formation of a robust thrombosis causing critical lumen occlusion. It has been estimated that lipid lowering, therapy does not induce lumen expansion but rather has most impact on risk reduction by the remodeling and stabilization of small, rupture-prone lesions.

Based on these past histories, a new era of medication strategy had come in late 1980s with an appearance of 3-hydroxy-3-methyl-glutaryl coenzyme A reductase inhibitors (statins) in clinical setting. Many large-scale pivotal clinical trials have then shown that statins remarkably reduced both atherogenic lipoproteins as well as cardiovascular morbidity and mortality (Scandinavian Simvastatin Survival Study Group, 1994; Sacks, 1996; The Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) Study Group, 1998). However, the angiographic paradox still exists in this era even with a strong statin (Ballantyne, 2008). To overcome the paradox by in-vivo detection of plaque regression and stabilization, new development of commercially available intravascular imaging modalities contributed a lot to understanding the mechanism of statins for reducing cardiovascular events in patients with coronary artery disease. These modalities can visualize plaque size and its serial changes, and can even visualize tissue components within plaque to be able to estimate plaque vulnerability.

In this chapter, readers will be able to describe the imaging mechanisms of intravascular ultrasound and coronary angioscopy especially for observing plaque regression and stabilization. Then, a variety of important evidences of plaque regression and stabilization evaluated by these systems will be introduced in order to understand the clinical feasibility of these modalities as well as to recognize current clinical cutting edge of knowledge regarding plaque regression and stabilization.

#### **2. Assessment of plaque regression and stability**

#### **2.1 Assessment with intravascular ultrasound**

Intravascular ultrasound (IVUS) can provide gray-scale images with an accurate representation of plaque cross-sectional areas and volumes. Therefore, IVUS can follow invivo plaque volumes serially in same patients. IVUS imaging is performed with an automatic catheter-pullback system to acquire consecutive cross-sections of arterial wall. Cross-sectional plaque area for each section can be measured by tracings of lumen-intima border as well as media-adventitia (External elastic membrane area: EEM area). The difference of the two areas corresponds to the plaque area (intima-media complex area). The product of a certain constant distance-related interval and the integration of these plaque areas calculated from each cross-section resulted in total plaque volume of interest. The certain interval varied from 0.1 mm to 10 mm according to the study concept. The IVUS indices used in major clinical trials were as follows: 1) Nominal Change of Percent Plaque

this kind of "angiographic paradox". This paradox suggested that the improvement of clinical outcome was not necessarily associated with the improvement of arterial lumen diameter. However, various pathological findings have resolved this enigma. First, the answer came from the recognition of a phenomenon called as vascular remodling (Glagov, 1987). The next answer was regarding the realization that lipid-rich, vulnerable plaques have a central role in acute coronary syndromes (Fuster, 1992; Libby, 1995). Vulnerable plaques are usually small in size and cause less than 50% occlusion. The vulnerable plaques are generally filled with intracellular and extracellular lipid, rich in macrophages and tissue factor, having low concentrations of smooth muscle cells as well as a thin fibrous cap (Shah, 2003; Falk, 1995). Rupture of a vulnerable plaque provokes the formation of a robust thrombosis causing critical lumen occlusion. It has been estimated that lipid lowering, therapy does not induce lumen expansion but rather has most impact on risk reduction by

Based on these past histories, a new era of medication strategy had come in late 1980s with an appearance of 3-hydroxy-3-methyl-glutaryl coenzyme A reductase inhibitors (statins) in clinical setting. Many large-scale pivotal clinical trials have then shown that statins remarkably reduced both atherogenic lipoproteins as well as cardiovascular morbidity and mortality (Scandinavian Simvastatin Survival Study Group, 1994; Sacks, 1996; The Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) Study Group, 1998). However, the angiographic paradox still exists in this era even with a strong statin (Ballantyne, 2008). To overcome the paradox by in-vivo detection of plaque regression and stabilization, new development of commercially available intravascular imaging modalities contributed a lot to understanding the mechanism of statins for reducing cardiovascular events in patients with coronary artery disease. These modalities can visualize plaque size and its serial changes, and can even visualize tissue components within plaque to be able to

In this chapter, readers will be able to describe the imaging mechanisms of intravascular ultrasound and coronary angioscopy especially for observing plaque regression and stabilization. Then, a variety of important evidences of plaque regression and stabilization evaluated by these systems will be introduced in order to understand the clinical feasibility of these modalities as well as to recognize current clinical cutting edge of knowledge

Intravascular ultrasound (IVUS) can provide gray-scale images with an accurate representation of plaque cross-sectional areas and volumes. Therefore, IVUS can follow invivo plaque volumes serially in same patients. IVUS imaging is performed with an automatic catheter-pullback system to acquire consecutive cross-sections of arterial wall. Cross-sectional plaque area for each section can be measured by tracings of lumen-intima border as well as media-adventitia (External elastic membrane area: EEM area). The difference of the two areas corresponds to the plaque area (intima-media complex area). The product of a certain constant distance-related interval and the integration of these plaque areas calculated from each cross-section resulted in total plaque volume of interest. The certain interval varied from 0.1 mm to 10 mm according to the study concept. The IVUS indices used in major clinical trials were as follows: 1) Nominal Change of Percent Plaque

the remodeling and stabilization of small, rupture-prone lesions.

estimate plaque vulnerability.

regarding plaque regression and stabilization.

**2.1 Assessment with intravascular ultrasound** 

**2. Assessment of plaque regression and stability** 

Volume: This is obtained from the absolute nominal change between the baseline and the follow-up period in percent value of plaque volume compared to EEM volume; 2) Percent Change in Plaque Volume: This is calculated from (follow-up plaque volume minus baseline plaque volume) divided by (follow-up plaque volume) times 100. It has been suggested that the former index might be more closely related to clinical outcome (Nicholls, 2010). However, this index would show "regression" even in case of increase in EEM volume (positive remodeling) without any change in plaque volume itself. The latter one may be more reflected to a particular change of a special plaque of interest. Although it has not yet been directly proved that these IVUS parameters are useful surrogate markers for clinical outcome, IVUS have demonstrated a remarkable change in plaque volume by use of statins.

Furthermore, current technologies of IVUS can perform tissue characterization of plaque components with a color-coded image. In Japan, three color-IVUS systems are now commercially available. In addition, various other methods have been proposed with sophisticated mathematical models to detect tissue-specific acoustic properties. An overview of these methods is as follows.

It was originally expected that tissue components within plaque could be identified from the video-intensity pattern of IVUS images. Subsequent studies, however, demonstrated significant limitations of tissue characterization by IVUS intensity patterns alone, especially in discriminating fibrous and fatty tissues or in assessing plaque vulnerability (Hiro, 1996; Hiro, 1997; Kimura, 1995; Jeremias, 1999). To overcome this limitation, special attempts to analyze the echo-signals including the raw radiofrequency (RF) ultrasound signal that comes from plaque segments. The echo signal, which is originally emitted as a pulse wave from the ultrasound catheter tip, is produced at the interface between the two materials having different acoustic impedances. There are several interfaces within plaque, so timeseries RF signal is then formed according to the degree of acoustic impedance mismatches and geometrical structure and distribution of each tissue components. Therefore, it can be expected that detection of special acoustic characteristics for each tissue component can allow us to visually identify it. Based upon this hypothesis, several successful studies have been reported, including the three commercially available machines.

#### **2.1.1 Integrated backscatter analysis (IB-IVUS®)**

This system visualizes the distribution of quantitative power or energy of echo for each segment of plaque using fast-Fourier transform of time-series RF signal. The total energy range is divided into four local ranges which correspond to four kinds of tissue components. This simple algorithm provides a high accuracy with a reliable sensitivity and specificity (Kawasaki , 2002).

#### **2.1.2 Autoregressive spectral analysis (Virtual histology®)**

The echo spectrum is first obtained by autoregressive spectral analysis for each portion of plaque. Autoregressive spectral analysis can obtain a spectrum of time-series signal, which has a different mathematical processing from fast-Fourier transform. Eight kinds of acoustic parameters are then measured for each spectrum. A classification tree which flows according to the values of the eight parameters makes the final diagnosis to discriminate four tissue types. The classification tree is already prepared with previous survey using tissue-known echo-samples (Nair, 2002). (Figure 1)

Plaque Regression and Stability Evaluated by

using this method (Murashige, 2005). (Figure 3)

**2.1.5 Fractal analysis** 

**2.1.6 Wavelet analysis** 

Fig. 3. Wavelet analysis

**2.1.7 Neural network theory** 

stripe pattern. Incited from (Murashige, 2005)

Intravascular Ultrasound and Coronary Angioscopy: A Review 27

This method obtained the value of fractal dimension, which represents how complex the echo-segment is from each plaque portion. It was found that the echo-signal was more

Wavelet analysis of RF IVUS signals is a novel mathematical model for assessing focal geometrical differences within arterial walls. Color coding of the wavelet correlation coefficient derived from the RF signal allows detection of changes in the geometrical profile of time-series signals to derive an image of plaque components (Figure 3). Murashige et al. showed that lipid-rich plaques could be detected with acceptable sensitivity and specificity

Wavelet correlation mapping of the RF signal from lipid-rich plaque revealed a unique

This method analyzes the RF signal with a self-learning system that resembles real neural actions in humans or animals. Kubota used a k-nearest neighbor method to classify tissue types of coronary plaque (Kubota , 2007). The k-nearest neighbor method is like a decisionmaking system by a majority vote. When a time-series signal is evaluated, there are numerous parameters obtained by a signal-processing system. The parameters (total number = n) from a signal area of interest, therefore, can yield a coordinate as: (x1,x2,x3,…..xn) (Let's call now point P). In such space, previously prepared coordinates obtained from the tissue-known signal exist around the point P. When you look around the point P for a constant distance, you can count the number of tissue-known points. If the majority of tissue-known points is from lipidic tissue, then the point P- corresponded tissue area is considered to be a lipidic tissue. Kubota R et al. modified this k-nearest method to enhance the accuracy of tissue characterization by IVUS. Sathyanarayana S, et al. performed

complex from lipidic tissue compared to fibrous tissue (Hiro, 2000).

#### Fig. 1. VH-IVUS

A pre-defined classification tree according to eight acoustic parameters identifies four kind of tissues.

#### **2.1.3 Attenuation-slope analysis**

The ultrasound energy is attenuated when running through tissues. The degree of attenuation depends upon the frequency. It is hypothesized that the frequency-dependence of ultrasound attenuation is different according to the tissue type. This system colorized the degree of frequency-dependent of ultrasound attenuation (Wilson , 1994).

#### **2.1.4 Angle-dependence analysis**

It has been demonstrated that intravascular ultrasound (IVUS) backscatter from fibrous tissue is strongly dependent on the ultrasound beam angle of incidence (Picano , 1985). It was found that this technique provides an accurate representation of the thickness of the fibrous cap in atherosclerotic plaque, the echo-intensity of which is highly angle-dependent (Hiro , 2001). (Figure 2)

Highly angle-dependent area (yellow) is accurately corresponded to fibrous cap. Incited from (Hiro, 2001)

#### **2.1.5 Fractal analysis**

26 Intravascular Ultrasound

A pre-defined classification tree according to eight acoustic parameters identifies four kind

The ultrasound energy is attenuated when running through tissues. The degree of attenuation depends upon the frequency. It is hypothesized that the frequency-dependence of ultrasound attenuation is different according to the tissue type. This system colorized the

It has been demonstrated that intravascular ultrasound (IVUS) backscatter from fibrous tissue is strongly dependent on the ultrasound beam angle of incidence (Picano , 1985). It was found that this technique provides an accurate representation of the thickness of the fibrous cap in atherosclerotic plaque, the echo-intensity of which is highly angle-dependent

Highly angle-dependent area (yellow) is accurately corresponded to fibrous cap. Incited

degree of frequency-dependent of ultrasound attenuation (Wilson , 1994).

Fig. 1. VH-IVUS

**2.1.3 Attenuation-slope analysis** 

**2.1.4 Angle-dependence analysis** 

Fig. 2. Angle-dependence analysis

from (Hiro, 2001)

(Hiro , 2001). (Figure 2)

of tissues.

This method obtained the value of fractal dimension, which represents how complex the echo-segment is from each plaque portion. It was found that the echo-signal was more complex from lipidic tissue compared to fibrous tissue (Hiro, 2000).

#### **2.1.6 Wavelet analysis**

Wavelet analysis of RF IVUS signals is a novel mathematical model for assessing focal geometrical differences within arterial walls. Color coding of the wavelet correlation coefficient derived from the RF signal allows detection of changes in the geometrical profile of time-series signals to derive an image of plaque components (Figure 3). Murashige et al. showed that lipid-rich plaques could be detected with acceptable sensitivity and specificity using this method (Murashige, 2005). (Figure 3)

#### Fig. 3. Wavelet analysis

Wavelet correlation mapping of the RF signal from lipid-rich plaque revealed a unique stripe pattern. Incited from (Murashige, 2005)

#### **2.1.7 Neural network theory**

This method analyzes the RF signal with a self-learning system that resembles real neural actions in humans or animals. Kubota used a k-nearest neighbor method to classify tissue types of coronary plaque (Kubota , 2007). The k-nearest neighbor method is like a decisionmaking system by a majority vote. When a time-series signal is evaluated, there are numerous parameters obtained by a signal-processing system. The parameters (total number = n) from a signal area of interest, therefore, can yield a coordinate as: (x1,x2,x3,…..xn) (Let's call now point P). In such space, previously prepared coordinates obtained from the tissue-known signal exist around the point P. When you look around the point P for a constant distance, you can count the number of tissue-known points. If the majority of tissue-known points is from lipidic tissue, then the point P- corresponded tissue area is considered to be a lipidic tissue. Kubota R et al. modified this k-nearest method to enhance the accuracy of tissue characterization by IVUS. Sathyanarayana S, et al. performed

Plaque Regression and Stability Evaluated by

• Thin cap with large lipid core

• Fissured plaque

• Stenosis more than 90% As the minor criteria:

• Superficial calcified nodule

• Outward (positive) remodelling

• Intraplaque hemorrhage • Endothelial dysfunction

modern technology.

optimal systemic therapies.

• Glistening yellow by coronary angioscopy

So what criteria can we examine generally in all patients?

**2.3 Problems in assessing plaque vulnerability** 

following characteristics can be identified as vulnerable plaque:

• Endothelial denudation with superficial platelet aggregation

Intravascular Ultrasound and Coronary Angioscopy: A Review 29

Naghavi M, and a lot of famous investigators collaborated to try to establish the criteria for defining vulnerable plaques(Naghavi , 2003). As the major criteria, the plaque with the

IVUS and coronary angioscopy can actually represent the thickness of thin fibrous cap and the volume of lipid-rich core. However, Imoto K, et al demonstrated in the study with a biomechanical simulation of in-plaque stress distribution that plaques with the same thickness of fibrous cap does not necessarily indicate the same vulnerability to rupture (Imoto, 2005). Ambrose JA documented a get-to-the-point criticism in search of the vulnerable plaque(Ambrose, 2008). He proposed several prerequisites to establish the way

1. "Vulnerable plaque" caused by a thin-capped fibroatheroma can be identified with

4. The natural history of a "vulnerable plaque" has been identified in patients treated with

5. An interventional approach applied locally or regionally to an asymptomatic"vulnerable plaque" is proven to reduce future events relative to the best systemic medical therapy. He criticized that among these prerequisites, only the first is currently possible, but the others are not yet established and require further study. We have to realize that thin-capped fibro-atheroma is not a single cause of acute coronary syndrome. Erosion, inflammatory cell infilitration, intraplaque hemorrhage or local endothelial dysfunction should be also evaluated. Fukumoto Y, et al. has reported that color mapping of shear stress along plaque surface using IVUS images is useful for identifying future rupture point(Fukumoto, 2008), since it was found that local concentration of shear stress is related to a trigger of plaque rupture. Therefore, numerous local risk factor should be considered for identifying the vulnerable plaque. Even when the method is established, still we have additional problems. We have to possess a detailed data on the likelihood of a cardiac event for a proven "vulnerable plaque." For example, if only 5% of a given plaque type as identified will develop an event on follow-up, all 20 of these plaques will need to be treated with a new procedure to prevent 1 event, that is, NNT=20(Ambrose, 2008). Is this allowed in using the expensive stent therapy? Therefore, a well-designed clinical trial should be performed to prove the clinical feasibility of preventive therapy for a particular plaque which is identified as vulnerable.

to identify vulnerable plaque for distinctive improving patient vulnerability.

2. A "vulnerable plaque" caused by plaque erosion should be identifiable. 3. The number of "vulnerable plaques" is known, and the number is limited.

• Active inflammation (monocyte/macrophage and sometimes T-cell infiltration)

this kind of analysis in analyzing spectral similarity of the RF signal (Sathyanarayana , 2009). It was hypothesized that each tissue component has a special characteristic spectrum shape. This system is now commercially available with a system name, iMap ® (Figure 4). This system can identify four kinds of tissue, which definitions are slightly different from the one used in VH-IVUS. The imaging system is unique, in which the confidence level of identification of tissue types is represented the brightness of each color corresponded to each tissue type. The brightness of confidence level represents the degree of majority in the decision-making space of the k-nearest neighbor method.

#### Fig. 4. iMap system.

The system of iMap perform color mapping of four different tissue types. Confidence level of each tissue identification is reflected on the brightness of each color. CL:Confidence level

#### **2.2 Assessment with coronary angioscopy**

Coronary angioscopy provides a full-color perspective of the intravascular surface morphology of plaque. This technique also accurately represents the presence of thrombi. In this method, vulnerable plaques are detected as yellow plaques compared to the normal surface which is depicted as white. The degree of yellow grade of the plaque surface is corresponded to how rich lipidic components are under the plaque surface or how thin the thickness of fibrous cap is within the plaque. It has been documented that the degree of yellowness of plaque as well as the number of yellow plaque observed are related to plaque vulnerability and poor patient prognosis in cardiovascular outcome (Kodama , 2000; Ueda , 1997; Ueda , 2004; Naghavi , 2003; Asakura , 2001; Ohtani , 2006; Mizuno, 1992). This modality together with IVUS has provided various aspects of plaque regression and its stability.

#### **2.3 Problems in assessing plaque vulnerability**

Naghavi M, and a lot of famous investigators collaborated to try to establish the criteria for defining vulnerable plaques(Naghavi , 2003). As the major criteria, the plaque with the following characteristics can be identified as vulnerable plaque:


28 Intravascular Ultrasound

this kind of analysis in analyzing spectral similarity of the RF signal (Sathyanarayana , 2009). It was hypothesized that each tissue component has a special characteristic spectrum shape. This system is now commercially available with a system name, iMap ® (Figure 4). This system can identify four kinds of tissue, which definitions are slightly different from the one used in VH-IVUS. The imaging system is unique, in which the confidence level of identification of tissue types is represented the brightness of each color corresponded to each tissue type. The brightness of confidence level represents the degree of majority in the

The system of iMap perform color mapping of four different tissue types. Confidence level of each tissue identification is reflected on the brightness of each color. CL:Confidence level

Coronary angioscopy provides a full-color perspective of the intravascular surface morphology of plaque. This technique also accurately represents the presence of thrombi. In this method, vulnerable plaques are detected as yellow plaques compared to the normal surface which is depicted as white. The degree of yellow grade of the plaque surface is corresponded to how rich lipidic components are under the plaque surface or how thin the thickness of fibrous cap is within the plaque. It has been documented that the degree of yellowness of plaque as well as the number of yellow plaque observed are related to plaque vulnerability and poor patient prognosis in cardiovascular outcome (Kodama , 2000; Ueda , 1997; Ueda , 2004; Naghavi , 2003; Asakura , 2001; Ohtani , 2006; Mizuno, 1992). This modality together with IVUS has provided various aspects of plaque

decision-making space of the k-nearest neighbor method.

Fig. 4. iMap system.

regression and its stability.

**2.2 Assessment with coronary angioscopy** 

• Stenosis more than 90%

As the minor criteria:


So what criteria can we examine generally in all patients?

IVUS and coronary angioscopy can actually represent the thickness of thin fibrous cap and the volume of lipid-rich core. However, Imoto K, et al demonstrated in the study with a biomechanical simulation of in-plaque stress distribution that plaques with the same thickness of fibrous cap does not necessarily indicate the same vulnerability to rupture (Imoto, 2005). Ambrose JA documented a get-to-the-point criticism in search of the vulnerable plaque(Ambrose, 2008). He proposed several prerequisites to establish the way to identify vulnerable plaque for distinctive improving patient vulnerability.


He criticized that among these prerequisites, only the first is currently possible, but the others are not yet established and require further study. We have to realize that thin-capped fibro-atheroma is not a single cause of acute coronary syndrome. Erosion, inflammatory cell infilitration, intraplaque hemorrhage or local endothelial dysfunction should be also evaluated. Fukumoto Y, et al. has reported that color mapping of shear stress along plaque surface using IVUS images is useful for identifying future rupture point(Fukumoto, 2008), since it was found that local concentration of shear stress is related to a trigger of plaque rupture. Therefore, numerous local risk factor should be considered for identifying the vulnerable plaque. Even when the method is established, still we have additional problems.

We have to possess a detailed data on the likelihood of a cardiac event for a proven "vulnerable plaque." For example, if only 5% of a given plaque type as identified will develop an event on follow-up, all 20 of these plaques will need to be treated with a new procedure to prevent 1 event, that is, NNT=20(Ambrose, 2008). Is this allowed in using the expensive stent therapy? Therefore, a well-designed clinical trial should be performed to prove the clinical feasibility of preventive therapy for a particular plaque which is identified as vulnerable.

Plaque Regression and Stability Evaluated by

**Event) (Okazaki, 2004)** 

JAPAN-ACS study which is discussed next.

**Acute Coronary Syndrome) (Hiro, 2009)** 

Intravascular Ultrasound and Coronary Angioscopy: A Review 31

primary efficacy parameter of PAV, the mean decrease was −0.98% and the median was −0.79% (P<0.001 compared with baseline). For the second primary efficacy parameter, change in atheroma volume in the 10-mm subsegment with the greatest disease severity, the mean change was −6.1 mm3, and the median change was −5.6 mm3 (P<0.001 compared with baseline). This change represents a median reduction of 9.1% in atheroma volume in the 10-mm segment with the greatest disease severity. It was concluded that very highintensity statin therapy using rosuvastatin 40 mg/day achieved significant regression of atherosclerosis .In this study, remarkable regression of plaque by statin was first clearly indicated as a multicenter study result. Regression can be considered to be a completely

different process from inhibition of progression, so this result was striking.

**3.3 The ESTABLISH study (Early Statin Treatment in Patients with Acute Coronary Syndrome: Demonstration of the Beneficial Effect on Atherosclerotic Lesions by Serial Volumetric Intravascular Ultrasound Analysis during Half a Year after Coronary** 

**3.4 The JAPAN-ACS study (Japan Assessment of Pitavastatin and Atorvastatin in** 

This study had almost similar protocol for selecting patients with acute coronary syndrome and measuring protocol to the ESTABLISH study. Major difference was that this was a noninferiority test with randomization between patients with taking atorvastatin 20 mg/day and patients with pitavastatin of 4 mg/day. Therefore, based on the ESTABLISH study, the objective of this study was to evaluate whether the regressive effects of aggressive lipidlowering therapy with atorvastatin on coronary plaque volume in patients with acute coronary syndrome are generalized for other statins in multicenter setting (observation period:8-12 months) . The primary end point was the percentage change in nonculprit coronary plaque volume. Baseline low-density lipoprotein cholesterol level (mean, 133.8 and 130.9 mg/dL in atorvastatin, and pitavastatin groups, respectively) was reduced to 84.1 mg/dL (-35.8% decrease: P<0.001, compared to the baseline) in the atorvastatin group and to 81.1 mg/dL (-36.2% decrease: P<0.001)in the pitavastatin group. The mean percentage change in plaque volume was -18.1% and -16.9 % (p=0.5) in the pitavastatin and atorvastatin

This was a single-center, but should be discussed, since the results was historical. Most unique part of this study was study population. This study investigated the 6-month effect of early statin treatment by atorvastatin of 20 mg daily on plaque volume of a nonculprit lesion by serial volumetric intravascular ultrasound in patients with ACS. All patients who underwent emergency coronary angiography and percutaneous coronary intervention were randomized to intensive lipid-lowering therapy (n=35; atorvastatin 20 mg/day) or control (n=35) groups after PCI. Volumetric intravascular ultrasound analyses were performed at baseline and 6-month follow-up for a non-PCI site in 48 patients (atorvastatin, n=24; control, n=24). LDL-C level was significantly decreased by 41.7% (124.6 to 70.0 mg/dL) in the atorvastatin group compared with the control group, in which LDL-C was not significantly changed (123.9 to 119.4 mg/dL) (atorvastatin vs. control : P<0.0001). Plaque volume was significantly reduced in the atorvastatin group (mean 13.1% decrease) compared with the control group (8.7 % increase; P<0.0001). These results of the degree of plaque regression by statin were surprisingly remarkable compared to the former reports from foreign countries for patients with stable coronary artery disease. This evidence was then proved by the

#### **3. Clinical evidences using intravascular imagings**

A number of human studies in a single center demonstrated the beneficial effects of statin or other lipid-lowering drugs in plaque progression/regression and stabilization. For example, Takagi T, et al. documented in 1997 as one of the earliest reports on IVUS observation that administration of pravastatin reduced serum lipid levels and progression of coronary artery atherosclerotic plaque(Takagi, 1997). Kawasaki et al. reported with use three-dimensional color mapping of tissue components with IB-IVUS system that statin therapy reduced the lipid component in patients with stable angina without reducing the degree of stenosis(Kawasaki, 2005). Previous coronary angioscopic studies have demonstrated that statin therapy stabilizes yellow color grade of coronary plaques (Takano, 2003).

Using IVUS and/or coronary angioscopy, various human multicenter trials with statins have offered important information on plaque regression. In the following paragraphs, the trials including REVERSAL(Nissen , 2004), ASTEROID(Nissen , 2006), ESTABLISH(Okazaki, 2004), JAPAN-ACS(Hiro, 2009), COSMOS(Takayama, 2009), TWINS(Hirayama, 2009) and TOGETHAR(Kodama, 2010) are overviewed and discussed. These trials demonstrated not only the degree of regressive effects of statins on plaque, but also key determinants and mechanisms of plaque regression.

#### **3.1 The REVERSAL study (The Reversal of Atherosclerosis with Aggressive Lipid Lowering trial) (Nissen, 2004)**

This was to compare the 18-month effect of regimens designed to produce intensive lipid lowering or moderate lipid lowering on coronary artery atheroma burden and progression. Patients with stable coronary artery disease were randomly assigned to receive a moderate lipid lowering regimen consisting of 40 mg of pravastatin or an intensive lipid-lowering regimen consisting of 80 mg of atorvastatin. The primary efficacy parameter was the percentage change in atheroma volume (follow-up minus baseline). Baseline low-density lipoprotein cholesterol level (mean, 150.2 mg/dL in both treatment groups) was reduced to 110 mg/dL in the pravastatin group and to 79 mg/dL in the atorvastatin group (P<0.001). It was shown that progression of coronary atherosclerosis occurred in the pravastatin group (median change = 2.7%; 95% CI:0.2% to 4.7%; P=0.001) compared with baseline. Progression did not occur in the atorvastatin group (−0.4%; CI−2.4% to 1.5%; P=0.98) compared with baseline. It was concluded that for patients with coronary heart disease, intensive lipidlowering treatment with atorvastatin reduced progression of coronary atherosclerosis compared with pravastatin. In this study, remarkable regression of plaque by statin was not yet clearly indicated.

#### **3.2 The ASTEROID study (A study to Evaluate the Effect of Rosuvastatin on Intravascular Ultrasound-Derived Coronary Atheroma Burden) (Nissen, 2006)**

This study was to assess whether very intensive statin therapy could regress coronary atherosclerosis as determined by IVUS imaging. Patients with stable coronary artery disease received intensive statin therapy with rosuvastatin, 40 mg/day. Two primary efficacy parameters were prespecified: the change in percent atheroma volume (PAV) and the change in nominal atheroma volume in the 10-mm subsegment with the greatest disease severity at baseline (observation period: 24 months). Baseline low-density lipoprotein cholesterol level (mean, 130.4 mg/dL) was reduced to 60.8 mg/dL (P<0.001). For the

A number of human studies in a single center demonstrated the beneficial effects of statin or other lipid-lowering drugs in plaque progression/regression and stabilization. For example, Takagi T, et al. documented in 1997 as one of the earliest reports on IVUS observation that administration of pravastatin reduced serum lipid levels and progression of coronary artery atherosclerotic plaque(Takagi, 1997). Kawasaki et al. reported with use three-dimensional color mapping of tissue components with IB-IVUS system that statin therapy reduced the lipid component in patients with stable angina without reducing the degree of stenosis(Kawasaki, 2005). Previous coronary angioscopic studies have demonstrated that

Using IVUS and/or coronary angioscopy, various human multicenter trials with statins have offered important information on plaque regression. In the following paragraphs, the trials including REVERSAL(Nissen , 2004), ASTEROID(Nissen , 2006), ESTABLISH(Okazaki, 2004), JAPAN-ACS(Hiro, 2009), COSMOS(Takayama, 2009), TWINS(Hirayama, 2009) and TOGETHAR(Kodama, 2010) are overviewed and discussed. These trials demonstrated not only the degree of regressive effects of statins on plaque, but also key determinants and

**3.1 The REVERSAL study (The Reversal of Atherosclerosis with Aggressive Lipid** 

**3.2 The ASTEROID study (A study to Evaluate the Effect of Rosuvastatin on Intravascular Ultrasound-Derived Coronary Atheroma Burden)** 

This study was to assess whether very intensive statin therapy could regress coronary atherosclerosis as determined by IVUS imaging. Patients with stable coronary artery disease received intensive statin therapy with rosuvastatin, 40 mg/day. Two primary efficacy parameters were prespecified: the change in percent atheroma volume (PAV) and the change in nominal atheroma volume in the 10-mm subsegment with the greatest disease severity at baseline (observation period: 24 months). Baseline low-density lipoprotein cholesterol level (mean, 130.4 mg/dL) was reduced to 60.8 mg/dL (P<0.001). For the

This was to compare the 18-month effect of regimens designed to produce intensive lipid lowering or moderate lipid lowering on coronary artery atheroma burden and progression. Patients with stable coronary artery disease were randomly assigned to receive a moderate lipid lowering regimen consisting of 40 mg of pravastatin or an intensive lipid-lowering regimen consisting of 80 mg of atorvastatin. The primary efficacy parameter was the percentage change in atheroma volume (follow-up minus baseline). Baseline low-density lipoprotein cholesterol level (mean, 150.2 mg/dL in both treatment groups) was reduced to 110 mg/dL in the pravastatin group and to 79 mg/dL in the atorvastatin group (P<0.001). It was shown that progression of coronary atherosclerosis occurred in the pravastatin group (median change = 2.7%; 95% CI:0.2% to 4.7%; P=0.001) compared with baseline. Progression did not occur in the atorvastatin group (−0.4%; CI−2.4% to 1.5%; P=0.98) compared with baseline. It was concluded that for patients with coronary heart disease, intensive lipidlowering treatment with atorvastatin reduced progression of coronary atherosclerosis compared with pravastatin. In this study, remarkable regression of plaque by statin was not

statin therapy stabilizes yellow color grade of coronary plaques (Takano, 2003).

**3. Clinical evidences using intravascular imagings** 

mechanisms of plaque regression.

**Lowering trial) (Nissen, 2004)** 

yet clearly indicated.

**(Nissen, 2006)** 

primary efficacy parameter of PAV, the mean decrease was −0.98% and the median was −0.79% (P<0.001 compared with baseline). For the second primary efficacy parameter, change in atheroma volume in the 10-mm subsegment with the greatest disease severity, the mean change was −6.1 mm3, and the median change was −5.6 mm3 (P<0.001 compared with baseline). This change represents a median reduction of 9.1% in atheroma volume in the 10-mm segment with the greatest disease severity. It was concluded that very highintensity statin therapy using rosuvastatin 40 mg/day achieved significant regression of atherosclerosis .In this study, remarkable regression of plaque by statin was first clearly indicated as a multicenter study result. Regression can be considered to be a completely different process from inhibition of progression, so this result was striking.

#### **3.3 The ESTABLISH study (Early Statin Treatment in Patients with Acute Coronary Syndrome: Demonstration of the Beneficial Effect on Atherosclerotic Lesions by Serial Volumetric Intravascular Ultrasound Analysis during Half a Year after Coronary Event) (Okazaki, 2004)**

This was a single-center, but should be discussed, since the results was historical. Most unique part of this study was study population. This study investigated the 6-month effect of early statin treatment by atorvastatin of 20 mg daily on plaque volume of a nonculprit lesion by serial volumetric intravascular ultrasound in patients with ACS. All patients who underwent emergency coronary angiography and percutaneous coronary intervention were randomized to intensive lipid-lowering therapy (n=35; atorvastatin 20 mg/day) or control (n=35) groups after PCI. Volumetric intravascular ultrasound analyses were performed at baseline and 6-month follow-up for a non-PCI site in 48 patients (atorvastatin, n=24; control, n=24). LDL-C level was significantly decreased by 41.7% (124.6 to 70.0 mg/dL) in the atorvastatin group compared with the control group, in which LDL-C was not significantly changed (123.9 to 119.4 mg/dL) (atorvastatin vs. control : P<0.0001). Plaque volume was significantly reduced in the atorvastatin group (mean 13.1% decrease) compared with the control group (8.7 % increase; P<0.0001). These results of the degree of plaque regression by statin were surprisingly remarkable compared to the former reports from foreign countries for patients with stable coronary artery disease. This evidence was then proved by the JAPAN-ACS study which is discussed next.

#### **3.4 The JAPAN-ACS study (Japan Assessment of Pitavastatin and Atorvastatin in Acute Coronary Syndrome) (Hiro, 2009)**

This study had almost similar protocol for selecting patients with acute coronary syndrome and measuring protocol to the ESTABLISH study. Major difference was that this was a noninferiority test with randomization between patients with taking atorvastatin 20 mg/day and patients with pitavastatin of 4 mg/day. Therefore, based on the ESTABLISH study, the objective of this study was to evaluate whether the regressive effects of aggressive lipidlowering therapy with atorvastatin on coronary plaque volume in patients with acute coronary syndrome are generalized for other statins in multicenter setting (observation period:8-12 months) . The primary end point was the percentage change in nonculprit coronary plaque volume. Baseline low-density lipoprotein cholesterol level (mean, 133.8 and 130.9 mg/dL in atorvastatin, and pitavastatin groups, respectively) was reduced to 84.1 mg/dL (-35.8% decrease: P<0.001, compared to the baseline) in the atorvastatin group and to 81.1 mg/dL (-36.2% decrease: P<0.001)in the pitavastatin group. The mean percentage change in plaque volume was -18.1% and -16.9 % (p=0.5) in the pitavastatin and atorvastatin

Plaque Regression and Stability Evaluated by

change of plaque volume.

PTV:pitavastatin.

Intravascular Ultrasound and Coronary Angioscopy: A Review 33

Fig. 5. Meta-regressive analysis of the relationship between LDL-C level and the percent

re-estimated by documented data. Black line represents the meta-regression curve for the foreign patients with stable coronary artery disease. Red line represents the one for Japanese

was to elucidate 80-week time course of atorvastatin-induced changes in vulnerable plaque using angioscopy and intravascular ultrasound (IVUS). Patients with coronary artery disease received atorvastatin of 10-20 mg/day. Mean baseline LDL-C level of 144.4 mg/dL was significantly reduced to 86.4 mg/dL at week 28 and to 89.4 mg/dL at week 80. Angioscopic images were classified into 6 grades (0–5) based on yellow color intensity. The mean angioscopic grade of 58 yellow plaques significantly decreased from 1.5 (95% confidence CI: 1.2 to 1.8) to 1.1 (95%CI 0.9 to 1.3, P=0.012) at week 28 and 1.2 (95%CI :0.9 to 1.4, P=0.024) at week 80, compare to the baseline (no significant difference between week 28 and week 80). Mean volume of 30 lesions, including the 58 yellow plaques, significantly reduced –8.3% (95%CI: –11.5 to –5.2) at week 28 (P<0.001 for baseline vs week 28) and – 17.8% (95%CI –23.9 to –11.8) at week 80 (P<0.001) for baseline vs week 80. It should be noted

Some data was not the result as the primary endpoint of the study, which was

patients with ACS. The data of the COSMOS study is just in-between the two lines. See each protocol and result for each study from the papers by (Takano , 2003; Nissen , 2004; Nissen , 2006; Okazaki , 2004; Hiro , 2009). The data of A-PLUS was obtained from the paper by (Berry , 2007). ATV:atorvastatin, PRV:pravastatin, RSV:rosuvastatin,

groups, respectively, which was associated with negative vessel remodeling. The upper limit of 95% confidence interval of the mean difference in percentage change in plaque volume between the two groups did not exceed the pre-defined noninferiority margin of 5%, suggesting noninferiority between the two groups. It was thus proved that the efficacies of both group were equivalent in the percent change of plaque volume. This results supported the data of the ESTABLISH study that early administration of statins after the onset of ACS has the potential to reverse the process of atherosclerosis.This observation also generalized the effect of statins other than atorvastatin on plaque volume in the setting of ACS. The reason why plaques in Japanese patients with ACS shows greater regression by statin compared to the foreign patients with stable coronary artery disease might be shown by the COSMOS study which is summarized later.

Recently interesting results came from a sub-analysis of the JAPAN-ACS study (Hiro , 2010). It demonstrated that the regression of coronary plaque induced by statin therapy after ACS was weaker in diabetic patients than their counterparts, although the reduction of LDL-C level was similar between diabetic group and non-diabetic group. In addition, it was also interesting that significant correlation between % change of PV and low-density lipoprotein cholesterol (LDL-C) level was found in patients with diabetes mellitus (n=73, P<0.05, r=0.4), whereas there was no significant correlation between the 2 parameters in patients without diabetes mellitus (n=178). This study was suggesting that there might be LDL-C dependent mechanism and LDL-C non-depedent mechanism in plaque regression by statin. It might be possible that in diabetic patients LDL-C non-dependent mechanism is inhibited by unknown mechanism resulting smaller regression of plaque volume. The mechanism of plaque regression may have various steps and pathways.

#### **3.5 The COSMOS study (The Coronary Atherosclerosis study Measuring Effects of Rosuvastatin Using Intravascular Ultrasound in Japanese Subjects) (Takayama, 2009)**

This study was the first multicenter study on IVUS observation of plaque with use of statin for Japanese patients with stable coronary artery disease. This was as a single arm 76-week study to investigate the effect of rosuvastatin on plaque volume in such patients. The patients received first rosuvastatin 2.5mg/day, which could be increased at 4-week intervals to ≤20 mg/day. The primary end point was the percentage change in nonculprit coronary plaque volume. The change in the serum low-density lipoprotein-cholesterol level from baseline to end of follow-up was –38.6±16.9% (mean:140.2 to 82.9 mg/dL, P<0.0001). Percent change of plaque volume, the primary endpoint, was –5.1±14.1% (P<0.0001). The degree of plaque regression compared to the degree of reduction of LDL-C level was just in-between the results from the foreign patients with stable coronary artery disease and the ones from Japanese patients with acute coronary syndrome (Figure 5). Therefore, Japanese patients as well as patients with acute coronary artery disease can easily show regression of plaque volume compared to the foreign patients and patients with stable coronary artery disease, respectively. This might be due to the difference in plaque tissue characteristics. It has been reported that patients with ACS have many greater-risk nonculprit plaques(Asakura , 2001; Burke , 1997).

#### **3.6 The TWINS study (Hirayama, 2009)**

This study as well as the TOGETHAR study were using not only IVUS but also coronary angioscopy to examine the effect of statin on plaque characteristics. The aim of this study

groups, respectively, which was associated with negative vessel remodeling. The upper limit of 95% confidence interval of the mean difference in percentage change in plaque volume between the two groups did not exceed the pre-defined noninferiority margin of 5%, suggesting noninferiority between the two groups. It was thus proved that the efficacies of both group were equivalent in the percent change of plaque volume. This results supported the data of the ESTABLISH study that early administration of statins after the onset of ACS has the potential to reverse the process of atherosclerosis.This observation also generalized the effect of statins other than atorvastatin on plaque volume in the setting of ACS. The reason why plaques in Japanese patients with ACS shows greater regression by statin compared to the foreign patients with stable coronary artery disease might be shown

Recently interesting results came from a sub-analysis of the JAPAN-ACS study (Hiro , 2010). It demonstrated that the regression of coronary plaque induced by statin therapy after ACS was weaker in diabetic patients than their counterparts, although the reduction of LDL-C level was similar between diabetic group and non-diabetic group. In addition, it was also interesting that significant correlation between % change of PV and low-density lipoprotein cholesterol (LDL-C) level was found in patients with diabetes mellitus (n=73, P<0.05, r=0.4), whereas there was no significant correlation between the 2 parameters in patients without diabetes mellitus (n=178). This study was suggesting that there might be LDL-C dependent mechanism and LDL-C non-depedent mechanism in plaque regression by statin. It might be possible that in diabetic patients LDL-C non-dependent mechanism is inhibited by unknown mechanism resulting smaller regression of plaque volume. The mechanism of

by the COSMOS study which is summarized later.

plaque regression may have various steps and pathways.

**Subjects) (Takayama, 2009)** 

Burke , 1997).

**3.6 The TWINS study (Hirayama, 2009)** 

**3.5 The COSMOS study (The Coronary Atherosclerosis study Measuring Effects of Rosuvastatin Using Intravascular Ultrasound in Japanese** 

This study was the first multicenter study on IVUS observation of plaque with use of statin for Japanese patients with stable coronary artery disease. This was as a single arm 76-week study to investigate the effect of rosuvastatin on plaque volume in such patients. The patients received first rosuvastatin 2.5mg/day, which could be increased at 4-week intervals to ≤20 mg/day. The primary end point was the percentage change in nonculprit coronary plaque volume. The change in the serum low-density lipoprotein-cholesterol level from baseline to end of follow-up was –38.6±16.9% (mean:140.2 to 82.9 mg/dL, P<0.0001). Percent change of plaque volume, the primary endpoint, was –5.1±14.1% (P<0.0001). The degree of plaque regression compared to the degree of reduction of LDL-C level was just in-between the results from the foreign patients with stable coronary artery disease and the ones from Japanese patients with acute coronary syndrome (Figure 5). Therefore, Japanese patients as well as patients with acute coronary artery disease can easily show regression of plaque volume compared to the foreign patients and patients with stable coronary artery disease, respectively. This might be due to the difference in plaque tissue characteristics. It has been reported that patients with ACS have many greater-risk nonculprit plaques(Asakura , 2001;

This study as well as the TOGETHAR study were using not only IVUS but also coronary angioscopy to examine the effect of statin on plaque characteristics. The aim of this study

Fig. 5. Meta-regressive analysis of the relationship between LDL-C level and the percent change of plaque volume.

Some data was not the result as the primary endpoint of the study, which was re-estimated by documented data. Black line represents the meta-regression curve for the foreign patients with stable coronary artery disease. Red line represents the one for Japanese patients with ACS. The data of the COSMOS study is just in-between the two lines. See each protocol and result for each study from the papers by (Takano , 2003; Nissen , 2004; Nissen , 2006; Okazaki , 2004; Hiro , 2009). The data of A-PLUS was obtained from the paper by (Berry , 2007). ATV:atorvastatin, PRV:pravastatin, RSV:rosuvastatin, PTV:pitavastatin.

was to elucidate 80-week time course of atorvastatin-induced changes in vulnerable plaque using angioscopy and intravascular ultrasound (IVUS). Patients with coronary artery disease received atorvastatin of 10-20 mg/day. Mean baseline LDL-C level of 144.4 mg/dL was significantly reduced to 86.4 mg/dL at week 28 and to 89.4 mg/dL at week 80. Angioscopic images were classified into 6 grades (0–5) based on yellow color intensity. The mean angioscopic grade of 58 yellow plaques significantly decreased from 1.5 (95% confidence CI: 1.2 to 1.8) to 1.1 (95%CI 0.9 to 1.3, P=0.012) at week 28 and 1.2 (95%CI :0.9 to 1.4, P=0.024) at week 80, compare to the baseline (no significant difference between week 28 and week 80). Mean volume of 30 lesions, including the 58 yellow plaques, significantly reduced –8.3% (95%CI: –11.5 to –5.2) at week 28 (P<0.001 for baseline vs week 28) and – 17.8% (95%CI –23.9 to –11.8) at week 80 (P<0.001) for baseline vs week 80. It should be noted

Plaque Regression and Stability Evaluated by

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650

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that qualitative changes in plaque occurred relatively early after the beginning of atorvastatin therapy (by week 28), and that quantitative changes in atheroma volume occurred continuously, even after week 28, up to week 80. These non-parallel results suggest that there may be two different, probably independent, mechanisms involved in the reduction of vulnerability, improvement in characteristics, and reduction of the volume of yellow plaques. These different time courses suggested that the improvement in plaque characteristics occurs early, whereas atheroma volume regression occurs over a prolonged period of time.

#### **3.7 The TOGETHAR study (Kodama, 2010)**

This multicenter study also revealed that the stabilization and regression of atherosclerotic plaques by statin may differ. This study was performed to assess coronary plaque regression and stabilization following 52 weeks of pitavastatin treatment (2 mg/day). Low-density lipoprotein-cholesterol (LDL-C) was reduced 34.5% (mean: 145.0 to 93.6 mg/dl, P<0.001). Yellow grade decreased (2.9±0.8 to 2.6±0.7, P=0.040) during 52 weeks. However, percent atheroma volume on IVUS did not change during 52 weeks. It was concluded that fixed dose pitavastatin stabilized vulnerable coronary plaques by the reduction of yellow grade without significant reduction of plaque volume. The fact that plaque volume was not significantly changed was probably due to the characteristics patient populations that did not include patients with ACS. These results suggested that plaque stabilization and plaque regression reflect independent processes mediated by different mechanisms, which has been previously reported(Kawasaki , 2005; Schartl , 2001).

#### **4. Future perspectives**

Recently new intravascular imaging modalities have been proposed, including optical coherence tomography. Furthermore, noninvasive imaging system, such as multi-detector CT and MRI, can visualize coronary plaques more vividly than before. Therefore, brilliant future in terms of plaque imaging can be expected. We may have to produce the following future as: Fully understanding of the plaque regression and stabilization in terms of changes in tissue component; Perfect prediction of plaque rupture with an absolute value of its likelihood within a certain period; More detailed elucidation of mechanism of acute coronary syndrome, which is fully imaged by some imaging modalities; Best therapeutic ways which are clarified based on the data of plaque imaging. Therefore, the research world of plaque imaging for plaque regression and stability has still a wide variety of clinical goals.

#### **5. Conclusion**

Advanced developments in the field of intravascular ultrasound and angioscopy are offering their capabilities of accurately measuring plaque volume as well as identifying tissue components. These technologies significantly help understand in vivo pathological reactions of plaque by lipid-lowering therapy especially in plaque regression and stabilization. Furthermore, these technologies are providing numerous reliable evidences with multicenter studies.

#### **6. References**

34 Intravascular Ultrasound

that qualitative changes in plaque occurred relatively early after the beginning of atorvastatin therapy (by week 28), and that quantitative changes in atheroma volume occurred continuously, even after week 28, up to week 80. These non-parallel results suggest that there may be two different, probably independent, mechanisms involved in the reduction of vulnerability, improvement in characteristics, and reduction of the volume of yellow plaques. These different time courses suggested that the improvement in plaque characteristics occurs early, whereas atheroma volume regression occurs over a prolonged

This multicenter study also revealed that the stabilization and regression of atherosclerotic plaques by statin may differ. This study was performed to assess coronary plaque regression and stabilization following 52 weeks of pitavastatin treatment (2 mg/day). Low-density lipoprotein-cholesterol (LDL-C) was reduced 34.5% (mean: 145.0 to 93.6 mg/dl, P<0.001). Yellow grade decreased (2.9±0.8 to 2.6±0.7, P=0.040) during 52 weeks. However, percent atheroma volume on IVUS did not change during 52 weeks. It was concluded that fixed dose pitavastatin stabilized vulnerable coronary plaques by the reduction of yellow grade without significant reduction of plaque volume. The fact that plaque volume was not significantly changed was probably due to the characteristics patient populations that did not include patients with ACS. These results suggested that plaque stabilization and plaque regression reflect independent processes mediated by different mechanisms, which has been previously reported(Kawasaki , 2005;

Recently new intravascular imaging modalities have been proposed, including optical coherence tomography. Furthermore, noninvasive imaging system, such as multi-detector CT and MRI, can visualize coronary plaques more vividly than before. Therefore, brilliant future in terms of plaque imaging can be expected. We may have to produce the following future as: Fully understanding of the plaque regression and stabilization in terms of changes in tissue component; Perfect prediction of plaque rupture with an absolute value of its likelihood within a certain period; More detailed elucidation of mechanism of acute coronary syndrome, which is fully imaged by some imaging modalities; Best therapeutic ways which are clarified based on the data of plaque imaging. Therefore, the research world of plaque imaging for plaque regression and stability has still a wide variety of clinical

Advanced developments in the field of intravascular ultrasound and angioscopy are offering their capabilities of accurately measuring plaque volume as well as identifying tissue components. These technologies significantly help understand in vivo pathological reactions of plaque by lipid-lowering therapy especially in plaque regression and stabilization. Furthermore, these technologies are providing numerous reliable evidences

period of time.

Schartl , 2001).

goals.

**5. Conclusion** 

with multicenter studies.

**4. Future perspectives** 

**3.7 The TOGETHAR study (Kodama, 2010)** 


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**3** 

*Japan* 

Masanori Kawasaki *Department of Cardiology,* 

*Gifu University Graduate School of Medicine* 

**Integrated Backscatter Intravascular Ultrasound** 

About 30 years ago, a pathological study by Horie et al. demonstrated that plaque rupture into the lumen of a coronary artery may precede and cause thrombus formation leading to acute myocardial infarction (Horie et al., 1978). In an angioscopic study, Mizuno et al. demonstrated that disruption or erosion of vulnerable plaques and subsequent thromboses are the most frequent cause of acute coronary syndrome (Mizuno et al., 1992). The stability of atherosclerotic plaques is related to the histological composition of plaques and the thickness of fibrous caps. Therefore, recognition of the tissue characteristics of coronary plaques is important to understand and prevent acute coronary syndrome. Accurate identification of the tissue characteristics of coronary plaques *in vivo* may allow the identification of vulnerable plaques before the development of acute coronary syndrome. In the 1990's, a new technique was developed that could characterize myocardial tissues by integrated backscatter (IB) analysis of ultrasound images. This technique is capable of providing both conventional two-dimensional echocardiographic images and IB images. Ultrasound backscatter power is proportional to the difference of acoustic characteristic impedance that is determined by the density of tissue multiplied by the speed of sound. In studies of the myocardium, calibrated myocardial IB values were significantly correlated with the relative volume of interstitial fibrosis (Picano, 1990 et al.; Naito et al., 1996). In preliminary studies *in vitro*, IB values reflected the structural and biochemical composition of atherosclerotic lesion and could differentiate fibrofatty, fatty and calcification of arterial walls (Barziliai et al., 1987; Urbani et al., 1993; Picano et al., 1988). It was also reported that anisotropy of the direction and backscatter power is related to plaque type (De Kroon et al., 1991). Takiuchi et al. found that quantitative tissue characterization using IB ultrasound could identify lipid pool and fibrosis in human carotid and/or femoral arteries (Takiuchi et al., 2000). However, these studies were done *ex vivo* and different plaque types were measured in only a few local lesions. In the early 2000s, it was reported that IB values measured *in vivo* in human carotid arteries correlated well with postmortem histological classification (Kawasaki et al., 2001). This new non-invasive technique using IB values could characterize the twodimensional structures of arterial plaques *in vivo*. With this technique, plaque tissues were classified based on histopathology into 6 types, *i.e*. intraplaque hemorrhage, lipid pool, intimal hyperplasia, fibrosis, dense fibrosis, and calcification. This technique was applied in the clinical setting to predict cerebral ischemic lesions after carotid artery stenting. From the analysis of receiver operating characteristic (ROC) curves, a relative intraplaque hemorrhage + lipid pool area of 50% measured by IB ultrasound imaging was the most reliable cutoff value

**1. Introduction** 

Wissler, R.W. & Vesselinovitch, D. (1976). Studies of regression of advanced atherosclerosis in experimental animals and man. *Ann N Y Acad Sci* Vol.275, No.1, pp.363-378

## **Integrated Backscatter Intravascular Ultrasound**

#### Masanori Kawasaki

*Department of Cardiology, Gifu University Graduate School of Medicine Japan* 

#### **1. Introduction**

40 Intravascular Ultrasound

Wissler, R.W. & Vesselinovitch, D. (1976). Studies of regression of advanced

pp.363-378

atherosclerosis in experimental animals and man. *Ann N Y Acad Sci* Vol.275, No.1,

About 30 years ago, a pathological study by Horie et al. demonstrated that plaque rupture into the lumen of a coronary artery may precede and cause thrombus formation leading to acute myocardial infarction (Horie et al., 1978). In an angioscopic study, Mizuno et al. demonstrated that disruption or erosion of vulnerable plaques and subsequent thromboses are the most frequent cause of acute coronary syndrome (Mizuno et al., 1992). The stability of atherosclerotic plaques is related to the histological composition of plaques and the thickness of fibrous caps. Therefore, recognition of the tissue characteristics of coronary plaques is important to understand and prevent acute coronary syndrome. Accurate identification of the tissue characteristics of coronary plaques *in vivo* may allow the identification of vulnerable plaques before the development of acute coronary syndrome.

In the 1990's, a new technique was developed that could characterize myocardial tissues by integrated backscatter (IB) analysis of ultrasound images. This technique is capable of providing both conventional two-dimensional echocardiographic images and IB images. Ultrasound backscatter power is proportional to the difference of acoustic characteristic impedance that is determined by the density of tissue multiplied by the speed of sound. In studies of the myocardium, calibrated myocardial IB values were significantly correlated with the relative volume of interstitial fibrosis (Picano, 1990 et al.; Naito et al., 1996). In preliminary studies *in vitro*, IB values reflected the structural and biochemical composition of atherosclerotic lesion and could differentiate fibrofatty, fatty and calcification of arterial walls (Barziliai et al., 1987; Urbani et al., 1993; Picano et al., 1988). It was also reported that anisotropy of the direction and backscatter power is related to plaque type (De Kroon et al., 1991). Takiuchi et al. found that quantitative tissue characterization using IB ultrasound could identify lipid pool and fibrosis in human carotid and/or femoral arteries (Takiuchi et al., 2000). However, these studies were done *ex vivo* and different plaque types were measured in only a few local lesions. In the early 2000s, it was reported that IB values measured *in vivo* in human carotid arteries correlated well with postmortem histological classification (Kawasaki et al., 2001). This new non-invasive technique using IB values could characterize the twodimensional structures of arterial plaques *in vivo*. With this technique, plaque tissues were classified based on histopathology into 6 types, *i.e*. intraplaque hemorrhage, lipid pool, intimal hyperplasia, fibrosis, dense fibrosis, and calcification. This technique was applied in the clinical setting to predict cerebral ischemic lesions after carotid artery stenting. From the analysis of receiver operating characteristic (ROC) curves, a relative intraplaque hemorrhage + lipid pool area of 50% measured by IB ultrasound imaging was the most reliable cutoff value

Integrated Backscatter Intravascular Ultrasound 43

attenuation by flowing blood, an overall attenuation of 4.0 dB/mm was determined to be the most appropriate, and this value was used to correct for ultrasound signal attenuation. Therefore, when color-coded maps were constructed, each IB value was corrected by adding 4.0 dB/mm when the ROI was located 1.5 mm further away from the catheter and subtracting 4.0 dB/mm when the ROI was located 1.5 mm closer to the catheter. Colorcoded maps consisted of four major components: fibrous (green), dense fibrosis (yellow),

The histological analysis of each ROI showed the presence of typical tissue components including calcification (n = 41), fibrosis (n = 102) and lipid pool (n = 99). With the 38 MHz ultrasound mode, the average IB values in each ROI of these tissue components were -7.3 ± 6.5, -27.0 ± 5.3 and -51.2 ± 3.3 dB, respectively; however, with the 43 MHz ultrasound mode, the average IB values were -10.6 ± 6.1, -30.4 ± 4.9 and -54.0 ± 3.9 dB, respectively. The differences among IB values of lipid pool, fibrosis or calcification were significant (p<0.001). IB values were highest in calcification and lowest in lipid pool. There was no overlap between the IB values of lipid pool and calcification. According to the analysis of ROC curves, an IB value of ≤ -39 dB (area under curve = 0.98) was the most reliable cutoff point for discriminating lipid pool (90% sensitivity, 92% specificity) and fibrosis (94% sensitivity, 93% specificity), and an IB value of > -17 dB (area under curve = 0.99) was the most reliable cutoff point for discriminating calcification and fibrosis with the 38 MHz mode. An IB value of ≤ -42 dB (area under curve = 0.98) was the most reliable cutoff point for discriminating lipid pool and fibrosis and an IB value of > -20 dB (area under curve = 0.99) was the most reliable cutoff point for discriminating calcification and fibrosis with the 43 MHz mode. Based on the above cutoff points, two-dimensional color-coded maps of tissue characteristics were constructed. A total of 95 cross-sections were diagnosed as fibrocalcific, fibrous or lipid-rich by the IB-IVUS reader, who was blinded to the histological diagnoses. There was no difference in the diagnosis of the images obtained using either the 38 MHz or 43 MHz ultrasound signal. The overall agreement between the classifications made by IB-IVUS and histology (lipid-rich: n = 35, fibrous: n = 33 and fibrocalcific: n = 27) was excellent

lipid pool (blue), calcification (red).

(Cohen's κ = 0.83, 95% CI: 0.73 - 0.92).

two imaging modalities.

**4. Comparison between IB-IVUS and virtual hostology IVUS** 

area) was automatically calculated by the LUZEX F system.

Virtual histology IVUS (Virtual Histology Version 1.4, Volcano Corp., CA, USA) images were acquired by a VH-IVUS console with a 20 MHz phased-array catheter and stored on CD-ROM for offline analysis. To clarify the rotational and cross-sectional position of the included segment, multiple surgical needles were carefully inserted into the coronary arteries before IB-IVUS and VH-IVUS imaging to serve as reference points to compare the

In qualitative comparison, small (0.3mm x 0.3mm) region-of-interest (ROI)s were set on the same sites of histological and IVUS images. In quantitative comparison, histological images from cross-sections that were stained with Masson's trichrome were digitized, and the areas that were stained blue were automatically selected by a multipurpose image processor (LUZEX F, Nireco Co., Tokyo, Japan). Then the relative fibrous area (fibrous area / plaque

In the direct qualitative comparison, the overall agreement between the histological and IB-IVUS diagnoses was higher (Cohen's κ = 0.81, 95% CI: 0.74-0.90) than between the

for predicting cerebral ischemic lesions evaluated by diffusion-weighted magnetic resonance imaging after carotid artery stenting (Yamada et al., 2010).

Since it was difficult to differentiate lipid pool from intimal hyperplasia using IB values, the anatomical features of the lesion were used for this purpose. Because lipid pool is generally located under a fibrous cap, a region of interest (ROI) that was either lipid pool or intimal hyperplasia was classified as lipid pool only when that region was located underneath a ROI with fibrosis. Intimal hyperplasia was identified when a ROI that was either lipid pool or intimal hyperplasia was not covered by a fibrous cap. Most of these two lesion types could be differentiated using this method.

#### **2. IB-IVUS equipment and data acquisition**

In the next generation, this ultrasound IB technique was applied to coronary arteries by use of intravascular ultrasound (IVUS) (Kawasaki et al., 2002). A personal computer (Windows XP Professional, CPU: 3.4 GHz) equipped with newly developed custom software was connected to an IVUS imaging system (VISIWAVE, Terumo, Japan) to obtain the radio frequency signal, signal trigger and video image outputs. An analog-to-digital converter digitized the signals at 400 MHz with 8-bit resolution, and the digitized data were stored on the hard drive of the PC for later analysis. In the IVUS analysis, 512 vector lines of ultrasound signal around the circumference were analyzed to calculate the IB values. The IB values for each tissue component were calculated using a fast Fourier transform, and expressed as the average power, measured in decibels (dB), of the frequency component of the backscattered signal from a small volume of tissue. Ultrasound backscattered signals were acquired using a 38 or 43 MHz mechanically-rotating IVUS catheter (ViewIT, Terumo, Tokyo, Japan), digitized and subjected to spectral analysis. The tissue IB values were calibrated by subtracting the IB values from the IB value of a stainless steel needle placed at a distance of 1.5 mm from the catheter. IB-IVUS color-coded maps were constructed based on the IB values by use of custom software written by our group. Conventional IVUS images and IB-IVUS color-coded maps were immediately displayed side-by-side on a monitor. Color-coded maps of the coronary arteries were finally constructed after excluding the vessel lumen and area outside of the external elastic membrane by manually tracing the vessel lumen and external elastic membrane on the conventional IVUS images. With a transducer frequency of 38 or 43 MHz, the wavelength was calculated as 36 or 41 µm, respectively, assuming a tissue sound speed of approximately 1,560 m/sec.

#### **3. Correlation between IB-IVUS and histological images**

To compare IB-IVUS images with histological images, coronary cross-sections obtained at autopsy were stained with hematoxylin-eosin, elastic van Gieson and Masson's trichrome. In the training study, three pathologic subsets were identified in each ROI: lipid pool (extracellular lipid, macrophages, microcalcification and/or foam cells), fibrosis and calcification. Necrotic core that consisted of lipid pool, microcalcification and remnants of foam cells and/or dead lymphocytes were classified as lipid pool in the IB-IVUS analysis. In the validation study, coronary arterial cross-sections were classified into three categories: fibrocalcific, fibrous and lipid-rich.

To evaluate overall ultrasound signal attenuation, IB values of the same lesions (n = 10) were measured after moving the lesions 2.5 - 4.0 mm from the IVUS catheter. Including the

for predicting cerebral ischemic lesions evaluated by diffusion-weighted magnetic resonance

Since it was difficult to differentiate lipid pool from intimal hyperplasia using IB values, the anatomical features of the lesion were used for this purpose. Because lipid pool is generally located under a fibrous cap, a region of interest (ROI) that was either lipid pool or intimal hyperplasia was classified as lipid pool only when that region was located underneath a ROI with fibrosis. Intimal hyperplasia was identified when a ROI that was either lipid pool or intimal hyperplasia was not covered by a fibrous cap. Most of these two lesion types

In the next generation, this ultrasound IB technique was applied to coronary arteries by use of intravascular ultrasound (IVUS) (Kawasaki et al., 2002). A personal computer (Windows XP Professional, CPU: 3.4 GHz) equipped with newly developed custom software was connected to an IVUS imaging system (VISIWAVE, Terumo, Japan) to obtain the radio frequency signal, signal trigger and video image outputs. An analog-to-digital converter digitized the signals at 400 MHz with 8-bit resolution, and the digitized data were stored on the hard drive of the PC for later analysis. In the IVUS analysis, 512 vector lines of ultrasound signal around the circumference were analyzed to calculate the IB values. The IB values for each tissue component were calculated using a fast Fourier transform, and expressed as the average power, measured in decibels (dB), of the frequency component of the backscattered signal from a small volume of tissue. Ultrasound backscattered signals were acquired using a 38 or 43 MHz mechanically-rotating IVUS catheter (ViewIT, Terumo, Tokyo, Japan), digitized and subjected to spectral analysis. The tissue IB values were calibrated by subtracting the IB values from the IB value of a stainless steel needle placed at a distance of 1.5 mm from the catheter. IB-IVUS color-coded maps were constructed based on the IB values by use of custom software written by our group. Conventional IVUS images and IB-IVUS color-coded maps were immediately displayed side-by-side on a monitor. Color-coded maps of the coronary arteries were finally constructed after excluding the vessel lumen and area outside of the external elastic membrane by manually tracing the vessel lumen and external elastic membrane on the conventional IVUS images. With a transducer frequency of 38 or 43 MHz, the wavelength was calculated as 36 or 41 µm,

respectively, assuming a tissue sound speed of approximately 1,560 m/sec.

To compare IB-IVUS images with histological images, coronary cross-sections obtained at autopsy were stained with hematoxylin-eosin, elastic van Gieson and Masson's trichrome. In the training study, three pathologic subsets were identified in each ROI: lipid pool (extracellular lipid, macrophages, microcalcification and/or foam cells), fibrosis and calcification. Necrotic core that consisted of lipid pool, microcalcification and remnants of foam cells and/or dead lymphocytes were classified as lipid pool in the IB-IVUS analysis. In the validation study, coronary arterial cross-sections were classified into three categories:

To evaluate overall ultrasound signal attenuation, IB values of the same lesions (n = 10) were measured after moving the lesions 2.5 - 4.0 mm from the IVUS catheter. Including the

**3. Correlation between IB-IVUS and histological images** 

fibrocalcific, fibrous and lipid-rich.

imaging after carotid artery stenting (Yamada et al., 2010).

could be differentiated using this method.

**2. IB-IVUS equipment and data acquisition** 

attenuation by flowing blood, an overall attenuation of 4.0 dB/mm was determined to be the most appropriate, and this value was used to correct for ultrasound signal attenuation. Therefore, when color-coded maps were constructed, each IB value was corrected by adding 4.0 dB/mm when the ROI was located 1.5 mm further away from the catheter and subtracting 4.0 dB/mm when the ROI was located 1.5 mm closer to the catheter. Colorcoded maps consisted of four major components: fibrous (green), dense fibrosis (yellow), lipid pool (blue), calcification (red).

The histological analysis of each ROI showed the presence of typical tissue components including calcification (n = 41), fibrosis (n = 102) and lipid pool (n = 99). With the 38 MHz ultrasound mode, the average IB values in each ROI of these tissue components were -7.3 ± 6.5, -27.0 ± 5.3 and -51.2 ± 3.3 dB, respectively; however, with the 43 MHz ultrasound mode, the average IB values were -10.6 ± 6.1, -30.4 ± 4.9 and -54.0 ± 3.9 dB, respectively. The differences among IB values of lipid pool, fibrosis or calcification were significant (p<0.001). IB values were highest in calcification and lowest in lipid pool. There was no overlap between the IB values of lipid pool and calcification. According to the analysis of ROC curves, an IB value of ≤ -39 dB (area under curve = 0.98) was the most reliable cutoff point for discriminating lipid pool (90% sensitivity, 92% specificity) and fibrosis (94% sensitivity, 93% specificity), and an IB value of > -17 dB (area under curve = 0.99) was the most reliable cutoff point for discriminating calcification and fibrosis with the 38 MHz mode. An IB value of ≤ -42 dB (area under curve = 0.98) was the most reliable cutoff point for discriminating lipid pool and fibrosis and an IB value of > -20 dB (area under curve = 0.99) was the most reliable cutoff point for discriminating calcification and fibrosis with the 43 MHz mode.

Based on the above cutoff points, two-dimensional color-coded maps of tissue characteristics were constructed. A total of 95 cross-sections were diagnosed as fibrocalcific, fibrous or lipid-rich by the IB-IVUS reader, who was blinded to the histological diagnoses. There was no difference in the diagnosis of the images obtained using either the 38 MHz or 43 MHz ultrasound signal. The overall agreement between the classifications made by IB-IVUS and histology (lipid-rich: n = 35, fibrous: n = 33 and fibrocalcific: n = 27) was excellent (Cohen's κ = 0.83, 95% CI: 0.73 - 0.92).

#### **4. Comparison between IB-IVUS and virtual hostology IVUS**

Virtual histology IVUS (Virtual Histology Version 1.4, Volcano Corp., CA, USA) images were acquired by a VH-IVUS console with a 20 MHz phased-array catheter and stored on CD-ROM for offline analysis. To clarify the rotational and cross-sectional position of the included segment, multiple surgical needles were carefully inserted into the coronary arteries before IB-IVUS and VH-IVUS imaging to serve as reference points to compare the two imaging modalities.

In qualitative comparison, small (0.3mm x 0.3mm) region-of-interest (ROI)s were set on the same sites of histological and IVUS images. In quantitative comparison, histological images from cross-sections that were stained with Masson's trichrome were digitized, and the areas that were stained blue were automatically selected by a multipurpose image processor (LUZEX F, Nireco Co., Tokyo, Japan). Then the relative fibrous area (fibrous area / plaque area) was automatically calculated by the LUZEX F system.

In the direct qualitative comparison, the overall agreement between the histological and IB-IVUS diagnoses was higher (Cohen's κ = 0.81, 95% CI: 0.74-0.90) than between the

Integrated Backscatter Intravascular Ultrasound 45

Westford, MA) was advanced into the coronary arteries. IB-IVUS and optical coherence tomography (M2 OCT Imaging system, LightLab Imaging, Inc., Westford, MA) were performed in each patient at the same site without significant stenosis as described below. IB-IVUS images were obtained every one second using an automatic pullback device at a rate of 0.5 mm/sec. optical coherence tomography images were obtained using an automatic pullback system at a rate of 0.5 mm/sec. IB-IVUS images were obtained at 0.5 mm intervals, whereas optical coherence tomography images were obtained at 0.03 mm intervals. Therefore, the segments of coronary artery to compare between the two methods were selected based on the IB-IVUS images. Then, these same coronary segments were identified in optical coherence tomography using the distance from easily-definable side branches and calcification as reference markers to ensure that IB-IVUS and optical coherence tomography were compared at the same site. The cross-sections that did not have sufficient imaging quality to analyze tissue characteristics were excluded from the comparison. In the IB-IVUS analysis, images were processed by a smoothing method that averaged nine IB values in nine pixels located in a square field of the color-coded maps to reduce uneven surfaces of

Fig. 2. The same coronary segments were selected for imaging using the distance from easily-identifiable side branches and calcification as reference markers to ensure that integrated backscatter intravascular ultrasound (IB-IVUS) and optical coherence tomography (OCT) were compared at the same site. (A) Conventional IVUS image. (B) Corresponding OCT image. (C) IB-IVUS image. (D) Corresponding OCT image. (E) Fibrous caps that overlaid lipid pool were divided into regions-of-interest (ROIs) (every 10 from the center of the vessel) and the thickness of fibrous caps was measured as an average. The average thickness of fibrous cap was measured by averaging the thickness of fibrous cap

tissue components produced by signal noise.

every 2 within ROIs. \*: septal branch.

histological and VH-IVUS diagnoses (Cohen's κ = 0.30, 95% CI: 0.14-0.41) (Okubo et al., 2008 (a); Okubo et al., 2008 (b)).

In the direct quantitative comparison, the % fibrosis area determined by IB-IVUS was significantly correlated with the relative area of fibrosis based on histology (r=0.67, p<0.001), whereas the % fibrous area and % fibrous area + % fibro-fatty area determined by VH-IVUS were not correlated with the relative area of fibrosis based on histology (Figure 1) (Okubo et al., 2008).

Fig. 1. Representative lesion used in the direct comparison study. A: histological images stained with Masson's trichrome. Bar = 1 mm. B: Images after quantification by the image processor. Areas that were stained blue by Masson's trichrome were automatically selected (green area) by the multipurpose image processor (LUZEX F) and the relative fibrous area (fibrous area / plaque area) was automatically calculated by the system. C: IB-IVUS images corresponding to sections analyzed by histology. D: IVUS-VH images corresponding to sections analyzed by histology. Percentages indicate the relative fibrous areas determined by each method.

#### **5. Comparison of the thickness of the fibrous cap measured by IB-IVUS and optical coherence tomography in vivo**

During routine selective percutaneous coronary intervention in 42 consecutive patients, a total of 28 cross-sections that consisted of lipid overlaid by a fibrous cap were imaged by both IVUS and optical coherence tomography in 24 patients with stable angina pectoris. A 0.016-inch optical coherence tomography catheter (Imagewire, LightLab Imaging, Inc.,

histological and VH-IVUS diagnoses (Cohen's κ = 0.30, 95% CI: 0.14-0.41) (Okubo et al., 2008

In the direct quantitative comparison, the % fibrosis area determined by IB-IVUS was significantly correlated with the relative area of fibrosis based on histology (r=0.67, p<0.001), whereas the % fibrous area and % fibrous area + % fibro-fatty area determined by VH-IVUS were not correlated with the relative area of fibrosis based on histology (Figure 1) (Okubo et

Fig. 1. Representative lesion used in the direct comparison study. A: histological images stained with Masson's trichrome. Bar = 1 mm. B: Images after quantification by the image processor. Areas that were stained blue by Masson's trichrome were automatically selected (green area) by the multipurpose image processor (LUZEX F) and the relative fibrous area (fibrous area / plaque area) was automatically calculated by the system. C: IB-IVUS images corresponding to sections analyzed by histology. D: IVUS-VH images corresponding to sections analyzed by histology. Percentages indicate the relative fibrous areas determined

**5. Comparison of the thickness of the fibrous cap measured by IB-IVUS and** 

During routine selective percutaneous coronary intervention in 42 consecutive patients, a total of 28 cross-sections that consisted of lipid overlaid by a fibrous cap were imaged by both IVUS and optical coherence tomography in 24 patients with stable angina pectoris. A 0.016-inch optical coherence tomography catheter (Imagewire, LightLab Imaging, Inc.,

(a); Okubo et al., 2008 (b)).

al., 2008).

by each method.

**optical coherence tomography in vivo** 

Westford, MA) was advanced into the coronary arteries. IB-IVUS and optical coherence tomography (M2 OCT Imaging system, LightLab Imaging, Inc., Westford, MA) were performed in each patient at the same site without significant stenosis as described below.

IB-IVUS images were obtained every one second using an automatic pullback device at a rate of 0.5 mm/sec. optical coherence tomography images were obtained using an automatic pullback system at a rate of 0.5 mm/sec. IB-IVUS images were obtained at 0.5 mm intervals, whereas optical coherence tomography images were obtained at 0.03 mm intervals. Therefore, the segments of coronary artery to compare between the two methods were selected based on the IB-IVUS images. Then, these same coronary segments were identified in optical coherence tomography using the distance from easily-definable side branches and calcification as reference markers to ensure that IB-IVUS and optical coherence tomography were compared at the same site. The cross-sections that did not have sufficient imaging quality to analyze tissue characteristics were excluded from the comparison. In the IB-IVUS analysis, images were processed by a smoothing method that averaged nine IB values in nine pixels located in a square field of the color-coded maps to reduce uneven surfaces of tissue components produced by signal noise.

Fig. 2. The same coronary segments were selected for imaging using the distance from easily-identifiable side branches and calcification as reference markers to ensure that integrated backscatter intravascular ultrasound (IB-IVUS) and optical coherence tomography (OCT) were compared at the same site. (A) Conventional IVUS image. (B) Corresponding OCT image. (C) IB-IVUS image. (D) Corresponding OCT image. (E) Fibrous caps that overlaid lipid pool were divided into regions-of-interest (ROIs) (every 10 from the center of the vessel) and the thickness of fibrous caps was measured as an average. The average thickness of fibrous cap was measured by averaging the thickness of fibrous cap every 2 within ROIs. \*: septal branch.

Integrated Backscatter Intravascular Ultrasound 47

Fig. 4. Left: Correlation between the thickness of fibrous cap measured by integrated backscatter

There have been many clinical studies performed using IB-IVUS. In a prospective study, IB-IVUS was performed in 140 patients with stable angina pectoris in one or two arterial segments without significant stenosis (Sano et al., 2006). The % lipid area was greater in plaques that caused acute coronary syndrome than in plaques that did not cause acute coronary syndrome (72 ± 10 versus 50 ± 16%, p<0.001). The % fibrous area was smaller in plaques that caused acute coronary syndrome than in plaques that did not cause acute

Fig. 5. Images of lesion in patients with (right) and without (left) acute coronary syndrome.

(\*) indicates the guidewire artifact.

intravascular ultrasound and optical coherence tomography. Right: Bland-Altman plot.

**6. Clinical studies conducted by use of IB-IVUS** 

coronary syndrome (23 ± 6 versus 47 ± 14%, p<0.001) (Figure 5).

Fibrous caps that overlaid lipid pool were divided into ROI (every 10 rotation from the center of the vessel lumen) and the average thickness was determined. The average thickness of fibrous cap was determined by averaging the thickness of fibrous cap every 2 within the ROIs (Figure 2). The areas where the radial axis from the center of the vessel lumen crossed the tangential line of the vessel surface with an angle less than a 80 were excluded from the comparison.

The thickness of fibrous cap measured by IB-IVUS was significantly correlated with that measured by optical coherence tomography (y = 0.99x – 0.19, r = 0.74, p<0.001) (Figure 3) (Kawasaki et al., 2010).

Fig. 3. (A) Representative integrated backscatter intravascular ultrasound (IB-IVUS) images processed by a smoothing method. (B) Original IB-IVUS images (C) Corresponding optical coherence tomography. \*: attenuation by guide wire. Bar = 1mm.

A Bland-Altman plot showed that the mean difference between the thickness of fibrous cap measured by IB-IVUS and optical coherence tomography (IB-IVUS - optical coherence tomography) was -2 ± 147 µm (Figure 4). The difference between the two methods appeared to increase as the thickness of the fibrous cap increased. Optical coherence tomography has a better potential for characterizing tissue components located on the near side of the vessel lumen, whereas IB-IVUS has a better potential for characterizing tissue components of entire plaques (Kawasaki et al., 2006).

Fibrous caps that overlaid lipid pool were divided into ROI (every 10 rotation from the center of the vessel lumen) and the average thickness was determined. The average thickness of fibrous cap was determined by averaging the thickness of fibrous cap every 2 within the ROIs (Figure 2). The areas where the radial axis from the center of the vessel lumen crossed the tangential line of the vessel surface with an angle less than a 80 were

The thickness of fibrous cap measured by IB-IVUS was significantly correlated with that measured by optical coherence tomography (y = 0.99x – 0.19, r = 0.74, p<0.001) (Figure 3)

Fig. 3. (A) Representative integrated backscatter intravascular ultrasound (IB-IVUS) images processed by a smoothing method. (B) Original IB-IVUS images (C) Corresponding optical

A Bland-Altman plot showed that the mean difference between the thickness of fibrous cap measured by IB-IVUS and optical coherence tomography (IB-IVUS - optical coherence tomography) was -2 ± 147 µm (Figure 4). The difference between the two methods appeared to increase as the thickness of the fibrous cap increased. Optical coherence tomography has a better potential for characterizing tissue components located on the near side of the vessel lumen, whereas IB-IVUS has a better potential for characterizing tissue components of entire

coherence tomography. \*: attenuation by guide wire. Bar = 1mm.

plaques (Kawasaki et al., 2006).

excluded from the comparison.

(Kawasaki et al., 2010).

Fig. 4. Left: Correlation between the thickness of fibrous cap measured by integrated backscatter intravascular ultrasound and optical coherence tomography. Right: Bland-Altman plot.

#### **6. Clinical studies conducted by use of IB-IVUS**

There have been many clinical studies performed using IB-IVUS. In a prospective study, IB-IVUS was performed in 140 patients with stable angina pectoris in one or two arterial segments without significant stenosis (Sano et al., 2006). The % lipid area was greater in plaques that caused acute coronary syndrome than in plaques that did not cause acute coronary syndrome (72 ± 10 versus 50 ± 16%, p<0.001). The % fibrous area was smaller in plaques that caused acute coronary syndrome than in plaques that did not cause acute coronary syndrome (23 ± 6 versus 47 ± 14%, p<0.001) (Figure 5).

Fig. 5. Images of lesion in patients with (right) and without (left) acute coronary syndrome. (\*) indicates the guidewire artifact.

Integrated Backscatter Intravascular Ultrasound 49

Fig. 6. A: Three-dimensional color-coded maps of coronary arterial plaques constructed by three-dimensional IB-IVUS. B: Three-dimensional color-coded maps of each characteristic.

IB-IVUS occasionally underestimates calcified lesions and overestimates lipid pool behind calcification due to the acoustic shadow derived from calcification. Acoustic shadow caused by calcification hinders the precise determination of the tissue characteristics of coronary plaques. However, there were many cases in which lesions that were classified as lipid pool by IB-IVUS due to the acoustic shadow behind calcification actually included lipid core in the same lesion analyzed by histology (n = 16/21, 76%). Our results are consistent with previous results that showed that necrotic core and fibrofatty components were located behind calcification (83 - 89%) (Kume et al., 2007). Since calcification usually originates in lesions with lipid accumulation, the diagnosis of lipid pool by IB-IVUS in lesions behind

There were a few limitations of the ultrasound method. First, the angle-dependence of the ultrasound signal makes tissue characterization unstable when lesions are not perpendicular to the ultrasound axis. Picano et al. reported that angular scattering behavior is large in calcified and fibrous tissues, whereas it is slight to nonexistent in normal and fatty plaques (Picano et al., 1985). According to that report, although there was no crossover of IB values between fibrous and fibrofatty within an angle span of 10°, or between fibrous and fatty within an angle span of 14°, this angle-dependence of the ultrasound signal might be partially responsible for the variation of IB values obtained from each tissue component. There was also a report that demonstrated the degree of angle-dependence of 30 MHz ultrasound in detail (Courtney et al., 2002). In that report, the angle-dependence of 30 MHz ultrasound in the

The number of voxels of each tissue characteristic was automatically calculated.

calcification was usually accurate.

**8. Limitations** 

The optimum cutoffs for the calculation of diagnostic accuracy to classify plaques that caused acute coronary syndrome were obtained from the ROC curve. The optimal cutoffs of % fibrous area and % lipid area were 25% and 65% respectively. Regarding remodeling index, Takeuchi et al. reported that % lipid volume in the positive remodeling plaques was greater than the non-positive remodeling plaques (40.5 ± 14.8 versus 26.4 ± 15.9%, p<0.001) and they concluded that positive remodeling lesions contain more lipid-rich components compared with non-positive remodeling lesions, which may account for the higher incidence of acute coronary syndrome and plaque vulnerability (Takeuchi et al., 2009).

During percutaneous coronary intervention, 107 non-culprit intermediate plaques in left anterior descending coronary arteries were analyzed by IB-IVUS (Komura et al., 2010). Plaques in the proximal segment had a higher % lipid content than did plaques in the distal segment (36.1 ± 12.3 versus 18.6 ± 13.1%, p<0.01). A total of 155 consecutive patients who underwent percutaneous coronary intervention were investigated by IB-IVUS. Lipid-rich plaques measured by IB-IVUS proved to be an independent morphologic predictor of nontarget ischemic events after percutaneous coronary intervention, and the risk was particularly increased in patients with elevated serum C-reactive protein levels (Amano et at., 2011). Amano et al. reported that patients with metabolic syndrome showed a significant increase in % lipid area (38 ± 19% versus 30 ± 19%, p=0.02) and metabolic syndrome was associated with lipid-rich plaques, contributing to an increase of plaque vulnerability (Amano et al., 2007). Kimura et al. demonstrated that the ratio of LDL to HDL cholesterol was an independent predictor of lipid area / non- lipid area (Kimura et al., 2010).

A substantial reduction of acute cardiac events has been shown in most lipid-lowering trials, despite only a minimal geometric regression of plaque (Brown BG et al., 1993; Fernández-Ortiz A et al., 1994). These findings suggest that plaque stability was increased by the removal of lipids from lipid-rich plaques. Three-dimensional IB-IVUS demonstrated that statin therapy for 6 months reduced the lipid volume in patients with stable angina (pravastatin: 25.5 ± 5.7 to 21.9 ± 5.3%, p<0.05; atorvastatin: 26.5 ± 5.2 to 19.9 ± 5.5%, p<0.01) without reducing the degree of stenosis. To improve the accuracy of the volumetric analysis, polar coordinates in the twodimensional color-coded maps were transformed into Cartesian coordinates (64 x 64 pixels) using computer software, because the size of each ROI was different in the polar coordinates. Three-dimensional IB-IVUS offers the potential for quantitative volumetric tissue characterization of coronary atherosclerosis (Kawasaki et al., 2005) (Figure 6).

Otagiri et al. investigated the effectiveness of rosuvastatin in patients with acute coronary syndrome using IB-IVUS. They demonstrated that reduction rate of % lipid volume after 6 months of rosuvastatin therapy was significantly correlated with the baseline values (r = - 0.498, p=0.024) (Otagiri et al., 2011). Early intervention with rosuvastatin in acute coronary syndrome patients caused significant reduction of the non-culprit plaque during 6 months. This regression was mainly due to the decrease in the lipid component measured by IB-IVUS.

#### **7. Technical consideration**

The fixation and processing of arterial samples for histopathology decreases the total vessel and luminal cross-sectional area, but the absolute wall area (total vessel cross-sectional area minus luminal cross-sectional area) does not change in vessels with minimal atherosclerotic narrowing (Lockwood et al., 1991; Siegel et al., 1985). Several studies have documented that formalin fixation does not significantly affect the morphology and quantitative echo characteristic of plaque tissue from human aortic walls (Kawasaki et al., 2001; Picano et al., 1983).

The optimum cutoffs for the calculation of diagnostic accuracy to classify plaques that caused acute coronary syndrome were obtained from the ROC curve. The optimal cutoffs of % fibrous area and % lipid area were 25% and 65% respectively. Regarding remodeling index, Takeuchi et al. reported that % lipid volume in the positive remodeling plaques was greater than the non-positive remodeling plaques (40.5 ± 14.8 versus 26.4 ± 15.9%, p<0.001) and they concluded that positive remodeling lesions contain more lipid-rich components compared with non-positive remodeling lesions, which may account for the higher incidence of acute coronary syndrome and plaque vulnerability (Takeuchi et al., 2009). During percutaneous coronary intervention, 107 non-culprit intermediate plaques in left anterior descending coronary arteries were analyzed by IB-IVUS (Komura et al., 2010). Plaques in the proximal segment had a higher % lipid content than did plaques in the distal segment (36.1 ± 12.3 versus 18.6 ± 13.1%, p<0.01). A total of 155 consecutive patients who underwent percutaneous coronary intervention were investigated by IB-IVUS. Lipid-rich plaques measured by IB-IVUS proved to be an independent morphologic predictor of nontarget ischemic events after percutaneous coronary intervention, and the risk was particularly increased in patients with elevated serum C-reactive protein levels (Amano et at., 2011). Amano et al. reported that patients with metabolic syndrome showed a significant increase in % lipid area (38 ± 19% versus 30 ± 19%, p=0.02) and metabolic syndrome was associated with lipid-rich plaques, contributing to an increase of plaque vulnerability (Amano et al., 2007). Kimura et al. demonstrated that the ratio of LDL to HDL cholesterol

was an independent predictor of lipid area / non- lipid area (Kimura et al., 2010).

characterization of coronary atherosclerosis (Kawasaki et al., 2005) (Figure 6).

**7. Technical consideration** 

1983).

A substantial reduction of acute cardiac events has been shown in most lipid-lowering trials, despite only a minimal geometric regression of plaque (Brown BG et al., 1993; Fernández-Ortiz A et al., 1994). These findings suggest that plaque stability was increased by the removal of lipids from lipid-rich plaques. Three-dimensional IB-IVUS demonstrated that statin therapy for 6 months reduced the lipid volume in patients with stable angina (pravastatin: 25.5 ± 5.7 to 21.9 ± 5.3%, p<0.05; atorvastatin: 26.5 ± 5.2 to 19.9 ± 5.5%, p<0.01) without reducing the degree of stenosis. To improve the accuracy of the volumetric analysis, polar coordinates in the twodimensional color-coded maps were transformed into Cartesian coordinates (64 x 64 pixels) using computer software, because the size of each ROI was different in the polar coordinates. Three-dimensional IB-IVUS offers the potential for quantitative volumetric tissue

Otagiri et al. investigated the effectiveness of rosuvastatin in patients with acute coronary syndrome using IB-IVUS. They demonstrated that reduction rate of % lipid volume after 6 months of rosuvastatin therapy was significantly correlated with the baseline values (r = - 0.498, p=0.024) (Otagiri et al., 2011). Early intervention with rosuvastatin in acute coronary syndrome patients caused significant reduction of the non-culprit plaque during 6 months. This regression was mainly due to the decrease in the lipid component measured by IB-IVUS.

The fixation and processing of arterial samples for histopathology decreases the total vessel and luminal cross-sectional area, but the absolute wall area (total vessel cross-sectional area minus luminal cross-sectional area) does not change in vessels with minimal atherosclerotic narrowing (Lockwood et al., 1991; Siegel et al., 1985). Several studies have documented that formalin fixation does not significantly affect the morphology and quantitative echo characteristic of plaque tissue from human aortic walls (Kawasaki et al., 2001; Picano et al.,

Fig. 6. A: Three-dimensional color-coded maps of coronary arterial plaques constructed by three-dimensional IB-IVUS. B: Three-dimensional color-coded maps of each characteristic. The number of voxels of each tissue characteristic was automatically calculated.

IB-IVUS occasionally underestimates calcified lesions and overestimates lipid pool behind calcification due to the acoustic shadow derived from calcification. Acoustic shadow caused by calcification hinders the precise determination of the tissue characteristics of coronary plaques. However, there were many cases in which lesions that were classified as lipid pool by IB-IVUS due to the acoustic shadow behind calcification actually included lipid core in the same lesion analyzed by histology (n = 16/21, 76%). Our results are consistent with previous results that showed that necrotic core and fibrofatty components were located behind calcification (83 - 89%) (Kume et al., 2007). Since calcification usually originates in lesions with lipid accumulation, the diagnosis of lipid pool by IB-IVUS in lesions behind calcification was usually accurate.

#### **8. Limitations**

There were a few limitations of the ultrasound method. First, the angle-dependence of the ultrasound signal makes tissue characterization unstable when lesions are not perpendicular to the ultrasound axis. Picano et al. reported that angular scattering behavior is large in calcified and fibrous tissues, whereas it is slight to nonexistent in normal and fatty plaques (Picano et al., 1985). According to that report, although there was no crossover of IB values between fibrous and fibrofatty within an angle span of 10°, or between fibrous and fatty within an angle span of 14°, this angle-dependence of the ultrasound signal might be partially responsible for the variation of IB values obtained from each tissue component. There was also a report that demonstrated the degree of angle-dependence of 30 MHz ultrasound in detail (Courtney et al., 2002). In that report, the angle-dependence of 30 MHz ultrasound in the

Integrated Backscatter Intravascular Ultrasound 51

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Second, the guidewire was not used in the process of imaging because the present studies were performed *ex vivo*. Imaging artifacts *in vivo* due to the guidewire may decrease the diagnostic accuracy. However, removal of the guidewire during imaging after completing the intervention procedure and/or excluding the area behind calcification from the analysis may be necessary in the clinical setting to eliminate this problem. Finally, detecting thrombus from a single IVUS cross-section was not possible because we usually look at multiple IVUS images over time for speckling, scintillation, motion and blood flow in the "microchannel" (Mintz et al., 2001). The analysis of IB values in multiple cross-sections over time is required for the detection of thrombus.

#### **9. References**


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**4** 

**IVUS Role in Studies Assessing** 

T. Kovarnik1, A. Wahle2, R.W. Downe2 and M. Sonka2

*First Faculty of Medicine, Charles University in Prague and* 

*General University Hospital in Prague,* 

*The University of Iowa, Iowa City IA,* 

*1Czech Republic* 

*2USA* 

*2Dept. of Electrical and Computer Engineering,* 

*12nd Department of Medicine - Department of Cardiovascular Medicine,* 

Atherosclerosis is known as a chronic progressive disease with accumulation of atherosclerotic plaque inside the vessel wall. Angiography studies revealed small (1-2%) increase of lumen during high dose lipid-lowering therapy, but angiography is not the appropriate tool for plaque analysis and has many limitations for precise lumen measurement due to its projective nature. In contrast, intravascular ultrasound or IVUS can accurately measure lumen and vessel diameters, and consequently determine local plaque burden. Careful mechanical pullback allows volume measurements of the lumen, vessel and plaque over a vessel segment. Serial measurements (baseline and follow-up after several months, typically 12±3 months) allow to evaluate changes of these volumes, thus to search for plaque progression or plaque regression and assess their mechanisms (for example decrease of plaque volume or increase of vessel volume), type of vessel reaction (positive and negative remodeling), development of risky plaque features like plaque ulceration and

Studies with intravascular ultrasound have shown that disease progression can be stopped (GAIN1, REVERSAL2) or reversed (ASTEROID3, ESTABLISH4, COSMOS5), especially in response to aggressive lipid-lowering treatment. The mean changes of plaque volume in the treated groups were quite small; on the other hand, large scale lipid-lowering trials have shown significant reduction of ischemic events. This discrepancy between the clinical benefits and the small changes in plaque mass can be explained by plaque stabilization (changes of plaque composition from a high risk profile to a low risk profile). However, conventional grayscale IVUS has significant limitations in the assessment of plaque composition. Virtual histology (VH) based on spectral analysis of IVUS radiofrequency data

Risk factors for atherosclerosis are same for all coronary arteries, but some regions are more affected then others like the proximal third of the arteries, ostial regions, and bifurcations. There must be some local factor playing an important role. Local wall shear stress has been

was developed to quantify coronary plaque components6.

**1. Introduction** 

plaque ruptures.

**Atherosclerosis Development** 

integrated backscatter intravascular ultrasound for tissue characterization of coronary plaques. *Ultrasound Med Biol*. Vol 34:655-63. (a)


## **IVUS Role in Studies Assessing Atherosclerosis Development**

T. Kovarnik1, A. Wahle2, R.W. Downe2 and M. Sonka2 *12nd Department of Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, 2Dept. of Electrical and Computer Engineering, The University of Iowa, Iowa City IA, 1Czech Republic 2USA* 

#### **1. Introduction**

52 Intravascular Ultrasound

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vivo radiofrequency-based ultrasonic tissue characterization of the atherosclerotic

(2010). Prediction of silent ischemic lesions after carotid artery stenting using integrated backscatter ultrasound and magnetic resonance imaging. *Atherosclerosis*

Atherosclerosis is known as a chronic progressive disease with accumulation of atherosclerotic plaque inside the vessel wall. Angiography studies revealed small (1-2%) increase of lumen during high dose lipid-lowering therapy, but angiography is not the appropriate tool for plaque analysis and has many limitations for precise lumen measurement due to its projective nature. In contrast, intravascular ultrasound or IVUS can accurately measure lumen and vessel diameters, and consequently determine local plaque burden. Careful mechanical pullback allows volume measurements of the lumen, vessel and plaque over a vessel segment. Serial measurements (baseline and follow-up after several months, typically 12±3 months) allow to evaluate changes of these volumes, thus to search for plaque progression or plaque regression and assess their mechanisms (for example decrease of plaque volume or increase of vessel volume), type of vessel reaction (positive and negative remodeling), development of risky plaque features like plaque ulceration and plaque ruptures.

Studies with intravascular ultrasound have shown that disease progression can be stopped (GAIN1, REVERSAL2) or reversed (ASTEROID3, ESTABLISH4, COSMOS5), especially in response to aggressive lipid-lowering treatment. The mean changes of plaque volume in the treated groups were quite small; on the other hand, large scale lipid-lowering trials have shown significant reduction of ischemic events. This discrepancy between the clinical benefits and the small changes in plaque mass can be explained by plaque stabilization (changes of plaque composition from a high risk profile to a low risk profile). However, conventional grayscale IVUS has significant limitations in the assessment of plaque composition. Virtual histology (VH) based on spectral analysis of IVUS radiofrequency data was developed to quantify coronary plaque components6.

Risk factors for atherosclerosis are same for all coronary arteries, but some regions are more affected then others like the proximal third of the arteries, ostial regions, and bifurcations. There must be some local factor playing an important role. Local wall shear stress has been

IVUS Role in Studies Assessing Atherosclerosis Development 55

muscle cell components within the cap are absent or sparse. The thickness of such a thin fibrous cap is less than 65 μm11,12, so thin that it may not be identifiable even with IVUS.

While the entire coronary arteries are exposed to the systemic risk factors, atherosclerotic lesions frequently form at specific regions such as at the vicinity of side branches, along the outer wall of bifurcations, and on the inner wall of curved vessels. An important local factor contributing to lesion formation in these locations is the effective endothelial shear stress (ESS)13, also called wall shear stress (WSS). Many studies confirmed the mechanistic role of low ESS in the development of atherosclerosis14-17. ESS is the tangential force derived from the friction of the flowing blood on the endothelial surface of the arterial wall and is proportional to the product of the blood viscosity (μ) and the spatial gradient of blood

Viscosity can be measured or calculated from the measured hematocrit. Intracoronary blood flow can be calculated directly from the time required for the volume of blood contained within the vascular section to leave this section and be displaced by radio-opaque material

Normal ESS is pulsatile and unidirectional with magnitude that vary within a range of 15-70 dyne/cm2 over the cardiac cycle17. Stone et al.19 published that plaque progression in minimally diseased coronary artery subsegments occurs almost exclusively in the areas of low ESS. At the same time, the vessels react on plaque progression by positive remodeling in the regions with a low ESS. However, the positive remodeling was also found in regions with high ESS with no plaque progression. It is important to keep in mind that imaging may be performed at a time when the ESS distribution, which leads to a specific plaque development, may have already been altered by plaque development at this or an adjacent location20. There are likely multiple stimuli and mechanistic pathway responsible for such positive remodeling. Low ESS contributes not only to plaque progression, but also increases the plaque vulnerability21. On the contrary, Helderman et al.22 found higher numbers of macrophages and higher metalloproteases activity in the region with high ESS. The question how the low ESS contributes to the plaque vulnerability has not been reliably answered yet. The mechanisms how low ESS influences local atherosclerosis likely includes activation of mechanoreceptors in the membrane of the endothelial cells and this signal activates or inhibits mechanosensitive genes. The atheroprotective genes are suppressed, whereas the

The atherosclerosis was thought to be a one-way process for many years. However, atherosclerosis regression was seen in autopsy findings from children, in angiographic

Fatty streaks in the aorta and the coronary arteries can been seen even in one year old children. These changes disappear at the age of four years and have an unquestionable relationship with breast feeding. Until now, it is not clear whether these findings reflect normal physiologic changes or whether they exhibit signs of premature atherosclerosis24.

Several angiographic studies assessing effects of statins on plaque progression have been published. The main target was the assessment of the minimal lumen diameter or mean

pro-atherogenic genes are upregulated in the regions with a low ESS23.

**2.2 Shear stress** 

velocity at the wall.

during a contrast injection18.

**2.3 Atherosclerosis regression** 

**2.4 Angiographic studies** 

studies and in studies conducted with IVUS.

identified as such a factor, which is caused by friction between virtual layers of blood inside arteries (the velocity of blood flow is maximal in the middle part of arteries and minimal just next to the endothelium). Shear stress induces deformation of endothelial cells and activates many pro-atherosclerotic genes (VCAM, ICAM, endothelin etc).

This chapter summarizes results of several aforementioned studies and their impact on routine daily practice. Further, it explains how to perform serial IVUS study with precise measurement of plaque volume changes and plaque risk feature changes. Second part of this chapter is focused on 3D vessel reconstruction based of angiography, IVUS, virtual histology and shear stress analysis fusion, which is the technique used for better detailed analyses of the atherosclerotic development.

#### **2. Atherosclerosis**

#### **2.1 Atherosclerosis development**

Atherosclerosis and its complications are the most frequent causes of mortality and morbidity in the developed countries. The atherosclerotic research made a great progress in investigation of atherosclerosis development, but the regression of atherosclerosis is still a process, which is not well understood.

The best description of atherosclerosis development was proposed by H. Stary et al.7, who recognized eight stages of atherosclerotic plaque maturation:


Types I-II are also called initial lesions, types IV and V developed lesion, type VI is called a complicated lesion and types VII and VIII chronic lesions8. This description of atherosclerosis development was done by examinations of post mortem specimens from adults and children. One of the most important findings is that the atherosclerotic mass is located in the vessel wall, and that the lumen area is preserved by positive remodeling up to a specific threshold when luminal narrowing starts to occur. This finding was also confirmed *in vivo* by IVUS9. The process of remodeling cannot be observed during coronary angiography, given that only the lumen is visualized and its patency is originally retained. While positive remodeling preserves the lumen, at the same time it constitutes a risk factor for development of an acute coronary syndrome. A likely common pathway is the effect of metalloproteases (enzymes which can breakdown collagen). They allow vessel enlargement, but also increase risk of plaque rupture due to the decrease of collagen amount inside the plaque10.

Further morphologic features indicating vulnerable plaque are plaque rupture and higher content of necrotic tissue. A very specific type of the rupture-prone plaque is called thin cap fibroatheroma (TCFA). Pathologic description of this type of plaque consist of a large necrotic core with an overlying thin and disrupted fibrous cap infiltrated by macrophages. The smooth muscle cell components within the cap are absent or sparse. The thickness of such a thin fibrous cap is less than 65 μm11,12, so thin that it may not be identifiable even with IVUS.

#### **2.2 Shear stress**

54 Intravascular Ultrasound

identified as such a factor, which is caused by friction between virtual layers of blood inside arteries (the velocity of blood flow is maximal in the middle part of arteries and minimal just next to the endothelium). Shear stress induces deformation of endothelial cells and activates

This chapter summarizes results of several aforementioned studies and their impact on routine daily practice. Further, it explains how to perform serial IVUS study with precise measurement of plaque volume changes and plaque risk feature changes. Second part of this chapter is focused on 3D vessel reconstruction based of angiography, IVUS, virtual histology and shear stress analysis fusion, which is the technique used for better detailed

Atherosclerosis and its complications are the most frequent causes of mortality and morbidity in the developed countries. The atherosclerotic research made a great progress in investigation of atherosclerosis development, but the regression of atherosclerosis is still a

The best description of atherosclerosis development was proposed by H. Stary et al.7, who




Types I-II are also called initial lesions, types IV and V developed lesion, type VI is called a complicated lesion and types VII and VIII chronic lesions8. This description of atherosclerosis development was done by examinations of post mortem specimens from adults and children. One of the most important findings is that the atherosclerotic mass is located in the vessel wall, and that the lumen area is preserved by positive remodeling up to a specific threshold when luminal narrowing starts to occur. This finding was also confirmed *in vivo* by IVUS9. The process of remodeling cannot be observed during coronary angiography, given that only the lumen is visualized and its patency is originally retained. While positive remodeling preserves the lumen, at the same time it constitutes a risk factor for development of an acute coronary syndrome. A likely common pathway is the effect of metalloproteases (enzymes which can breakdown collagen). They allow vessel enlargement, but also increase risk of plaque rupture

Further morphologic features indicating vulnerable plaque are plaque rupture and higher content of necrotic tissue. A very specific type of the rupture-prone plaque is called thin cap fibroatheroma (TCFA). Pathologic description of this type of plaque consist of a large necrotic core with an overlying thin and disrupted fibrous cap infiltrated by macrophages. The smooth

many pro-atherosclerotic genes (VCAM, ICAM, endothelin etc).

recognized eight stages of atherosclerotic plaque maturation:

extracellular accumulation of lipid droplets and lipid pools)



change their phenotype into foam cells )


bleeding to plaque from vasa vasorum )

due to the decrease of collagen amount inside the plaque10.


analyses of the atherosclerotic development.

**2.1 Atherosclerosis development** 

process, which is not well understood.

**2. Atherosclerosis** 

While the entire coronary arteries are exposed to the systemic risk factors, atherosclerotic lesions frequently form at specific regions such as at the vicinity of side branches, along the outer wall of bifurcations, and on the inner wall of curved vessels. An important local factor contributing to lesion formation in these locations is the effective endothelial shear stress (ESS)13, also called wall shear stress (WSS). Many studies confirmed the mechanistic role of low ESS in the development of atherosclerosis14-17. ESS is the tangential force derived from the friction of the flowing blood on the endothelial surface of the arterial wall and is proportional to the product of the blood viscosity (μ) and the spatial gradient of blood velocity at the wall.

Viscosity can be measured or calculated from the measured hematocrit. Intracoronary blood flow can be calculated directly from the time required for the volume of blood contained within the vascular section to leave this section and be displaced by radio-opaque material during a contrast injection18.

Normal ESS is pulsatile and unidirectional with magnitude that vary within a range of 15-70 dyne/cm2 over the cardiac cycle17. Stone et al.19 published that plaque progression in minimally diseased coronary artery subsegments occurs almost exclusively in the areas of low ESS. At the same time, the vessels react on plaque progression by positive remodeling in the regions with a low ESS. However, the positive remodeling was also found in regions with high ESS with no plaque progression. It is important to keep in mind that imaging may be performed at a time when the ESS distribution, which leads to a specific plaque development, may have already been altered by plaque development at this or an adjacent location20. There are likely multiple stimuli and mechanistic pathway responsible for such positive remodeling. Low ESS contributes not only to plaque progression, but also increases the plaque vulnerability21. On the contrary, Helderman et al.22 found higher numbers of macrophages and higher metalloproteases activity in the region with high ESS. The question how the low ESS contributes to the plaque vulnerability has not been reliably answered yet. The mechanisms how low ESS influences local atherosclerosis likely includes activation of mechanoreceptors in the membrane of the endothelial cells and this signal activates or inhibits mechanosensitive genes. The atheroprotective genes are suppressed, whereas the pro-atherogenic genes are upregulated in the regions with a low ESS23.

#### **2.3 Atherosclerosis regression**

The atherosclerosis was thought to be a one-way process for many years. However, atherosclerosis regression was seen in autopsy findings from children, in angiographic studies and in studies conducted with IVUS.

Fatty streaks in the aorta and the coronary arteries can been seen even in one year old children. These changes disappear at the age of four years and have an unquestionable relationship with breast feeding. Until now, it is not clear whether these findings reflect normal physiologic changes or whether they exhibit signs of premature atherosclerosis24.

#### **2.4 Angiographic studies**

Several angiographic studies assessing effects of statins on plaque progression have been published. The main target was the assessment of the minimal lumen diameter or mean

IVUS Role in Studies Assessing Atherosclerosis Development 57

The inclusion criterion is typically the identification of at least one location with the luminal stenosis > 20% by angiography, another useful criterion is may be plaque burden > 40% assessed by IVUS. In case of similar findings in more than one coronary artery during angiography, the artery with the longer plaque, or in case of several stenoses present in any single artery, the plaque with the most severe plaque burden should be selected for the IVUS analysis. The recommended segment length is greater than 30 mm with at least two clear landmarks (fiduciary points) in the proximal and distal parts of the analyzed segment. An obvious proximal landmark in the left coronary artery is the left main bifurcation. Further landmarks may be clearly defined side branches (conus branch or proximal atrial branch in the right coronary artery) or some recognizable calcifications. Despite the clear landmarks and identical conditions of the pullbacks during the baseline and follow-up, the baseline/followup pullback lengths represented by frame counts will not be identical in the majority of cases. Possible reasons for this situation are technical errors while performing of pullback (low battery power, not straightened IVUS catheter before pullback, tight Y connector), or a slightly different trajectory of the IVUS catheters due to different positions of guide wires inside the coronary artery. Differences between the baseline and follow-up in the number of frames may be up to 15%, which is considered acceptable. Consequently, volumes may have to be

calculated using the mean length between landmarks from the two studies31.

drawn on top of the EEM contour at the mouth of the side branch31.

Several automatic border detection software applications were developed to decrease the necessity of manual tracing. However, according to our experiences, careful inspection of all acquired frames and providing manual correction of almost all frames is frequently necessary during baseline/follow-up trials. The presence of calcium further complicates adventitial border detection. Heavily calcified lesions should be avoided for these types of trials due to a high risk of inaccuracy of volume measurements. Using cross sectional analysis, a single deposit with an arc of calcium < 45 degrees or multiple small arcs of up to 180 degrees can be acceptable since they can be extrapolated. Another challenging part of a vessel when performing vessel wall border detection are regions with originating side branches. Several rules are recommended unless the branch is specifically modeled as such as described in the next paragraphs: The EEM contour should be interpolated to follow the main vessel crosssections immediately proximal and distal to the side branch and the lumen contour should be

The parameters, which may be calculated include total atheroma volume (TAV) counted as (EEMCSA-Lumen CSA) and percent atheroma volume PAV counted as ((EEMCSA-Lumen CSA) / EEMCSA) x 100. Note that the presented simple calculation of TAV would not represent a true volume and would only be valid for comparisons if the inter-frame distance stays constant across all analyses. Therefore, TAV should be normalized with respect to the lesion length as described earlier: TAV / lesion length or normalized as (EEMCSA-Lumen CSA) / (number of analyzed frames per patient ) and multiplied by mean/median no. of analyzed frames in the population 31-33 . For expressing of changes between baseline and follow-up,- the absolute change of TAV or PAV (follow-up minus baseline) can be used and the percent change of TAV can be expressed as (TAVfollow up – TAV baseline / TAV baseline x 100)31. The same

approach to quantifying changes is possible for lumen volumes and vessel volumes.

Another set of interesting and important parameters is describes the vessel remodeling. For serial studies, it is recommended to calculate a remodeling index as (vessel volumefollow up – vessel volumebaseline), in which a positive value means positive remodeling and conversely a negative value represents negative remodeling. Furthermore, vessels with the positive

lumen diameter, differences between 0.03-0.08 mm were reported. It is questionable whether the angiography can precisely detect these negligible differences. Furthermore, these lumen changes are only indirect markers of plaque changes. The overview of angiographic studies is provided in Table 1.


Abbreviations: MLD = minimal lumen diameter, LDLc = low density lipoprotein cholesterol

Table 1. Angiographic studies with statins.

#### **2.5 Studies with intravascular ultrasound - Methodology**

IVUS can precisely measure lumen, vessel and plaque volumes and therefore is an ideal tool for performing follow-up studies assessing changes of these volumes during lipid lowering therapy. Two different IVUS designs can be used: Rotating element IVUS catheters operating at frequencies of 40 MHz, or electronic phased array catheters operating at a frequency of 20 MHz. Automatic motorized pullback is mandatory at a rate of 0.5 or 1.0 mm/s for reliable three-dimensional imaging. There are several important factors which influence the pullback quality31


Patients suitable for a plaque regression study are usually admitted for stable angina pectoris and undergo diagnostic angiography in the majority of cases. Patients with normal findings on coronary angiography are excluded. For some research protocols, patients with a left main stenosis or a significant stenosis of all three coronary arteries may also be excluded because they will require revascularization and would not be suitable for a followup study. It is questionable whether patients with one significant stenosis should or should not be included. From our point of view, symptomatic patients with at least one significant stenosis should undergo revascularization and not be included in a medication-based plaque regression study.

The ideal situation would be to perform IVUS in all three coronary arteries and to follow all identified plaques. However, such a design would be time consuming and complicated for the analysis and therefore, in a majority of trials, only one vessel is investigated at a time.

lumen diameter, differences between 0.03-0.08 mm were reported. It is questionable whether the angiography can precisely detect these negligible differences. Furthermore, these lumen changes are only indirect markers of plaque changes. The overview of angiographic studies

MASS26 - 0.08 mm / 4 years - 31.4%

PLAC-129 - 0.03 mm / 1 year - 28

IVUS can precisely measure lumen, vessel and plaque volumes and therefore is an ideal tool for performing follow-up studies assessing changes of these volumes during lipid lowering therapy. Two different IVUS designs can be used: Rotating element IVUS catheters operating at frequencies of 40 MHz, or electronic phased array catheters operating at a frequency of 20 MHz. Automatic motorized pullback is mandatory at a rate of 0.5 or 1.0 mm/s for reliable three-dimensional imaging. There are several important factors which

1. Adequate battery power in battery controlled pullback device. Using a battery at the

2. Opening of the Y connector before starting the pullback. It causes small bleeding, but the movement of IVUS catheter is significantly smoother and thus more accurate. 3. Straightening of the IVUS catheter before pullback, otherwise the speed of the IVUS catheter is not continuous/constant-speed at the beginning of the acquisition 4. Even if the catheter is straightened, the pullback is the least accurate at the beginning of pullback and most accurate in the proximal part of image vessel. For this reason, it is recommended to start the IVUS pullback about 10 mm distal to the location of interest. Patients suitable for a plaque regression study are usually admitted for stable angina pectoris and undergo diagnostic angiography in the majority of cases. Patients with normal findings on coronary angiography are excluded. For some research protocols, patients with a left main stenosis or a significant stenosis of all three coronary arteries may also be excluded because they will require revascularization and would not be suitable for a followup study. It is questionable whether patients with one significant stenosis should or should not be included. From our point of view, symptomatic patients with at least one significant stenosis should undergo revascularization and not be included in a medication-based

The ideal situation would be to perform IVUS in all three coronary arteries and to follow all identified plaques. However, such a design would be time consuming and complicated for the analysis and therefore, in a majority of trials, only one vessel is investigated at a time.

end of its life produces a non-continuous pullback with a decreasing speed.

*simvastatin* SCAT25 - 0.07 mm / 3-5 years - 30%

*lovastatin* CCAIT27 - 0.05 mm / 2 years - 29% *pravastatin* REGRESS28 - 0.03 mm / 2 years - 25%

*fluvastatin* LCAS30 - 0.028mm / 2.5 years - 22.5% Abbreviations: MLD = minimal lumen diameter, LDLc = low density lipoprotein cholesterol

**study change of MLD change of LDLc** 

is provided in Table 1.

Table 1. Angiographic studies with statins.

influence the pullback quality31

plaque regression study.

**2.5 Studies with intravascular ultrasound - Methodology** 

The inclusion criterion is typically the identification of at least one location with the luminal stenosis > 20% by angiography, another useful criterion is may be plaque burden > 40% assessed by IVUS. In case of similar findings in more than one coronary artery during angiography, the artery with the longer plaque, or in case of several stenoses present in any single artery, the plaque with the most severe plaque burden should be selected for the IVUS analysis. The recommended segment length is greater than 30 mm with at least two clear landmarks (fiduciary points) in the proximal and distal parts of the analyzed segment. An obvious proximal landmark in the left coronary artery is the left main bifurcation. Further landmarks may be clearly defined side branches (conus branch or proximal atrial branch in the right coronary artery) or some recognizable calcifications. Despite the clear landmarks and identical conditions of the pullbacks during the baseline and follow-up, the baseline/followup pullback lengths represented by frame counts will not be identical in the majority of cases. Possible reasons for this situation are technical errors while performing of pullback (low battery power, not straightened IVUS catheter before pullback, tight Y connector), or a slightly different trajectory of the IVUS catheters due to different positions of guide wires inside the coronary artery. Differences between the baseline and follow-up in the number of frames may be up to 15%, which is considered acceptable. Consequently, volumes may have to be calculated using the mean length between landmarks from the two studies31.

Several automatic border detection software applications were developed to decrease the necessity of manual tracing. However, according to our experiences, careful inspection of all acquired frames and providing manual correction of almost all frames is frequently necessary during baseline/follow-up trials. The presence of calcium further complicates adventitial border detection. Heavily calcified lesions should be avoided for these types of trials due to a high risk of inaccuracy of volume measurements. Using cross sectional analysis, a single deposit with an arc of calcium < 45 degrees or multiple small arcs of up to 180 degrees can be acceptable since they can be extrapolated. Another challenging part of a vessel when performing vessel wall border detection are regions with originating side branches. Several rules are recommended unless the branch is specifically modeled as such as described in the next paragraphs: The EEM contour should be interpolated to follow the main vessel crosssections immediately proximal and distal to the side branch and the lumen contour should be drawn on top of the EEM contour at the mouth of the side branch31.

The parameters, which may be calculated include total atheroma volume (TAV) counted as (EEMCSA-Lumen CSA) and percent atheroma volume PAV counted as ((EEMCSA-Lumen CSA) / EEMCSA) x 100. Note that the presented simple calculation of TAV would not represent a true volume and would only be valid for comparisons if the inter-frame distance stays constant across all analyses. Therefore, TAV should be normalized with respect to the lesion length as described earlier: TAV / lesion length or normalized as (EEMCSA-Lumen CSA) / (number of analyzed frames per patient ) and multiplied by mean/median no. of analyzed frames in the population 31-33 . For expressing of changes between baseline and follow-up,- the absolute change of TAV or PAV (follow-up minus baseline) can be used and the percent change of TAV can be expressed as (TAVfollow up – TAV baseline / TAV baseline x 100)31. The same approach to quantifying changes is possible for lumen volumes and vessel volumes.

Another set of interesting and important parameters is describes the vessel remodeling. For serial studies, it is recommended to calculate a remodeling index as (vessel volumefollow up – vessel volumebaseline), in which a positive value means positive remodeling and conversely a negative value represents negative remodeling. Furthermore, vessels with the positive

IVUS Role in Studies Assessing Atherosclerosis Development 59

Fig. 2. Meshing of the luminal surface obtained from a geometrically-correct 3D

The estimation of the absolute orientation of the IVUS frames in 3-D is a non-trivial issue and is usually resolved by using the angiographic lumen as a reference. The outline of the vessel lumen is visible in both angiographic projections when a small amount of contrast dye is injected. This is utilized to establish the orientation of the IVUS frames by finding their best fit with the angiographic outline. Using differential geometry, only the relative orientation changes from frame to frame can be established, the absolute orientation of the frame set yet needs to be determined at this stage. For this, a 3-D elliptical lumen outline is reconstructed from the angiograms and compared with the IVUS lumen outline, mapped into 3-D using an arbitrary initial orientation. This allows a non-iterative approach in which a single correction angle is calculated from an initial orientation and then applied to the entire frame set. The reconstructed vascular model provides 3-D locations for detected circumferential vertices (72 in our case) on both lumen/plaque and media/adventitia contours, oriented with respect to the IVUS catheter path. The blood flow through the coronary arteries is simulated and the wall shear stress distribution determined using

reconstruction depicting a side branch.

computational fluid dynamics (CFD) methodology.

remodeling should be subdivided into expansive (over compensatory) where ΔEEM / Δatheroma is > 1 or incomplete where ΔEEM / Δatheroma is between 0 and 1.031.

More sophisticated assessment of plaque behavior is enabled by 3D reconstruction of vessels, which is done by fusion of angiography and IVUS. This technique builds geometrically correct 3-D or 4-D (i.e., 3-D over all phases of the cardiac cycle) reconstructions of coronary arteries and computes quantitative indices of coronary lumen and wall morphology. The reconstructions may also serve as input for hemodynamic and morphologic analyses and allow for interactive visualization34 (*Figure 1*).

Fig. 1. Plaque thickness assessment with local plaque thickness indicated by color coding on the lumen surface.

In general, vessel curvature and torsion are derived from biplane (or a pair of single-plane) X-ray angiograms, and the cross-sectional information is obtained from IVUS. Thus, the resulting model accurately reflects the spatial geometry of the vessel and includes any accumulated plaque. Fusion leads to a 3-D or 4-D model, consisting of the lumen/plaque and media/adventitia contours oriented relative to the IVUS catheter. This may result in a surface mesh, which can include any branches segmented along with the main vessel to the extent visible in the IVUS (*Figure 2*). After proper meshing, this model is suitable for hemodynamic analyses.

Morphologic analyses are performed following the resampling of the cross sections orthogonal to the vessel centerline, to eliminate distortions from the position of the IVUS catheter within the vessel. The quantitative results may annotate this resampled contour model, which is then used for visualization and further analysis.

remodeling should be subdivided into expansive (over compensatory) where ΔEEM /

More sophisticated assessment of plaque behavior is enabled by 3D reconstruction of vessels, which is done by fusion of angiography and IVUS. This technique builds geometrically correct 3-D or 4-D (i.e., 3-D over all phases of the cardiac cycle) reconstructions of coronary arteries and computes quantitative indices of coronary lumen and wall morphology. The reconstructions may also serve as input for hemodynamic and

Fig. 1. Plaque thickness assessment with local plaque thickness indicated by color coding on

In general, vessel curvature and torsion are derived from biplane (or a pair of single-plane) X-ray angiograms, and the cross-sectional information is obtained from IVUS. Thus, the resulting model accurately reflects the spatial geometry of the vessel and includes any accumulated plaque. Fusion leads to a 3-D or 4-D model, consisting of the lumen/plaque and media/adventitia contours oriented relative to the IVUS catheter. This may result in a surface mesh, which can include any branches segmented along with the main vessel to the extent visible in the IVUS (*Figure 2*). After proper meshing, this model is suitable for

Morphologic analyses are performed following the resampling of the cross sections orthogonal to the vessel centerline, to eliminate distortions from the position of the IVUS catheter within the vessel. The quantitative results may annotate this resampled contour

model, which is then used for visualization and further analysis.

the lumen surface.

hemodynamic analyses.

Δatheroma is > 1 or incomplete where ΔEEM / Δatheroma is between 0 and 1.031.

morphologic analyses and allow for interactive visualization34 (*Figure 1*).

Fig. 2. Meshing of the luminal surface obtained from a geometrically-correct 3D reconstruction depicting a side branch.

The estimation of the absolute orientation of the IVUS frames in 3-D is a non-trivial issue and is usually resolved by using the angiographic lumen as a reference. The outline of the vessel lumen is visible in both angiographic projections when a small amount of contrast dye is injected. This is utilized to establish the orientation of the IVUS frames by finding their best fit with the angiographic outline. Using differential geometry, only the relative orientation changes from frame to frame can be established, the absolute orientation of the frame set yet needs to be determined at this stage. For this, a 3-D elliptical lumen outline is reconstructed from the angiograms and compared with the IVUS lumen outline, mapped into 3-D using an arbitrary initial orientation. This allows a non-iterative approach in which a single correction angle is calculated from an initial orientation and then applied to the entire frame set. The reconstructed vascular model provides 3-D locations for detected circumferential vertices (72 in our case) on both lumen/plaque and media/adventitia contours, oriented with respect to the IVUS catheter path. The blood flow through the coronary arteries is simulated and the wall shear stress distribution determined using computational fluid dynamics (CFD) methodology.

IVUS Role in Studies Assessing Atherosclerosis Development 61

25 decrease of plaque area in pravastatin

group, no

40 relative change of TAV 20%

131 relative change of TAV 2.5% vs. +

502 TAV: - 0.4mm3 vs. + 5.1mm3, relative change of TAV: + 4.1 vs. + 5.4% PAV: + 0.6% vs. +

> in worst 10 mm segment: -6.1mm3, 9.1% relative changes and – 14.7mm3 of normalized TAV

126 relative change of TAV: -5.1%

70 TAV: – 8.3mm3 vs. + 4.2mm3

252 TAV: – 8,2mm3 and – 10,6 mm3 PAV: -5,7% vs. –

6,3%

extent of

relative changes of TAV -13.1% vs. + 8.7

patients with CAD and polyvascular

atherosclerosis had smaller regression compared to patients with CAD only40

available, authors found plaque regression

11.8%

1.9%

volumetric analysis

**results change of lipids** 

LDLc: –27% vs.–9% HDLc: +29% vs. +17%

LDLc: -42% vs. -16% HDLc: +9% vs. + 12%

LDLc: –46.3% vs. –25.2 HDLc: +2.9 vs. +5.6%

LDLc : –23.5% HDLc : +9.3%

LDLc: -53.2% HDLc: +14.7%

LDLc: -38.6% HDLc: +19.8%

LDLc: –13,6% HDLc: +7%

LDLc: -43.8% vs. -3.6% HDLc: +2.4% vs. +7.0%

LDLc -36.2% vs.– 35.8% HDLc +9.9% vs.+8%

**of patient**

**study study design number** 

mg vs. standard

atorvastatatin vs. 40 mg pravastatin

dietary treatment or cholesterol absorption inhibitors

vs. atorvastatin

*ASTEROID3* rosuvastatin 40 mg 349 PAV: -0.98%, TAV

*Jensen41* simvastatin 40mg 40 TAV or PAV are not

vs. dietary stabilization

*Takagi.37* pravastatin 10mg

*Ishikawa 38* pravastatin 10-20 mg

*GAIN1* atorvastatin 20-80

*COSMOS5* rosuvastatin 2.5- 20mg

*ESTABLISH4\** atorvastatin vs.

*JAPAN-ACS39* pitavastatin 4gm

20mg

*REVERSAL2* 80 mg

therapy,

During the CFD, blood is treated as an incompressible, homogenous, and Newtonian fluid. Since the flow rate are difficult to be measured in each of the coronary arteries during data acquisition for each patient due to procedural limitations, a flow rate of 100 ml/min is sometimes assumed for all the coronary arterial segments employed in this analysis. Positive and negative wall shear stress values are determined at each circumferential lumen location and mapped onto the lumen vertices for each contour of the perpendicularly oriented 3-D model35 (*Figure 3*).

Fig. 3. Shear stress assessment on a 3-D reconstructed coronary artery (the arrow indicates the direction of blood flow).

#### **2.6 Studies with intravascular ultrasound – Overview**

Studies with intravascular ultrasound have shown that disease progression can be stopped (GAIN1, REVERSAL2) or reversed (ASTEROID3, ESTABLISH4, COSMOS5) during lipid lowering therapy, as summarized in Table 2. The promising drug torcetrapib - inhibitor of cholesteryl ester transfer protein (CETP), which facilitates the transfer of cholesteryl ester from HDL cholesterol to LDL cholesterol and VLDL cholesterol did not decrease percent atheroma volume. Furthermore, it increased the mortality (cardiovascular and all cause mortality) in ILLUMINATE trial36. The reason was increasing of blood pressure together with decreasing of potassium level (aldosteron like action). However, new CETP inhibitor without these effects is tested in preclinical trials.

During the CFD, blood is treated as an incompressible, homogenous, and Newtonian fluid. Since the flow rate are difficult to be measured in each of the coronary arteries during data acquisition for each patient due to procedural limitations, a flow rate of 100 ml/min is sometimes assumed for all the coronary arterial segments employed in this analysis. Positive and negative wall shear stress values are determined at each circumferential lumen location and mapped onto the lumen vertices for each contour of the perpendicularly

Fig. 3. Shear stress assessment on a 3-D reconstructed coronary artery (the arrow indicates

Studies with intravascular ultrasound have shown that disease progression can be stopped (GAIN1, REVERSAL2) or reversed (ASTEROID3, ESTABLISH4, COSMOS5) during lipid lowering therapy, as summarized in Table 2. The promising drug torcetrapib - inhibitor of cholesteryl ester transfer protein (CETP), which facilitates the transfer of cholesteryl ester from HDL cholesterol to LDL cholesterol and VLDL cholesterol did not decrease percent atheroma volume. Furthermore, it increased the mortality (cardiovascular and all cause mortality) in ILLUMINATE trial36. The reason was increasing of blood pressure together with decreasing of potassium level (aldosteron like action). However, new CETP inhibitor

oriented 3-D model35 (*Figure 3*).

the direction of blood flow).

**2.6 Studies with intravascular ultrasound – Overview** 

without these effects is tested in preclinical trials.


IVUS Role in Studies Assessing Atherosclerosis Development 63

tissue and increase of necrotic core (NC) and calcification (DC) were found in HEAVEN and in IBIS 2 (non-darapladib arm) studies. Nasu found decrease of NC and FF and increase of F and DC tissues, Kawasaki published decrease of lipid and fibrous tissues, Clementi found

However, there are a lot of substantial differences among these studies. They are comparing patients with or without lipid-lowering pretreatment, analyzing the whole examined segment or only the worst part of vessel and they are using different techniques for plaque composition assessment: VH-IVUS (Volcano Therapeutics), iMAP-IVUS (Boston Scientific),

Every new drug or new therapeutic approach must demonstrate a significant clinical benefit in terms of a reduction in cardiovascular morbidity and mortality. Due to the high standard of care in modern era, it becomes more and more difficult to find significant differences between new and previous treatments. The assessment of plaque volume changes can be used as an alternative end point instead of "hard" clinical endpoints, because both angiographic53 and IVUS assessed plaque progression54,55 correlate with coronary events.

Studies with intravascular ultrasound confirmed the existence of atherosclerosis regression. This process can be started by high dose of lipid lowering drugs in combination with changing the life style, more recently also with ACAT inhibitors. To date, changes of plaque composition during development and regression of atherosclerosis have not been precisely

Recent regression/progression studies performed with intravascular ultrasound have a well-defined methodology, which must be fully respected to obtain reliable and comparable results. In addition to plain 2D IVUS studies, more comprehensive studies can be performed with high-tech vessel analysis in terms of 3D/4D reconstruction with a full-range of descriptions of the observed atherosclerotic processes including volume measurements, assessments of plaque composition and computing functional aspects such as the luminal shear stress. This concept allows a more complex assessment of atherosclerosis development and can reveal additional relationships among the morphologic and functional factors.

[1] Schartl M, Bocksch W, Koschyk D, et al. Use of Intravascular Ultrasound to Compare

[2] Nissen S, Tuzscu M, Schoenhagen P, et al. Effect of Intensive Compared With Moderate

[3] Nissen SE, Nicholls SJ, Sipahi I, Libby P, Raichlen JS, Ballantyne CM. Effect of very high-

Effects of Different Strategies of Lipid-Lowering Therapy on Plaque Volume and Composition in Patients With Coronary Artery Disease. *Circulation* 2001;104:387-

Lipid-Lowering Therapy on Progression of Coronary Atherosclertosis. *JAMA*

intensity statin therapy on regression of coronary atherosclerosis: The ASTEROID

increase of NC and Hong increase of F and FF and decrease of NC and DC.

Integrated Backscatter IVUS and automated differential echogenicity52.

This strategy enables to decrease a number of patients and duration of study56.

described, and conflicting results continue being published in the literature.

**2.7 Regresion of atherosclerosis as a surrogate study endpoint** 

**3. Conclusion** 

**4. References** 

392

2004;291:1071-1080

trial. JAMA 2006;295:1556-1565


\* patiens with ACS, 2 weeks after ACS with repeated IVUS after two weeks, torcetrapib is an inhibitor for cholesteryl ester transfer protein , its development was stopped due to severe side effects (increase of blood pressure), ACAT inhibitor (acyl–coenzyme A:cholesterol acyltransferase, which esterifies cholesterol in a variety of cells and tissues, CAD coronary artery disease

Table 2. IVUS controlled progression / regression studies

The changes of plaque volume were also examined in trials focusing on plaque composition. Decrease of plaque volume was found in HEAVEN46 (percent atheroma volume), IBIS 249 (total atheroma volume) and studies done by Clementi47 (total atheroma volume) and Nasu47 Only non-significant changes of plaque volume were found in studies done by Kawasaki50, Hong51.

The changes of plaques composition during lipid-lowering therapy are not clear, because aforesaid studies found different results. Decrease of fibrous (F) tissue and fibro-fatty (FF) tissue and increase of necrotic core (NC) and calcification (DC) were found in HEAVEN and in IBIS 2 (non-darapladib arm) studies. Nasu found decrease of NC and FF and increase of F and DC tissues, Kawasaki published decrease of lipid and fibrous tissues, Clementi found increase of NC and Hong increase of F and FF and decrease of NC and DC.

However, there are a lot of substantial differences among these studies. They are comparing patients with or without lipid-lowering pretreatment, analyzing the whole examined segment or only the worst part of vessel and they are using different techniques for plaque composition assessment: VH-IVUS (Volcano Therapeutics), iMAP-IVUS (Boston Scientific), Integrated Backscatter IVUS and automated differential echogenicity52.

#### **2.7 Regresion of atherosclerosis as a surrogate study endpoint**

Every new drug or new therapeutic approach must demonstrate a significant clinical benefit in terms of a reduction in cardiovascular morbidity and mortality. Due to the high standard of care in modern era, it becomes more and more difficult to find significant differences between new and previous treatments. The assessment of plaque volume changes can be used as an alternative end point instead of "hard" clinical endpoints, because both angiographic53 and IVUS assessed plaque progression54,55 correlate with coronary events. This strategy enables to decrease a number of patients and duration of study56.

#### **3. Conclusion**

62 Intravascular Ultrasound

57 PAV -1.1% vs + 0,14%

58 TAV –1,4 mm3 vs. +7,6 mm3 PAV – 1,95 % vs.

910 normalized TAV – 9.4 vs- - 6.3mm3 ,

> PAV + 0.12% vs. + 0.19%, p=0.72

??? normalized TAV: -1.3 mm3 vs. – 5.6 mm3 PAV: +0.8% vs.

+1,6%

p=0.02

+0.6%

26 TAV - 6.7 vs. 2.3 mm3

89 PAV - 0.4% vs. + 1.4%, p=0.01

80 TAV – 36.4 vs. +

\* patiens with ACS, 2 weeks after ACS with repeated IVUS after two weeks, torcetrapib is an inhibitor for cholesteryl ester transfer protein , its development was stopped due to severe side effects (increase of blood pressure), ACAT inhibitor (acyl–coenzyme A:cholesterol acyltransferase, which

The changes of plaque volume were also examined in trials focusing on plaque composition. Decrease of plaque volume was found in HEAVEN46 (percent atheroma volume), IBIS 249 (total atheroma volume) and studies done by Clementi47 (total atheroma volume) and Nasu47 Only non-significant changes of plaque volume were found in studies done by Kawasaki50,

The changes of plaques composition during lipid-lowering therapy are not clear, because aforesaid studies found different results. Decrease of fibrous (F) tissue and fibro-fatty (FF)

esterifies cholesterol in a variety of cells and tissues, CAD coronary artery disease

11.2 mm3, p<0.0001

25 TAV -12.7 not available

**results change of lipids** 

not available

not available

not available

LDLc: -28.6% vs. – 1.9% HDLc: +4,5% vs. -1.3%

LDL -47.7% vs. -1.1 HDL +2.2% vs. – 0.6%

LDLc: –34% vs. 0% HDLc: -1% vs +1%

LDLc: –13.3% vs. +6.6% HDLc: +58.6% vs. +2.2%

**of patient**

**study study design number** 

ApoA-I Milano vs.

20mg vs. usual care

atorvastatin vs-. atorvastatin

recombinant

placebo

*REACH43* atorvatatin 10-

*ILLUSTRATE44* torcetrapib+

*ACTIVATE32* pactimibe vs.

*Nakayama45* pioglitazon 15mg

placebo

vs. standard therapy in diabetic

l vs. standard care

pioglitazone for 6 month, no control

control according

Table 2. IVUS controlled progression / regression studies

patients

*HEAVEN46* atorvastatin+ezetro

Clementi47 Atorvastatin 80mg + 30mg

group

to LDLc

Nasu48 Fluvastatin vs.

Hong51.

*Nissen42*

Studies with intravascular ultrasound confirmed the existence of atherosclerosis regression. This process can be started by high dose of lipid lowering drugs in combination with changing the life style, more recently also with ACAT inhibitors. To date, changes of plaque composition during development and regression of atherosclerosis have not been precisely described, and conflicting results continue being published in the literature.

Recent regression/progression studies performed with intravascular ultrasound have a well-defined methodology, which must be fully respected to obtain reliable and comparable results. In addition to plain 2D IVUS studies, more comprehensive studies can be performed with high-tech vessel analysis in terms of 3D/4D reconstruction with a full-range of descriptions of the observed atherosclerotic processes including volume measurements, assessments of plaque composition and computing functional aspects such as the luminal shear stress. This concept allows a more complex assessment of atherosclerosis development and can reveal additional relationships among the morphologic and functional factors.

#### **4. References**


IVUS Role in Studies Assessing Atherosclerosis Development 65

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**1. Introduction** 

**5** 

*USA* 

**IVUS in the Assessment of** 

Sudhir S. Kushwaha and Eugenia Raichlin *Mayo Clinic and University of Nebraska Medical Center* 

**Coronary Allograft Vasculopathy** 

**Cardiac allograft vasculopathy (CAV)** is a unique form of accelerated atherosclerosis and remains the leading cause of late morbidity and mortality in heart transplant patients

Although the pathogenesis of CAV is not fully elucidated, it seems to result from a complex interplay between immunologic and nonimmunologic factors, with consequent repetitive vascular injury and a localized sustained inflammatory response (Costanzo et al., 1998), (Julius et al., 2000). CAV affects large epicardial vessels and the microcirculation which results in a progressive luminal narrowing (Gao et al., 1990) and reduces myocardial blood flow (Kushwaha et al., 1998). CAV may be present in intramyocardial vessels even if epicardial disease is not evident (Clausell et al., 1995). Autopsy findings have demonstrated the presence of CAV in nearly all specimens at two years and changes are seen as early as 6

Early CAV is clinically silent, and ischemia is usually not evident until the disease is far advanced (Ciliberto et al., 1993), (Collings et al., 1994, (Mairesse et al., 1995), (Smart et al., 1991), (Stark et al., 1991) and graft failure tends to develop as a late manifestation of the disease. Therefore, identification of the asymptomatic patient at early stages of the disease is an important strategy for the prevention of irreversible detrimental effects on the graft.

Noninvasive screening tests for CAV such as the exercise electrocardiogram, thallium scintigraphy, and exercise radionucleotide ventriculography have shown insufficient sensitivity and specificity for reliable detection of CAV (Smart, 1991). Traditionally, **coronary angiography** has been used for the diagnosis of CAV and, according to the amount of stenosis in the most severely affected vessel, CAV is usually classified as absent (0% stenosis), mild (up

However, coronary angiography, given that it basically provides images in the form of a lumenogram, has been shown to systematically underestimate the presence of coronary atherosclerosis in transplant recipients as validated in autopsy studies (St. Goar et al., 1992), (Dressler et al., 1992). No information on vessel wall structure and intimal thickening is provided by coronary angiography. Being a highly specific (97.8%) tool, the diffuse nature of

accounting for 30% mortality at 5 years (Miller et al., 1993), (Taylor et al., 2007).

weeks after cardiac transplant (Baldwin et al., 1987), (St. Goar et al., 1992).

to 30% stenosis), moderate (30–70% stenosis), or severe (>70% stenosis).

**2. IVUS and allograft vasculopathy 2.1 Limitations of coronary angiogram** 


## **IVUS in the Assessment of Coronary Allograft Vasculopathy**

Sudhir S. Kushwaha and Eugenia Raichlin *Mayo Clinic and University of Nebraska Medical Center USA* 

#### **1. Introduction**

68 Intravascular Ultrasound

[54] Ricciardi MJ, Meyers S, Choi K, Pang JL, Goodreau L, Davidson CJ. Angiographically

[55] Bose D, von Birgelen C, Erbel R. Intravascular ultrasound for the evaluation of therapies targeting coronary atherosclerosis. J Am Coll Cardiol 2007;49:925-932

adverse cardiac events. Am Heart J 2003;146:507–12

silent left main disease detected by intravascular ultrasound: a marker for future

**Cardiac allograft vasculopathy (CAV)** is a unique form of accelerated atherosclerosis and remains the leading cause of late morbidity and mortality in heart transplant patients accounting for 30% mortality at 5 years (Miller et al., 1993), (Taylor et al., 2007).

Although the pathogenesis of CAV is not fully elucidated, it seems to result from a complex interplay between immunologic and nonimmunologic factors, with consequent repetitive vascular injury and a localized sustained inflammatory response (Costanzo et al., 1998), (Julius et al., 2000). CAV affects large epicardial vessels and the microcirculation which results in a progressive luminal narrowing (Gao et al., 1990) and reduces myocardial blood flow (Kushwaha et al., 1998). CAV may be present in intramyocardial vessels even if epicardial disease is not evident (Clausell et al., 1995). Autopsy findings have demonstrated the presence of CAV in nearly all specimens at two years and changes are seen as early as 6 weeks after cardiac transplant (Baldwin et al., 1987), (St. Goar et al., 1992).

Early CAV is clinically silent, and ischemia is usually not evident until the disease is far advanced (Ciliberto et al., 1993), (Collings et al., 1994, (Mairesse et al., 1995), (Smart et al., 1991), (Stark et al., 1991) and graft failure tends to develop as a late manifestation of the disease. Therefore, identification of the asymptomatic patient at early stages of the disease is an important strategy for the prevention of irreversible detrimental effects on the graft.

#### **2. IVUS and allograft vasculopathy**

#### **2.1 Limitations of coronary angiogram**

Noninvasive screening tests for CAV such as the exercise electrocardiogram, thallium scintigraphy, and exercise radionucleotide ventriculography have shown insufficient sensitivity and specificity for reliable detection of CAV (Smart, 1991). Traditionally, **coronary angiography** has been used for the diagnosis of CAV and, according to the amount of stenosis in the most severely affected vessel, CAV is usually classified as absent (0% stenosis), mild (up to 30% stenosis), moderate (30–70% stenosis), or severe (>70% stenosis).

However, coronary angiography, given that it basically provides images in the form of a lumenogram, has been shown to systematically underestimate the presence of coronary atherosclerosis in transplant recipients as validated in autopsy studies (St. Goar et al., 1992), (Dressler et al., 1992). No information on vessel wall structure and intimal thickening is provided by coronary angiography. Being a highly specific (97.8%) tool, the diffuse nature of

IVUS in the Assessment of Coronary Allograft Vasculopathy 71

Fig. 2. Measurements of lumen and vessel wall dimensions in an ultrasound image

vessel circumference involved was proposed by the Stanford group (Table 1).

Table 1. Ultrasound classification of CAV in cardiac transplant recipients)

The maximal intimal thickness (MIT) assessed by 2D-IVUS is a commonly used measure to describe the severity of lesions and has been defined as a clinically useful surrogate for clinical outcome (Mehra et al., 1995a), (Rickenbacher et al., 1995a). The threshold of MIT > 0.5 mm is usually acceptable (Kapadia et al., 2000), but this categorical classification of MIT, a continuous variable, into normal or abnormal is inherently arbitrary. This definition, however, is based on information provided by histological and ultrasound studies. In an autopsy study, normal intimal thickness, not including media, ranged between 0.10 and 0.30 mm in individuals between 21 and 40 years of age (Sims et al., 2002), (Velican et al., 1985). Therefore, intimal thickness > 0.3 mm is considered to represent significant CAV. A classification of the vascular disease severity according to **intimal thickness** and degree of

The thickness of the **media** is usually about 0.02-0.23 mm and is unchanged or decreased with the development of CAV. Thus, the thickness of the normal **intima plus media** in young and middle age individuals ranges from 0.45 to 0.50 mm. (Sims et al., 2002), (Velican et al., 1985).

Despite this immense value of IVUS in the detection of CAV, there is controversy regarding the methodology and imaging protocols. Site selection and adequate sampling for quantitative analysis is crucial. Most studies have selectively visualized the LAD, making the assumption that CAV occurs uniformly throughout the coronary tree. It has been demonstrated, that multi-vessel imaging is definitely more sensitive in detecting transplant vasculopathy lesions compared to single-vessel imaging (Kapadia, 2000), and sampling of a single coronary artery for imaging may not be sufficient to adequately

Adapted from Tuzcu et al., 1995

Adapted from St. Goar, 1992

CAV limits the sensitivity of coronary angiography to 79.3% (Sharples et al., 2003), (St. Goar et al., 1992). As a result, one fifth of patients with CAV have false normal coronary angiography (Sharples et al., 2003). Moreover, the reported 50% negative predictive value (Cale et al. 2010) limits the clinical utility of routine angiographic surveillance for CAV in heart transplant recipients. Based on these limitations, at least one transplant center has abandoned coronary angiogram for routine monitoring of heart-transplant recipients (Clague et al., 2001).

Intravascular ultrasound (IVUS) is a safe and reproducible imaging technique (Batkoff et al., 1996) that is more sensitive than angiography and useful for the early diagnosis of CAV, morphometric and volumetric analysis, assessing plaque composition and vessel remodeling (Miller et al., 1995), (Pflugfelder et al., 1993), (St. Goar et al., 1992), (Yeung et al., 1995). Whereas angiographic disease is present in 10% to 20% of patients at 1 year and 50% by 5 years after transplantation (Gao et al., 1988), (Uretsky et al., 1987) the prevalence of abnormal intimal thickening is seen in 50% of patients by 1 year in IVUS imaging (Gao et al., 1988), (Tuzcu et al., 1996), (Yeung et al., 1995). Therefore, IVUS is now considered the "gold standard" for the evaluation of CAV (Kapadia et al., 2000).

#### **2.2 Lesion morphology and quantitative analysis**

IVUS reveals cross sectional coronary artery image, which in post-transplant patients typically have tri-laminar appearance (Figure 1) with bright inner layer (intima), an echo-fine middle layer (media) and a bright dense outer layer (adventitia); and allows the following measurements: (1) maximal intimal thickness (MIT) as the greatest distance from the intimal leading edge to media-adventitia border, (2) minimal intimal thickness as the shortest distance from the intimal leading edge to media-adventitia border, (3) minimal luminal diameter as the shortest distance between opposing intimal leading edges, (4) lumen area as the area within the boundaries of the intimal leading edge, (5) vessel area as the area within the mediaadventitia border, (6) plaque cross-sectional area as the difference between vessel and lumen areas, (7) plaque index as (lumen area/vessel area) X 100, and (8) eccentric index: [(maximal plaque thickness - minimal plaque thickness)/ maximal plaque thickness] X 100 (Figure 2).

Adapter from Tuzcu et al., 1995

Inset shows the three layers of the vessel wall (black arrow). The thin echogenic inner layer corresponds to the intima, the thin echolucent middle layer to the media, and the echogenic outer layer to the adventitia

Fig. 1. Ultrasound image of a normal coronary artery

Adapted from Tuzcu et al., 1995

70 Intravascular Ultrasound

CAV limits the sensitivity of coronary angiography to 79.3% (Sharples et al., 2003), (St. Goar et al., 1992). As a result, one fifth of patients with CAV have false normal coronary angiography (Sharples et al., 2003). Moreover, the reported 50% negative predictive value (Cale et al. 2010) limits the clinical utility of routine angiographic surveillance for CAV in heart transplant recipients. Based on these limitations, at least one transplant center has abandoned coronary

Intravascular ultrasound (IVUS) is a safe and reproducible imaging technique (Batkoff et al., 1996) that is more sensitive than angiography and useful for the early diagnosis of CAV, morphometric and volumetric analysis, assessing plaque composition and vessel remodeling (Miller et al., 1995), (Pflugfelder et al., 1993), (St. Goar et al., 1992), (Yeung et al., 1995). Whereas angiographic disease is present in 10% to 20% of patients at 1 year and 50% by 5 years after transplantation (Gao et al., 1988), (Uretsky et al., 1987) the prevalence of abnormal intimal thickening is seen in 50% of patients by 1 year in IVUS imaging (Gao et al., 1988), (Tuzcu et al., 1996), (Yeung et al., 1995). Therefore, IVUS is now considered the "gold

IVUS reveals cross sectional coronary artery image, which in post-transplant patients typically have tri-laminar appearance (Figure 1) with bright inner layer (intima), an echo-fine middle layer (media) and a bright dense outer layer (adventitia); and allows the following measurements: (1) maximal intimal thickness (MIT) as the greatest distance from the intimal leading edge to media-adventitia border, (2) minimal intimal thickness as the shortest distance from the intimal leading edge to media-adventitia border, (3) minimal luminal diameter as the shortest distance between opposing intimal leading edges, (4) lumen area as the area within the boundaries of the intimal leading edge, (5) vessel area as the area within the mediaadventitia border, (6) plaque cross-sectional area as the difference between vessel and lumen areas, (7) plaque index as (lumen area/vessel area) X 100, and (8) eccentric index: [(maximal plaque thickness - minimal plaque thickness)/ maximal plaque thickness] X 100 (Figure 2).

Inset shows the three layers of the vessel wall (black arrow). The thin echogenic inner layer corresponds to the intima, the thin echolucent middle layer to the media, and the echogenic outer layer to the

angiogram for routine monitoring of heart-transplant recipients (Clague et al., 2001).

standard" for the evaluation of CAV (Kapadia et al., 2000).

**2.2 Lesion morphology and quantitative analysis** 

Adapter from Tuzcu et al., 1995

Fig. 1. Ultrasound image of a normal coronary artery

adventitia

Fig. 2. Measurements of lumen and vessel wall dimensions in an ultrasound image

The maximal intimal thickness (MIT) assessed by 2D-IVUS is a commonly used measure to describe the severity of lesions and has been defined as a clinically useful surrogate for clinical outcome (Mehra et al., 1995a), (Rickenbacher et al., 1995a). The threshold of MIT > 0.5 mm is usually acceptable (Kapadia et al., 2000), but this categorical classification of MIT, a continuous variable, into normal or abnormal is inherently arbitrary. This definition, however, is based on information provided by histological and ultrasound studies. In an autopsy study, normal intimal thickness, not including media, ranged between 0.10 and 0.30 mm in individuals between 21 and 40 years of age (Sims et al., 2002), (Velican et al., 1985). Therefore, intimal thickness > 0.3 mm is considered to represent significant CAV. A classification of the vascular disease severity according to **intimal thickness** and degree of vessel circumference involved was proposed by the Stanford group (Table 1).

The thickness of the **media** is usually about 0.02-0.23 mm and is unchanged or decreased with the development of CAV. Thus, the thickness of the normal **intima plus media** in young and middle age individuals ranges from 0.45 to 0.50 mm. (Sims et al., 2002), (Velican et al., 1985).


Adapted from St. Goar, 1992

Table 1. Ultrasound classification of CAV in cardiac transplant recipients)

Despite this immense value of IVUS in the detection of CAV, there is controversy regarding the methodology and imaging protocols. Site selection and adequate sampling for quantitative analysis is crucial. Most studies have selectively visualized the LAD, making the assumption that CAV occurs uniformly throughout the coronary tree. It has been demonstrated, that multi-vessel imaging is definitely more sensitive in detecting transplant vasculopathy lesions compared to single-vessel imaging (Kapadia, 2000), and sampling of a single coronary artery for imaging may not be sufficient to adequately

IVUS in the Assessment of Coronary Allograft Vasculopathy 73

(Left) Gray scale IVUS cross-section imaging shows concentric plaque: a (PV/SL) of 6.79 and a PI of 32%

Fig. 3. Gray scale IVUS cross-section imaging shows concentric plaque with corresponding

Morphologic studies performed with IVUS have led to important insights into the etiology

Coronary artery vasculopathy (CAV) is a multifactorial phenomenon with variable morphologic features. Previous histological ex-vivo studies described two microscopic types of coronary allograft lesions (Johnson, 1989). One type of coronary lesion is confined to the proximal region of epicardial arteries and indistinguishable from typical atherosclerosis of native vessels. The second type is characterized by the presence of vasculitis, involving the entire coronary arterial system and has been suggested to represent the immune mediated vessel injury (Higuchi et al., 1999). The ability to differentiate between the existence of classic atherosclerosis and transplant-specific immunologically mediated CAV holds both prognostic and therapeutic values and this

(Right) The corresponding VH-IVUS image depicts specific color-coded plaque components and demonstrates fibrous plaque of 47%, fibrofatty plaque of 20%, dense calcium of 14%, and necrotic core

of 27%.PV/SL, plaque volume normalized for segment length; PI, plaque index

**2.5 Impact of IVUS in understanding coronary allograft vasculopathy** 

was calculated

VH-IVUS image

Adapted from Raichlin et al., 2007b

and pathogenesis of CAV.

assess the prevalence of CAV. However, multi-vessel imaging is time consuming, adds to the cost of the procedure and, although procedural complications other than occasional spasm resolved with intracoronary nitroglycerin did not occur, the long-term safety of the multi-vessel imaging remains unknown. Thus, the limitations of single vessel imaging should be weighed against the potential benefits from adequate sampling of multi-vessel imaging.

#### **2.3 Three-dimensional reconstruction (3D-IVUS)**

2D-IVUS has limitation in spatial registration and the inability to assess the full extent of vascular disease (Tuzcu, 2005) which reduces its sensitivity to detect the changes of atherosclerotic burden in CAV. Three-dimensional (3D-IVUS) reconstruction allows rapid and accurate measurement of volume and plaque dimensions with full extent of atherosclerotic pathology. Automated pullback with a known pullback speed is necessary. The vessel, lumen and plaque volume can be calculated using the Simpson rule for images that are 1 mm apart. Since the histology literature does not commonly depend on volumetric indices, currently, there is no well-defined threshold for these measurements and the information is not readily obtainable. Because of its superior reproducibility, however, 3D-IVUS may be used to assess the progression of coronary artery disease and allow for more accurate evaluation of interventions aimed at preventing or attenuating coronary artery disease (Bae et al., 2006), (White et al., 2003).

#### **2.4 Virtual Histology Intravascular Ultrasound (VH-IVUS)**

Grayscale IVUS is able to visualize coronary atherosclerosis in vivo and allows rapid and accurate assessment of plaque area and distribution, lesion length, and coronary remodelling (Bae et al., 2006), (Kapadia et al., 2000), (White et al., 2003), but has a significant limitation in the evaluation of atherosclerotic plaque composition.

VH-IVUS is a novel technology to characterize the different types of plaque morphology in vivo which based on the spectral analysis of the radiofrequency ultrasound signals in a frequency domain (Nair et al., 2002), (Nasu et al., 2006), (Rodriguez-Granillo et al., 2005). It displays the reconstructed color coded tissue map of plaque composition overlaid on a greyscale image and groups plaque components into 4 basic tissue types: fibrous tissue (green), fibro-fatty tissue (light green), necrotic core (red), and dense calcium (white). (Figure 3) This approach has not been validated with histological techniques in heart transplant patients, however in the non-transplant population the overall predictive accuracies were 90.4% for fibrous tissue, 92.8% for fibrolipidic, 89.5% necrotic core, and 90.9% for dense calcium (Nair et al, 2001), (Nair et al, 2002), (Nasu et al, 2006). In native coronaries morphological composition of atherosclerotic plaque is a useful determinant of the plaque vulnerability (Ehara et al., 2004), (Naghavi et al., 2003), (Valgimigli et al., 2007), and identified plaques with a high-risk of future clinical events (Bae et al., 2008), (Kawaguchi et al., 2007), (Kawamoto et al., 2007). After heart transplantation, simultaneous assessment of virtual histology with IVUS provides detailed information about plaque morphology and composition, may improve the risk stratification of heart transplant recipients (Konig et al., 2008) and add important information in the clinical evaluation of heart transplant recipients (Raichlin et al., 2009).

assess the prevalence of CAV. However, multi-vessel imaging is time consuming, adds to the cost of the procedure and, although procedural complications other than occasional spasm resolved with intracoronary nitroglycerin did not occur, the long-term safety of the multi-vessel imaging remains unknown. Thus, the limitations of single vessel imaging should be weighed against the potential benefits from adequate sampling of multi-vessel

2D-IVUS has limitation in spatial registration and the inability to assess the full extent of vascular disease (Tuzcu, 2005) which reduces its sensitivity to detect the changes of atherosclerotic burden in CAV. Three-dimensional (3D-IVUS) reconstruction allows rapid and accurate measurement of volume and plaque dimensions with full extent of atherosclerotic pathology. Automated pullback with a known pullback speed is necessary. The vessel, lumen and plaque volume can be calculated using the Simpson rule for images that are 1 mm apart. Since the histology literature does not commonly depend on volumetric indices, currently, there is no well-defined threshold for these measurements and the information is not readily obtainable. Because of its superior reproducibility, however, 3D-IVUS may be used to assess the progression of coronary artery disease and allow for more accurate evaluation of interventions aimed at preventing or attenuating coronary artery

Grayscale IVUS is able to visualize coronary atherosclerosis in vivo and allows rapid and accurate assessment of plaque area and distribution, lesion length, and coronary remodelling (Bae et al., 2006), (Kapadia et al., 2000), (White et al., 2003), but has a significant

VH-IVUS is a novel technology to characterize the different types of plaque morphology in vivo which based on the spectral analysis of the radiofrequency ultrasound signals in a frequency domain (Nair et al., 2002), (Nasu et al., 2006), (Rodriguez-Granillo et al., 2005). It displays the reconstructed color coded tissue map of plaque composition overlaid on a greyscale image and groups plaque components into 4 basic tissue types: fibrous tissue (green), fibro-fatty tissue (light green), necrotic core (red), and dense calcium (white). (Figure 3) This approach has not been validated with histological techniques in heart transplant patients, however in the non-transplant population the overall predictive accuracies were 90.4% for fibrous tissue, 92.8% for fibrolipidic, 89.5% necrotic core, and 90.9% for dense calcium (Nair et al, 2001), (Nair et al, 2002), (Nasu et al, 2006). In native coronaries morphological composition of atherosclerotic plaque is a useful determinant of the plaque vulnerability (Ehara et al., 2004), (Naghavi et al., 2003), (Valgimigli et al., 2007), and identified plaques with a high-risk of future clinical events (Bae et al., 2008), (Kawaguchi et al., 2007), (Kawamoto et al., 2007). After heart transplantation, simultaneous assessment of virtual histology with IVUS provides detailed information about plaque morphology and composition, may improve the risk stratification of heart transplant recipients (Konig et al., 2008) and add important information in the clinical evaluation of heart transplant recipients

imaging.

**2.3 Three-dimensional reconstruction (3D-IVUS)** 

disease (Bae et al., 2006), (White et al., 2003).

(Raichlin et al., 2009).

**2.4 Virtual Histology Intravascular Ultrasound (VH-IVUS)** 

limitation in the evaluation of atherosclerotic plaque composition.

(Left) Gray scale IVUS cross-section imaging shows concentric plaque: a (PV/SL) of 6.79 and a PI of 32% was calculated

(Right) The corresponding VH-IVUS image depicts specific color-coded plaque components and demonstrates fibrous plaque of 47%, fibrofatty plaque of 20%, dense calcium of 14%, and necrotic core of 27%.PV/SL, plaque volume normalized for segment length; PI, plaque index

Adapted from Raichlin et al., 2007b

Fig. 3. Gray scale IVUS cross-section imaging shows concentric plaque with corresponding VH-IVUS image

#### **2.5 Impact of IVUS in understanding coronary allograft vasculopathy**

Morphologic studies performed with IVUS have led to important insights into the etiology and pathogenesis of CAV.

Coronary artery vasculopathy (CAV) is a multifactorial phenomenon with variable morphologic features. Previous histological ex-vivo studies described two microscopic types of coronary allograft lesions (Johnson, 1989). One type of coronary lesion is confined to the proximal region of epicardial arteries and indistinguishable from typical atherosclerosis of native vessels. The second type is characterized by the presence of vasculitis, involving the entire coronary arterial system and has been suggested to represent the immune mediated vessel injury (Higuchi et al., 1999). The ability to differentiate between the existence of classic atherosclerosis and transplant-specific immunologically mediated CAV holds both prognostic and therapeutic values and this

IVUS in the Assessment of Coronary Allograft Vasculopathy 75

Fig. 4. Grayscale intravascular ultrasound (IVUS) cross-section imaging (bottom) and corresponding virtual histology (VH)-IVUS images (top) from patients with VH-IVUS–

**A** Progression in plaque volume in VH-IVUS derived inflammatory plaque (IP) and noninflammatory

**C** Remodeling index in VH-IVUS derived inflammatory plaque (IP) and noninflammatory plaque (NIP)

Fig. 5. Progression in Plaque Volume, Plaque Index, and Remodeling Index in IP and NIP

The natural history of donor lesions after transplantation is largely unknown. In the 2010 ISHLT registry older donor age is an independent risk factor for early CAV (Stehlik et al.,

Change in Plaque Volume (mm3/mm) **IP** (n=21) 2.42 ± 1.78; **NIP** (n=17) -0.11±1.65; p=0.01 **B** Progression in plaque index in the in VH-IVUS derived inflammatory plaque (IP) and

Change in Plaque Index (%): **IP** (n=21) 7± 9; **NIP** (n=17) 0.1± 8; p=0.04

Remodeling Index: **IP** (n=21) 1.24 ± 0.44, **NIP** (n=17) 1.09 ± 0.36; p=0.03

Adapted from Raichlin et al., 2009

derived inflammatory plaque

plaque (NIP) groups

groups

Groups

noninflammatory plaque (NIP) groups

Adapted from Raichlin et al., 2009

morphologic heterogeneity has been evident in gray scale (Tuzcu et al., 1996) and VH-IVUS study (Raichlin et al., 2009).

Typical atherosclerosis has been detected in 56% of donor hearts despite a mean donor age of thirty-two years (Tuzcu et al., 1995) and IVUS studies have demonstrated that atherosclerotic lesions located in proximal segments, involved the bifurcation sites with eccentric focal plaques, appeared similar to conventional atherosclerosis, were associated with fibrotic and fibro-fatty tissues in VH-IVUS (Konig et al., 2008), (Raichlin et al., 2009) positively correlated with the donor age and probably related to donor-derived coronary atherosclerosis (Kapadia et al., 1998), (Tuzcu et al., 1996).

On other hand de novo lesions assessed by IVUS were diffuse and circumferential, involved more commonly the mid and distal segments of the coronary arteries (Kapadia et al., 1998) and were associated with necrotic core and dense calcium burden ≥ 30%, which presumably reflects the inflammatory burden of the cardiac allograft atherosclerotic plaque (Raichlin et al., 2009). (Figure 4)

Previous studies have demonstrated that early immunological events surrounding engraftment lead to an inflammatory process in the vascular endothelium (Brunner-La Rocca et al., 1998), (Caforio et al., 2004), (Hornick et al., 1997), (Jimenez et al., 2001), (Narrod et al., 1989), (Opelz et al., 1997), (Vassalli et al., 2003), (Yamani et al., 2002). Although CAV may develop at any stage after transplantation, events during the first year, resulting most likely from initial and ongoing immunologically mediated injury to the vascular endothelium appear to be important in CAV pathogenesis (Kobashigawa et al., 2003) leading to more rapid progression in intimal thickening during the first year after transplantation (Kobashigawa et al., 1995), (Mehra et al., 1995d), (Rickenbacher et al., 1995a). A cross-sectional study demonstrated a mean absolute increase of 0.23 mm 10% in intimal thickening and intimal index respectively (Kobashigawa, 1995) during the first year of transplantation. After the first year, the intimal thickness and intimal area do not increase rapidly but new lesions continue to develop at previously normal sites (Kapadia SR et al., 1998). This underscores the importance for continued surveillance for transplant vasculopathy beyond first year after transplantation.

A relationship between immune events and an increase in systemic inflammatory markers following heart transplantation has been shown in several clinical studies (Eisenberg, 2000), (Labarrere, 2002) suggesting that chronic inflammation may be a central event in cardiac allograft vasculopathy. Experimental evidence demonstrated that acute cellular allograft rejection and CAV are closely related processes (Brunner-La Rocca et al., 1998), (Caforio et al., 2004), (Hornick et al., 1997), (Jimenez et al., 2001), (Narrod et al., 1989), (Opelz et al., 1997), (Vassalli et al., 2003), (Yamani et al., 2005) and elevated systemic levels of the inflammatory markers were predictive not only of cardiac allograft vasculopathy but also of allograft failure (Eisenberg & Pethig, 2000), (Hognestad et al., 2003), (Labarrere et al., 2002), (Raichlin et al., 2007b). An association between early recurrent cellular rejections and an increase in intimal thickening (Mehra et al., 1995a) and the presence of necrotic plaque (Raichlin et al., 2007b) has been revealed in 2D and VH-IVUS studies. Moreover, focal inflammation as assessed by VH-IVUS resulted in subsequent progression of CAV. Thus, VH-IVUS can be used for in-vivo identification of patients with increased burden of "inflammatory plaque" and the predicting the progression of CAV following heart transplantation (Raichlin et al., 2009). (Figure 5)

Adapted from Raichlin et al., 2009

morphologic heterogeneity has been evident in gray scale (Tuzcu et al., 1996) and VH-

Typical atherosclerosis has been detected in 56% of donor hearts despite a mean donor age of thirty-two years (Tuzcu et al., 1995) and IVUS studies have demonstrated that atherosclerotic lesions located in proximal segments, involved the bifurcation sites with eccentric focal plaques, appeared similar to conventional atherosclerosis, were associated with fibrotic and fibro-fatty tissues in VH-IVUS (Konig et al., 2008), (Raichlin et al., 2009) positively correlated with the donor age and probably related to donor-derived coronary

On other hand de novo lesions assessed by IVUS were diffuse and circumferential, involved more commonly the mid and distal segments of the coronary arteries (Kapadia et al., 1998) and were associated with necrotic core and dense calcium burden ≥ 30%, which presumably reflects the inflammatory burden of the cardiac allograft atherosclerotic plaque (Raichlin et

Previous studies have demonstrated that early immunological events surrounding engraftment lead to an inflammatory process in the vascular endothelium (Brunner-La Rocca et al., 1998), (Caforio et al., 2004), (Hornick et al., 1997), (Jimenez et al., 2001), (Narrod et al., 1989), (Opelz et al., 1997), (Vassalli et al., 2003), (Yamani et al., 2002). Although CAV may develop at any stage after transplantation, events during the first year, resulting most likely from initial and ongoing immunologically mediated injury to the vascular endothelium appear to be important in CAV pathogenesis (Kobashigawa et al., 2003) leading to more rapid progression in intimal thickening during the first year after transplantation (Kobashigawa et al., 1995), (Mehra et al., 1995d), (Rickenbacher et al., 1995a). A cross-sectional study demonstrated a mean absolute increase of 0.23 mm 10% in intimal thickening and intimal index respectively (Kobashigawa, 1995) during the first year of transplantation. After the first year, the intimal thickness and intimal area do not increase rapidly but new lesions continue to develop at previously normal sites (Kapadia SR et al., 1998). This underscores the importance for continued surveillance for transplant

A relationship between immune events and an increase in systemic inflammatory markers following heart transplantation has been shown in several clinical studies (Eisenberg, 2000), (Labarrere, 2002) suggesting that chronic inflammation may be a central event in cardiac allograft vasculopathy. Experimental evidence demonstrated that acute cellular allograft rejection and CAV are closely related processes (Brunner-La Rocca et al., 1998), (Caforio et al., 2004), (Hornick et al., 1997), (Jimenez et al., 2001), (Narrod et al., 1989), (Opelz et al., 1997), (Vassalli et al., 2003), (Yamani et al., 2005) and elevated systemic levels of the inflammatory markers were predictive not only of cardiac allograft vasculopathy but also of allograft failure (Eisenberg & Pethig, 2000), (Hognestad et al., 2003), (Labarrere et al., 2002), (Raichlin et al., 2007b). An association between early recurrent cellular rejections and an increase in intimal thickening (Mehra et al., 1995a) and the presence of necrotic plaque (Raichlin et al., 2007b) has been revealed in 2D and VH-IVUS studies. Moreover, focal inflammation as assessed by VH-IVUS resulted in subsequent progression of CAV. Thus, VH-IVUS can be used for in-vivo identification of patients with increased burden of "inflammatory plaque" and the predicting the progression of CAV following heart

IVUS study (Raichlin et al., 2009).

al., 2009). (Figure 4)

atherosclerosis (Kapadia et al., 1998), (Tuzcu et al., 1996).

vasculopathy beyond first year after transplantation.

transplantation (Raichlin et al., 2009). (Figure 5)

Fig. 4. Grayscale intravascular ultrasound (IVUS) cross-section imaging (bottom) and corresponding virtual histology (VH)-IVUS images (top) from patients with VH-IVUS– derived inflammatory plaque

**A** Progression in plaque volume in VH-IVUS derived inflammatory plaque (IP) and noninflammatory plaque (NIP) groups

Change in Plaque Volume (mm3/mm) **IP** (n=21) 2.42 ± 1.78; **NIP** (n=17) -0.11±1.65; p=0.01 **B** Progression in plaque index in the in VH-IVUS derived inflammatory plaque (IP) and noninflammatory plaque (NIP) groups

Change in Plaque Index (%): **IP** (n=21) 7± 9; **NIP** (n=17) 0.1± 8; p=0.04

**C** Remodeling index in VH-IVUS derived inflammatory plaque (IP) and noninflammatory plaque (NIP) groups

Remodeling Index: **IP** (n=21) 1.24 ± 0.44, **NIP** (n=17) 1.09 ± 0.36; p=0.03

Adapted from Raichlin et al., 2009

Fig. 5. Progression in Plaque Volume, Plaque Index, and Remodeling Index in IP and NIP Groups

The natural history of donor lesions after transplantation is largely unknown. In the 2010 ISHLT registry older donor age is an independent risk factor for early CAV (Stehlik et al.,

IVUS in the Assessment of Coronary Allograft Vasculopathy 77

2005). (Figure 6 and 7) Thus, the prognostic value of IVUS has significant clinical utility in the identification of a high-risk population and underscores the importance of serial IVUS

Fig. 6. Serial intravascular ultrasound examination at baseline (left side panel) and 1 year follow-up (right side panel) demonstrates significant plaque development at the first year.

Fig. 7. Kaplan-Meier all-cause mortality **(left)** and death and myocardial infarction (MI) **(right)** rates of patients with and without rapidly progressive transplant vasculopathy.

IVUS also provides a sensitive tool to evaluate the effectiveness of different therapeutic and preventive modalities influencing CAV and various clinical protocols have incorporated IVUS findings as surrogate end-points for clinical events. Serial IVUS has been essential as a research tool in studies that assess emerging transplant vasculopathy therapies (Bae et al., 2006), (Eisen et al., 2003), (Fang et al., 2002), (Mehra et al., 1995c), (Raichlin et al., 2007a). The effects of early use of pravastatin on CAV have been assessed by IVUS imaging in a randomized study (Kobashigawa, 1995). 2D-IVUS measurements at baseline and 1 year after

Thick lines - without rapid progression; thin lines - with rapid progression

Transplant vasculopathy at the same site in a coronary vessel segment

examinations (Kapadia et al., 1999).

Adapted from Tuzcu et al., 2010

Adapted from Tuzcu et al., 2005

1089). Several studies, however, have found no significant difference in the rate of intimal thickening between patients with donor hearts having pre-existing coronary artery disease and those without (Botas et al., 1995), (Li et al., 2006). From multiple variables only serum triglyceride level and pre-transplant body mass index were found to be significant predictors for the progression of donor atherosclerosis (Kapadia SR et al., 1998). A VH-IVUS study has demonstrated relatively slow progression of CAV in a group of patients with fibrous, presumably donor-derived plaque (Raichlin et al., 2009).(Figure 5) Several studies, however, have shown that the presence of donor lesions leads to the more frequent development of de novo transplant vasculopathy lesions (Botas et al., 1995), (Escobar et al., 1994), (Gao et al., 1997). The impact of donor and recipient gender on transplant vasculopathy has also been assessed. Male recipients of a female allograft had a higher degree of vascular intimal hyperplasia compared with either male or female recipients of a male allograft as detected by IVUS imaging 1 year after heart transplantation (Mehra et al., 1994).

Arterial remodeling has been studied in the transplant population in serial and crosssectional IVUS study designs. In its early stages, CAV shows no decrease in luminal diameter due to vascular remodeling, thus limiting the ability of angiography to detect and diagnose early CAV (Nissen et al., 2001). Three year serial IVUS studies have shown that the rate of remodeling of donor lesions is different from CAV. Furthermore, the rate of remodeling is different depending on the time interval from transplantation (Ziada et al., 1997). Both compensatory local vessel enlargement (positive remodeling) and vascular constriction (negative remodeling) have been demonstrated and it is thought that inadequate compensatory enlargement probably contributes significantly to luminal obstruction (Pethig et al., 1998). In a study of 3D-VH-IVUS, the coronary arteries with "inflammatory plaque" showed positive remodeling compared to "non-inflammatory plaque" (Raichlin et al., 2009).(Figure 5) These data are consistent with previous findings from a non-transplant population, which showed that inflammation is associated with expansion of the internal elastic lamina and positive remodeling closely correlates with plaque vulnerability (Burke et al., 2004), (Rodriguez-Granillo et al., 2006).

IVUS imaging has also have been used to evaluate the impact of non-immunological factors in the development of transplant vasculopathy lesions. Total cholesterol, low-density lipoprotein cholesterol, triglyceride levels, obesity indexes, donor age greater than 35, and years following cardiac transplantation were independent predictors of the severity of cardiac allograft vasculopathy as determined by the severity of intimal thickening (Escobar et al.,, 1994), (Hauptman et al., 1995), (Mehra et al., 1995), (Rickenbacher et al., 1995b), (Valantine et al., 1995).

#### **2.6 Clinical applications**

Studies performed using IVUS have shown a strong association between the severity of the disease and the clinical outcome. Severe intimal thickening predicted both events (death, MI, and re-transplantation) and survival in patients after transplantation (Mehra et al., 1995b), (Mehra et al., 1995c) regardless of the presence of angiographic CAV (Rickenbacher et al., 1995b). Moreover, rapidly progressive vasculopathy, defined as an increase of ≥ 0.5 mm in intimal thickness within the first year after transplantation, was a powerful predictor of all-cause mortality, nonfatal MI, and the subsequent development of angiographic coronary obstructions independent of other confounding variables, including rejection episodes, age, gender, and conventional risk factors (Kobashigawa et al., 2005), (Tuzcu et al., 2005). (Figure 6 and 7) Thus, the prognostic value of IVUS has significant clinical utility in the identification of a high-risk population and underscores the importance of serial IVUS examinations (Kapadia et al., 1999).

Adapted from Tuzcu et al., 2010

76 Intravascular Ultrasound

1089). Several studies, however, have found no significant difference in the rate of intimal thickening between patients with donor hearts having pre-existing coronary artery disease and those without (Botas et al., 1995), (Li et al., 2006). From multiple variables only serum triglyceride level and pre-transplant body mass index were found to be significant predictors for the progression of donor atherosclerosis (Kapadia SR et al., 1998). A VH-IVUS study has demonstrated relatively slow progression of CAV in a group of patients with fibrous, presumably donor-derived plaque (Raichlin et al., 2009).(Figure 5) Several studies, however, have shown that the presence of donor lesions leads to the more frequent development of de novo transplant vasculopathy lesions (Botas et al., 1995), (Escobar et al., 1994), (Gao et al., 1997). The impact of donor and recipient gender on transplant vasculopathy has also been assessed. Male recipients of a female allograft had a higher degree of vascular intimal hyperplasia compared with either male or female recipients of a male allograft as detected by

Arterial remodeling has been studied in the transplant population in serial and crosssectional IVUS study designs. In its early stages, CAV shows no decrease in luminal diameter due to vascular remodeling, thus limiting the ability of angiography to detect and diagnose early CAV (Nissen et al., 2001). Three year serial IVUS studies have shown that the rate of remodeling of donor lesions is different from CAV. Furthermore, the rate of remodeling is different depending on the time interval from transplantation (Ziada et al., 1997). Both compensatory local vessel enlargement (positive remodeling) and vascular constriction (negative remodeling) have been demonstrated and it is thought that inadequate compensatory enlargement probably contributes significantly to luminal obstruction (Pethig et al., 1998). In a study of 3D-VH-IVUS, the coronary arteries with "inflammatory plaque" showed positive remodeling compared to "non-inflammatory plaque" (Raichlin et al., 2009).(Figure 5) These data are consistent with previous findings from a non-transplant population, which showed that inflammation is associated with expansion of the internal elastic lamina and positive remodeling closely correlates with

IVUS imaging has also have been used to evaluate the impact of non-immunological factors in the development of transplant vasculopathy lesions. Total cholesterol, low-density lipoprotein cholesterol, triglyceride levels, obesity indexes, donor age greater than 35, and years following cardiac transplantation were independent predictors of the severity of cardiac allograft vasculopathy as determined by the severity of intimal thickening (Escobar et al.,, 1994), (Hauptman et al., 1995), (Mehra et al., 1995), (Rickenbacher et al., 1995b),

Studies performed using IVUS have shown a strong association between the severity of the disease and the clinical outcome. Severe intimal thickening predicted both events (death, MI, and re-transplantation) and survival in patients after transplantation (Mehra et al., 1995b), (Mehra et al., 1995c) regardless of the presence of angiographic CAV (Rickenbacher et al., 1995b). Moreover, rapidly progressive vasculopathy, defined as an increase of ≥ 0.5 mm in intimal thickness within the first year after transplantation, was a powerful predictor of all-cause mortality, nonfatal MI, and the subsequent development of angiographic coronary obstructions independent of other confounding variables, including rejection episodes, age, gender, and conventional risk factors (Kobashigawa et al., 2005), (Tuzcu et al.,

IVUS imaging 1 year after heart transplantation (Mehra et al., 1994).

plaque vulnerability (Burke et al., 2004), (Rodriguez-Granillo et al., 2006).

(Valantine et al., 1995).

**2.6 Clinical applications** 

Fig. 6. Serial intravascular ultrasound examination at baseline (left side panel) and 1 year follow-up (right side panel) demonstrates significant plaque development at the first year. Transplant vasculopathy at the same site in a coronary vessel segment

Adapted from Tuzcu et al., 2005

Fig. 7. Kaplan-Meier all-cause mortality **(left)** and death and myocardial infarction (MI) **(right)** rates of patients with and without rapidly progressive transplant vasculopathy. Thick lines - without rapid progression; thin lines - with rapid progression

IVUS also provides a sensitive tool to evaluate the effectiveness of different therapeutic and preventive modalities influencing CAV and various clinical protocols have incorporated IVUS findings as surrogate end-points for clinical events. Serial IVUS has been essential as a research tool in studies that assess emerging transplant vasculopathy therapies (Bae et al., 2006), (Eisen et al., 2003), (Fang et al., 2002), (Mehra et al., 1995c), (Raichlin et al., 2007a). The effects of early use of pravastatin on CAV have been assessed by IVUS imaging in a randomized study (Kobashigawa, 1995). 2D-IVUS measurements at baseline and 1 year after

IVUS in the Assessment of Coronary Allograft Vasculopathy 79

Coronary angiography has a high specificity of 97.8% but only moderate sensitivity of 79.3% in CAV detection. The intimal changes in CAV are best detected by intravascular ultrasound, which has become the gold standard for the early diagnosis of CAV. The prognostic value of IVUS has significant clinical utility in identification a high-risk population and underscores the importance of serial IVUS examinations during annual routine screening of heart transplant recipients. 3D-IVUS with simultaneous assessment of virtual histology may add important information in the clinical evaluation of heart

Bae, J.H., Rihal, C.S., Edwards, B.S., Kushwaha, S.S., Mathew, V., Prasad, A., et al. (2006).

Bae, J.H., Kwon, T.G., Hyun, D.W., Rihal, C.S., & Lerman, A. (2008). Predictors of Slow Flow

Baldwin, J.C., Oyer, P.E., Stinson, E.B., Starnes, V.A., Billingham, M.E., & Shumway, N.E.

Batkoff, B.W., Linker, D.T. (1996). Safety of intracoronary ultrasound: data from a Multicenter European Registry. *Cathet Cardiovasc Diagn.* 38(3):238-41 Botas, J., Pinto, F.J., Chenzbraun, A., Liang, D., Schroeder, J.S., Oesterle, S.N., et al. (1995).

Brunner-La Rocca, H.P., Schneider, J., Kunzli, A., Turina, M., & Kiowski, W. (1998). Cardiac

Burke, A.P., Kolodgie, F.D., Zieske, A., Fowler, D.R., Weber, D.K., Varghese, P.J., et al.

Caforio, A.L., Tona, F., Fortina, A.B., Angelini, A., Piaserico, S., Gambin,o A., et al. (2004).

Cale, R., Almeida, M., Rebocho, M.J., Aguiar, C., Sousa, P., Brito, J., et al. (2010). The value of

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postmortem study. *Arterioscler Thromb Vasc Biol.* 24(7):1266-71

allograft recipients. *Rev Port Cardiol.* Feb;29(2):231-41

exercise thallium scintigraphy. *Eur Heart J.* 14(2):226-9

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(1987). Comparison of cardiac rejection in heart and heart-lung transplantation. *J* 

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allograft rejection late after transplantation is a risk factor for graft coronary artery

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routine intracoronary ultrasound to assess coronary artery disease in cardiac

Coronary artery disease after heart transplantation: non-invasive evaluation with

**3. Conclusion** 

transplant recipients.

27;82(8):1108-11

Virtual Histology Study*. Heart*. 1:1

disease. *Transplantation.* Feb 27;65(4):538-43

*Heart Transplant.* 6(6):352-6

*Transplant.* Jun;4(6):962-70

**4. References** 

32

transplantation showed less increase in MIT and maximal intimal index with pravastatin therapy. The incidence of coronary vasculopathy as determined by angiography and at autopsy also was lower (Kobashigawa, 1995).

The influence of angiotensin-converting enzyme inhibitors and calcium blockers on the development of CAV has also been assessed. Mehra et al., using IVUS, demonstrated that heart transplant recipients treated with either diltiazem or angiotensin-converting enzyme inhibitors, or both have significantly less intimal hyperplasia 1 year after cardiac transplantation than matched untreated control subjects (Mehra et al., 1995b), (Mehra et al., 1995c). Another IVUS study has demonstrated that a combination of a calcium channel blocker and an angiotensin-converting enzyme inhibitors is more effective in CAV prevention than the individual use of either drug alone. This effect was independent of mean arterial pressure, suggesting these drugs have a synergistic anti-proliferative effect beyond the anti-hypertensive efficacy (Erinc et al., 2005). Moreover, a 3D-IVUS study demonstrated that lower serum lipid levels and angiotensin-converting enzyme inhibitors use in patients after heart transplantation is associated with CAV plaque regression (Bae et al., 2006). The question of whether supplementation with antioxidant vitamins C and E retards the early progression of CAV has also been assessed by 2D-IVUS (Fang et al., 2002).

IVUS imaging has been used to evaluate the effect of immunosuppressive therapy on the development of CAV. A randomized, double-blind trial, comparing mycophenolate mofetil with azathioprine as adjuvant to cyclosporine, revealed that the change in mean MIT was less for the mycophenolate mofetil group than for the azathioprine group (*p* = 0.056) (Eisen et al., 2005).

The first clinical evidence that proliferation signal inhibitors (PSIs) could limit the development of CAV in heart transplant recipients was provided by an international multicenter randomized, double-blind study (Eisen et al., 2003) comparing everolimus with azathioprine as adjuvant to full dose of cyclosporin in 634 de-novo heart transplant patients. The results of the intravascular substudy with matched analysis of baseline and 1-year images were available for 211 patients. The average increase in intimal thickness was significantly larger with azathioprine than with everolimus. The 12 months of double-blind period of this study were followed by 12 month of open-labeled period (Vigano et al., 2007) in 149 patients and showed that continued treatment with everolimus limits the progression of intimal thickening and lowers the incidence of allograft vasculopathy at 24 months when compared with azathioprine.

Similar benefits have also been seen in patients treated with sirolimus. In an open-labeled study (Keogh, 2004) of 136 de-novo transplant patients randomized to sirolimus or azathioprine, IVUS showed that the use of sirolimus significantly reduced the progression in intimal and media proliferation by six months, whereas azathioprine therapy resulted in increased plaque volume and plaque burden over time. This effect was sustained at two years.

The first evidence of using sirolimus for primary immunosuppression after heart transplantation demonstrated that complete CNI withdrawal and replacement with SRL results in attenuation of CAV progression by reducing intimal hyperplasia as evidenced by 3D-IVUS. Treatment with azathioprine or mycophenolate mofetil did not significantly affect the results. A CNI-free regimen was more effective when initiated within the first two years following transplantation (Raichlin et al., 2007a).

#### **3. Conclusion**

78 Intravascular Ultrasound

transplantation showed less increase in MIT and maximal intimal index with pravastatin therapy. The incidence of coronary vasculopathy as determined by angiography and at

The influence of angiotensin-converting enzyme inhibitors and calcium blockers on the development of CAV has also been assessed. Mehra et al., using IVUS, demonstrated that heart transplant recipients treated with either diltiazem or angiotensin-converting enzyme inhibitors, or both have significantly less intimal hyperplasia 1 year after cardiac transplantation than matched untreated control subjects (Mehra et al., 1995b), (Mehra et al., 1995c). Another IVUS study has demonstrated that a combination of a calcium channel blocker and an angiotensin-converting enzyme inhibitors is more effective in CAV prevention than the individual use of either drug alone. This effect was independent of mean arterial pressure, suggesting these drugs have a synergistic anti-proliferative effect beyond the anti-hypertensive efficacy (Erinc et al., 2005). Moreover, a 3D-IVUS study demonstrated that lower serum lipid levels and angiotensin-converting enzyme inhibitors use in patients after heart transplantation is associated with CAV plaque regression (Bae et al., 2006). The question of whether supplementation with antioxidant vitamins C and E retards the early progression of CAV has also been assessed by 2D-IVUS (Fang et al.,

IVUS imaging has been used to evaluate the effect of immunosuppressive therapy on the development of CAV. A randomized, double-blind trial, comparing mycophenolate mofetil with azathioprine as adjuvant to cyclosporine, revealed that the change in mean MIT was less for the mycophenolate mofetil group than for the azathioprine group (*p* = 0.056) (Eisen

The first clinical evidence that proliferation signal inhibitors (PSIs) could limit the development of CAV in heart transplant recipients was provided by an international multicenter randomized, double-blind study (Eisen et al., 2003) comparing everolimus with azathioprine as adjuvant to full dose of cyclosporin in 634 de-novo heart transplant patients. The results of the intravascular substudy with matched analysis of baseline and 1-year images were available for 211 patients. The average increase in intimal thickness was significantly larger with azathioprine than with everolimus. The 12 months of double-blind period of this study were followed by 12 month of open-labeled period (Vigano et al., 2007) in 149 patients and showed that continued treatment with everolimus limits the progression of intimal thickening and lowers the incidence of allograft vasculopathy at 24 months when

Similar benefits have also been seen in patients treated with sirolimus. In an open-labeled study (Keogh, 2004) of 136 de-novo transplant patients randomized to sirolimus or azathioprine, IVUS showed that the use of sirolimus significantly reduced the progression in intimal and media proliferation by six months, whereas azathioprine therapy resulted in increased plaque volume and plaque burden over time. This effect was sustained at

The first evidence of using sirolimus for primary immunosuppression after heart transplantation demonstrated that complete CNI withdrawal and replacement with SRL results in attenuation of CAV progression by reducing intimal hyperplasia as evidenced by 3D-IVUS. Treatment with azathioprine or mycophenolate mofetil did not significantly affect the results. A CNI-free regimen was more effective when initiated within the first two years

autopsy also was lower (Kobashigawa, 1995).

2002).

et al., 2005).

two years.

compared with azathioprine.

following transplantation (Raichlin et al., 2007a).

Coronary angiography has a high specificity of 97.8% but only moderate sensitivity of 79.3% in CAV detection. The intimal changes in CAV are best detected by intravascular ultrasound, which has become the gold standard for the early diagnosis of CAV. The prognostic value of IVUS has significant clinical utility in identification a high-risk population and underscores the importance of serial IVUS examinations during annual routine screening of heart transplant recipients. 3D-IVUS with simultaneous assessment of virtual histology may add important information in the clinical evaluation of heart transplant recipients.

#### **4. References**


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**1. Introduction** 

vulnerable lesions.

**1.1 Intravascular ultrasound (IVUS) and clinical applications** 

Atherosclerosis is a chronic disease potentially involving the whole vascular system that causes a spectrum of clinical manifestations ranging from stable angina to acute myocardial infarction or stroke. The continuous accumulation of lipids, inflammatory and/or fibrous elements in the arterial wall leads to progressive lumen narrowing. Acute coronary syndromes (acute myocardial infarction, unstable angina) have a complex and dynamic pathogenesis with coronary plaque rupture. Some plaques lead to clinical events whereas many others remain asymptomatic for life, different imaging modalities have been applied to define the atherosclerotic burden and the anatomical characteristics of unstable or

The vascular response to endothelial dysfonction is a well-orchestrated inflammatory response triggered by the accumulation of macrophages within the vessel wall. The formation of such vulnerable plaques prone to rupture underlies the majority of cases of acute myocardial infarction. The complex molecular and cellular inflammatory cascade is orchestrated by the recruitment of T lymphocytes and macrophages and their paracrine effects on endothelial and smooth muscle cells (1). Molecular imaging in atherosclerosis has evolved into an important clinical and research tool that allows in vivo visualization of inflammation and other biological processes. Several recent examples demonstrate the ability to detect high-risk plaques in

Intravascular ultrasound (IVUS) performed with an ultrasound machine that has been especially adapted to intravascular imaging. The machine can be permanently affixed in the catheterization lab or can be portable and moved from one catheterization room to another as needed. The IVUS catheter is attached to the ultrasound machine through an interface that ensures sterility of the catheter. Intravascular ultrasound is an exciting technology that allows in-vivo visualization of vascular anatomy by utilizing a miniature transducer. The IVUS catheter can be advanced into different vascular structures including peripheral arteries, coronary arteries, and intracardiac chambers. Intracoronary ultrasound has become particularly useful in further delineating plaque morphology and distribution, and providing a rationale to guide transcatheter coronary interventions (3). The reflected ultrasound from the intima is displayed as a single concentric echo. All of the ultrasound, however, is not reflected

patients, and assess the effects of pharmacotherapeutics in atherosclerosis (2).

**6** 

T. Ozcan

*Turkey* 

**Intravascular Ultrasound** 

*Mersin University, Faculty of Medicine, Department of Cardiology, Mersin* 

**(IVUS) and Clinical Applications** 


## **Intravascular Ultrasound (IVUS) and Clinical Applications**

#### T. Ozcan

*Mersin University, Faculty of Medicine, Department of Cardiology, Mersin Turkey* 

#### **1. Introduction**

86 Intravascular Ultrasound

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E.M. (1997). Three year ultrasound follow-up of donor transmitted atherosclerosis

#### **1.1 Intravascular ultrasound (IVUS) and clinical applications**

Atherosclerosis is a chronic disease potentially involving the whole vascular system that causes a spectrum of clinical manifestations ranging from stable angina to acute myocardial infarction or stroke. The continuous accumulation of lipids, inflammatory and/or fibrous elements in the arterial wall leads to progressive lumen narrowing. Acute coronary syndromes (acute myocardial infarction, unstable angina) have a complex and dynamic pathogenesis with coronary plaque rupture. Some plaques lead to clinical events whereas many others remain asymptomatic for life, different imaging modalities have been applied to define the atherosclerotic burden and the anatomical characteristics of unstable or vulnerable lesions.

The vascular response to endothelial dysfonction is a well-orchestrated inflammatory response triggered by the accumulation of macrophages within the vessel wall. The formation of such vulnerable plaques prone to rupture underlies the majority of cases of acute myocardial infarction. The complex molecular and cellular inflammatory cascade is orchestrated by the recruitment of T lymphocytes and macrophages and their paracrine effects on endothelial and smooth muscle cells (1). Molecular imaging in atherosclerosis has evolved into an important clinical and research tool that allows in vivo visualization of inflammation and other biological processes. Several recent examples demonstrate the ability to detect high-risk plaques in patients, and assess the effects of pharmacotherapeutics in atherosclerosis (2).

Intravascular ultrasound (IVUS) performed with an ultrasound machine that has been especially adapted to intravascular imaging. The machine can be permanently affixed in the catheterization lab or can be portable and moved from one catheterization room to another as needed. The IVUS catheter is attached to the ultrasound machine through an interface that ensures sterility of the catheter. Intravascular ultrasound is an exciting technology that allows in-vivo visualization of vascular anatomy by utilizing a miniature transducer. The IVUS catheter can be advanced into different vascular structures including peripheral arteries, coronary arteries, and intracardiac chambers. Intracoronary ultrasound has become particularly useful in further delineating plaque morphology and distribution, and providing a rationale to guide transcatheter coronary interventions (3). The reflected ultrasound from the intima is displayed as a single concentric echo. All of the ultrasound, however, is not reflected

Intravascular Ultrasound (IVUS) and Clinical Applications 89

In cases of coronary dissection, IVUS can distinguish atherosclerotic plaques from intramural hematoma and also detect the media dissection, false and true lumen and, if present, the intimal flap. Treatment of spontaneous dissection in particular is often especially challenging, since it commonly affects young individuals with little or no atherosclerotic burden. Ther-apy has traditionally been guided by clinical and angiographic findings. However, in small series of patients IVUS has been proven useful in the context of

There are some controversies between the results of the studies which compared the CIMT values of SCF patients and normal subject. A previous study shows that patients with SCF have a signicantly increased carotid IMT compared with those with normal coronary ow (34). But recent studies do not support this result (35). The investigated these values with comparing the IVUS and TIMI frame counts. Measurements of CIMT using ultrasound assess the extent and the severity of systemic atherosclerosis. Today, CIMT, measured with high-resolution B-mode ultrasound, is the standard for noninvasive surrogate measurements of atherosclerosis. It has been shown that a direct relation exits between CIMT and clinical cardiovascular disease (19-22). Due to these data, CIMT assessment can be used to document regression or progression of atherosclerosis (19-36) Besides, at least two large epidemiologic studies proposed that increased CIMT values are associated prospectively with increased risk of coronary artery disease (24,25,37). Several studies, CIMT was signicantly increased in SCF patients. This would mean the increased risk of coronary, cerebral and peripheral vascular diseases in these patients. However these risks are still not studied enough, and are unknown in this special group of patients. It was shown another study diffuse or regional calcication and intimal thickening in coronary arteries in most of the patients with SCF, despite the absence of angiographically detectable coronary focal stenosis or plaques in them. These results suggest that epicardial coronary arteries were affected as a part of diffuse atherosclerotic disease of all arterial system in this specic group of patients. IVUS imaging can detect early intimal thickening, which cannot be detected by conventional angiography (28-30,38). Some previous studies have shown the evidence of diffuse atherosclerosis despite angiographically normal coronary arteries in syndrome-X patients by intravascular ultrasound (28-30). Pekdemir et al. showed that most patients with SCF had longitudinally extended massive calcication throughout the epicardial coronary arteries. Cin et al. demonstrated that the patients with SCF had diffuse intimal thickening, widespread calcication along the coronary vessel wall, and atheroma which did not cause luminal irregularities in the coronary angiography (39,40). In the present study, according to the ndings of IVUS, the speculate that SCF may be a form or preliminary phase of diffuse atherosclerotic process that involve epicardial coronary arteries. However, in a previous study, Chilian et al. (41) have observed enhanced vasoconstrictor response in the monkeys with atherosclerosis and they speculated that the early pathophysiological consequences of atherosclerosis might extend into the microcirculation, which may be another mechanism for SCF. Erdogan et al. (42) suggest that coronary ow reserve (CFR) is impaired in patients with SCF. Impairment of endothelial function and reduced CFR, which reects coronary microvascular function, has been shown to be early manifestation of atherosclerosis. Mangieri et al. (12) and Kurtoglu et al. [11] have observed remarkable progress in restoring coronary ow when they studied dypyridamole in this group of patients. They concluded the theory that the pathophysiology underlying this disorder is closely related to the microvasculature and has a dynamic character. Near these

interventional treatment (33).

by the intima; some will penetrate through to the media. Since the media is composed primarily of homogeneous smooth muscle cells, ultrasound passes through with minimal reflection and appears as a dark zone devoid of echoes. The adventitia, is highly reflective because it has numerous collagen fibers laid down in parallel, thereby producing multiple interfaces from which to reflect sound. The adventitia will appear very bright. As a result, the normal coronary anatomy produces alternating bright and dark echoes:

1-A bright echo from the intima, 2-A dark zone from the media, 3-Multiple bright echoes from the adventitia

This pattern is called the normal "three layer appearance" of a coronary artery (4). The threelayer appearance is actually a simplified view since the IVUS resolution (approximately 120 microns) is not sufficient to detect the truly nondiseased intima (one or two cell layers thick or approximately 50 microns). The tomographic cross-sectional view of the artery is ideal to discern concentric from eccentric plaque distribution. This feature makes IVUS far more accurate than angiography for assessing plaque eccentricity (3). Because of the limitations of angiography, hazy angiographic sites could represent an irregular plaque/distorted lumen, a napkin-ring lesion, thrombus, or a dissection. IVUS is particularly useful in this situation because it immediately distinguishes between plaque and lumen irregularities, dissection, or discrete stenosis (5).

IVUS has also demonstrated that apparently normal areas by angiography are often markedly abnormal. One of the areas that IVUS can be useful is Slow coronary ow (SCF). Slow coronary ow is characterized with the late opacication of the epicardial coronary arteries without occlusive disease (6,7). It was rst described by Tambe et al. in 1972 (10). In 1973, Kemp et al. suggested it to be a variant of "syndrome X" (11). However, SCF differs in a distinct manner in which is a phenomenon characterized by delayed opacication of epicardial coronary arteries in the absence of epicardial occlusive disease. The exact etiology, pathogenesis and long term outcome of SCF patients is still unknown. Endothelial and vasomotor dysfunction, microvascular dysfunction, and occlusive disease of small coronary arteries were suggested in its etiology (8-17). The carotid artery intima-media thickness (CIMT) is the best known sonographic marker for early atherosclerotic vascular wall lesions (18). Previous cross-sectional studies in different populations have shown that, increase in CIMT is associated with cardiovascular event prevalence (19-25). Additionally, CIMT increase was strongly and signicantly correlated with myocardial infarction and stroke incidence (26). Angiography depicts only 2D silhouette of the lumen, whereas IVUS allows tomographic assessment of lumen area, plaque size, distribution, and composition. In young subjects, normal intimal thickness is typical 0.15 mm (27). Intravascular ultrasound (IVUS) can detect intimal thickening of the coronary arteries and is suitable for detection of early atherosclerosis that cannot be detected by conventional angiography (28-30).

In additon Intravascular ultrasound (IVUS) is useful during stent implantation to assess lesion severity, length, and morphology before stent implantation; to optimize stent expansion, extension, and apposition; and to identify and treat possible complications after stent implantation (31). Most of the evidence from the era of bare-metal stents indicates that IVUS guidance offers incremental information leading to lower rates of angiographic restenosis and repeat revascularization (32). In the current era of drug-eluting stents (DES) with ensuing low restenosis rates, the relationship between IVUS-guided DES implantation and clinical outcomes is less well established.

by the intima; some will penetrate through to the media. Since the media is composed primarily of homogeneous smooth muscle cells, ultrasound passes through with minimal reflection and appears as a dark zone devoid of echoes. The adventitia, is highly reflective because it has numerous collagen fibers laid down in parallel, thereby producing multiple interfaces from which to reflect sound. The adventitia will appear very bright. As a result, the

1-A bright echo from the intima, 2-A dark zone from the media, 3-Multiple bright echoes

This pattern is called the normal "three layer appearance" of a coronary artery (4). The threelayer appearance is actually a simplified view since the IVUS resolution (approximately 120 microns) is not sufficient to detect the truly nondiseased intima (one or two cell layers thick or approximately 50 microns). The tomographic cross-sectional view of the artery is ideal to discern concentric from eccentric plaque distribution. This feature makes IVUS far more accurate than angiography for assessing plaque eccentricity (3). Because of the limitations of angiography, hazy angiographic sites could represent an irregular plaque/distorted lumen, a napkin-ring lesion, thrombus, or a dissection. IVUS is particularly useful in this situation because it immediately distinguishes between plaque and lumen irregularities, dissection, or

IVUS has also demonstrated that apparently normal areas by angiography are often markedly abnormal. One of the areas that IVUS can be useful is Slow coronary ow (SCF). Slow coronary ow is characterized with the late opacication of the epicardial coronary arteries without occlusive disease (6,7). It was rst described by Tambe et al. in 1972 (10). In 1973, Kemp et al. suggested it to be a variant of "syndrome X" (11). However, SCF differs in a distinct manner in which is a phenomenon characterized by delayed opacication of epicardial coronary arteries in the absence of epicardial occlusive disease. The exact etiology, pathogenesis and long term outcome of SCF patients is still unknown. Endothelial and vasomotor dysfunction, microvascular dysfunction, and occlusive disease of small coronary arteries were suggested in its etiology (8-17). The carotid artery intima-media thickness (CIMT) is the best known sonographic marker for early atherosclerotic vascular wall lesions (18). Previous cross-sectional studies in different populations have shown that, increase in CIMT is associated with cardiovascular event prevalence (19-25). Additionally, CIMT increase was strongly and signicantly correlated with myocardial infarction and stroke incidence (26). Angiography depicts only 2D silhouette of the lumen, whereas IVUS allows tomographic assessment of lumen area, plaque size, distribution, and composition. In young subjects, normal intimal thickness is typical 0.15 mm (27). Intravascular ultrasound (IVUS) can detect intimal thickening of the coronary arteries and is suitable for detection of

early atherosclerosis that cannot be detected by conventional angiography (28-30).

and clinical outcomes is less well established.

In additon Intravascular ultrasound (IVUS) is useful during stent implantation to assess lesion severity, length, and morphology before stent implantation; to optimize stent expansion, extension, and apposition; and to identify and treat possible complications after stent implantation (31). Most of the evidence from the era of bare-metal stents indicates that IVUS guidance offers incremental information leading to lower rates of angiographic restenosis and repeat revascularization (32). In the current era of drug-eluting stents (DES) with ensuing low restenosis rates, the relationship between IVUS-guided DES implantation

normal coronary anatomy produces alternating bright and dark echoes:

from the adventitia

discrete stenosis (5).

In cases of coronary dissection, IVUS can distinguish atherosclerotic plaques from intramural hematoma and also detect the media dissection, false and true lumen and, if present, the intimal flap. Treatment of spontaneous dissection in particular is often especially challenging, since it commonly affects young individuals with little or no atherosclerotic burden. Ther-apy has traditionally been guided by clinical and angiographic findings. However, in small series of patients IVUS has been proven useful in the context of interventional treatment (33).

There are some controversies between the results of the studies which compared the CIMT values of SCF patients and normal subject. A previous study shows that patients with SCF have a signicantly increased carotid IMT compared with those with normal coronary ow (34). But recent studies do not support this result (35). The investigated these values with comparing the IVUS and TIMI frame counts. Measurements of CIMT using ultrasound assess the extent and the severity of systemic atherosclerosis. Today, CIMT, measured with high-resolution B-mode ultrasound, is the standard for noninvasive surrogate measurements of atherosclerosis. It has been shown that a direct relation exits between CIMT and clinical cardiovascular disease (19-22). Due to these data, CIMT assessment can be used to document regression or progression of atherosclerosis (19-36) Besides, at least two large epidemiologic studies proposed that increased CIMT values are associated prospectively with increased risk of coronary artery disease (24,25,37). Several studies, CIMT was signicantly increased in SCF patients. This would mean the increased risk of coronary, cerebral and peripheral vascular diseases in these patients. However these risks are still not studied enough, and are unknown in this special group of patients. It was shown another study diffuse or regional calcication and intimal thickening in coronary arteries in most of the patients with SCF, despite the absence of angiographically detectable coronary focal stenosis or plaques in them. These results suggest that epicardial coronary arteries were affected as a part of diffuse atherosclerotic disease of all arterial system in this specic group of patients. IVUS imaging can detect early intimal thickening, which cannot be detected by conventional angiography (28-30,38). Some previous studies have shown the evidence of diffuse atherosclerosis despite angiographically normal coronary arteries in syndrome-X patients by intravascular ultrasound (28-30). Pekdemir et al. showed that most patients with SCF had longitudinally extended massive calcication throughout the epicardial coronary arteries. Cin et al. demonstrated that the patients with SCF had diffuse intimal thickening, widespread calcication along the coronary vessel wall, and atheroma which did not cause luminal irregularities in the coronary angiography (39,40). In the present study, according to the ndings of IVUS, the speculate that SCF may be a form or preliminary phase of diffuse atherosclerotic process that involve epicardial coronary arteries. However, in a previous study, Chilian et al. (41) have observed enhanced vasoconstrictor response in the monkeys with atherosclerosis and they speculated that the early pathophysiological consequences of atherosclerosis might extend into the microcirculation, which may be another mechanism for SCF. Erdogan et al. (42) suggest that coronary ow reserve (CFR) is impaired in patients with SCF. Impairment of endothelial function and reduced CFR, which reects coronary microvascular function, has been shown to be early manifestation of atherosclerosis. Mangieri et al. (12) and Kurtoglu et al. [11] have observed remarkable progress in restoring coronary ow when they studied dypyridamole in this group of patients. They concluded the theory that the pathophysiology underlying this disorder is closely related to the microvasculature and has a dynamic character. Near these

Intravascular Ultrasound (IVUS) and Clinical Applications 91

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dysfunction in patients with chest pain and normal coronary arteries. Circulation

coronary vasodilatation in patients with angina pectoris and normal coronary

dependent vasodilation of the coronary resistance vessels is associated with

thickness and brachial-ankle pulse wave velocity in patients with and without

associated with left ventricular mass in older adults (a report from the

the common carotid arteries and lower limbs atherosclerosis in the elderly.

of major coronary risk factors and the acceleration of carotid atherosclerosis in the

with carotid arterial wall thickness and major risk factors: the atherosclerosis risk in

adults with minimal clinical or subclinical cardiovascular disease. J Am Geriatr Soc

intima and media thickness as a risk factor for myocardial infarction and stroke in

intravascular ultrasound application of simultaneous measurements of luminal

results, some other studies have shown the evidence of diffuse epicardial atherosclerosis despite angiographically normal coronary arteries (28-30,43). All these data, however, do not clearly delineate the borders of this disorder neither does it imply any interaction between micro and macrovasculature of the heart. In the present study, the correlation of TIMI frame count and the CIMT and coronary intima-media thickness suggest the atherosclerosis would be the pathophysiological mechanism of the disease. However, it is impossible to conclude any suggestion about microvascular pathology. The occurrence of myocardial ischemia was only sporadically demonstrated in these patients. It is concluded that most of these patients continue to experience regular and/or worsening chest pain despite reassurance that they do not have obstructed coronary arteries (44).

Prior to IVUS, only the lumen of a vessel could be visualized in vivo with angiography or angioscopy. IVUS extends our capability to visualize and assess the size of the vessel, should it be devoid of atherosclerotic disease. Prior to a discussion of the applications of IVUS, it is important to appreciate the added information provided by this procedure when compared with conventional angiography for the assessment of coronary artery disease. Today intravascular ultrasound (IVUS) offers qualitative details on plaque composition, like hard and soft components, that are helpful to assess unstable lesions. As a result, the appropriate indications and clinical cases provide impotant information.

#### **2. References**


results, some other studies have shown the evidence of diffuse epicardial atherosclerosis despite angiographically normal coronary arteries (28-30,43). All these data, however, do not clearly delineate the borders of this disorder neither does it imply any interaction between micro and macrovasculature of the heart. In the present study, the correlation of TIMI frame count and the CIMT and coronary intima-media thickness suggest the atherosclerosis would be the pathophysiological mechanism of the disease. However, it is impossible to conclude any suggestion about microvascular pathology. The occurrence of myocardial ischemia was only sporadically demonstrated in these patients. It is concluded that most of these patients continue to experience regular and/or worsening chest pain

Prior to IVUS, only the lumen of a vessel could be visualized in vivo with angiography or angioscopy. IVUS extends our capability to visualize and assess the size of the vessel, should it be devoid of atherosclerotic disease. Prior to a discussion of the applications of IVUS, it is important to appreciate the added information provided by this procedure when compared with conventional angiography for the assessment of coronary artery disease. Today intravascular ultrasound (IVUS) offers qualitative details on plaque composition, like hard and soft components, that are helpful to assess unstable lesions. As a result, the

[1] Andersson, J., Libby, P., *et al.* Adaptive immunity and atherosclerosis. Clin Immunol*.* 134

[2] Jaffer, F. A., Libby, P. *et al.* Molecular Imaging of Cardiovascular Disease. Circulation*.*

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[6] Lierde JV, Vrolix M, Sionis D, De Geest H, Piessens J. Lack of evidence for small vessel

[7] Yigit F, Sezgin AT, Demircan S, et al. Slow coronary flow is associated with carotid

[8] Tambe AA, Demany MA, Zimmerman HA, Mascarenhas E. Angina pectoris and slow

[9] Kemp Jr HG, Vokonas PS, Cohn PF, Gorlin R. The anginal syndrome associated with

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**Part 2** 

**Interventional Applications** 


## **Part 2**

**Interventional Applications** 

92 Intravascular Ultrasound

[29] Mintz GS, Painter JA, Pichard AD, et al. Atherosclerosis in angiographically "normal"

[30] Tuzcu EM, Kapadia SR, Tutar E, et al. High prevalence of coronary atherosclerosis in

[31] Mintz GS, Nissen SE, Anderson WD, et al. American College of Cardiology clinical

[32] Parise H, Maehara A, Stone GW, Leon MB, Mintz GS. Metaanalysis of randomized

[33] Arnold JR, West NE, van Gaal WJ, Karamitsos TD, Banning AP. The role of

[34] Tanriverdi H, Evrengul H. Carotid intima.–media thickness in coronary slow flow: relationship with plasma homocysteine levels. Coron Artery Dis 2006;17(4):331–7. [35] Yigit F, Sezgin AT, Demircan S, et al. Slow coronary flow is associated with carotid

[36] Ishizu T, Ishimitsu T, Kamiya H, et al. The correlation of irregularities in carotid arterial intima-media thickness with coronary artery disease. Heart Vessels 2002;17(1):1–6. [37] Cerne A, Kranjec I. Atherosclerotic burden in coronary and peripheral arteries in

[38] Kawano S, Yamagishi M, Hao H, Yutani C, Miyatake K.Wall composition in

[39] Pekdemir H, Polat G, CinVG, et al. Elevated plasma endothelin-1 levels in coronary

[40] Cin VG, Pekdemir H, Camsar A, et al. Diffuse intimal thickening of coronary arteries in

[41] ChillianWM,Dellsperger KC, Layne SM, et al. Effects of atherosclerosis on the coronary

[42] Erdogan D, Caliskan M, Gullu H, et al. Coronary flow reserve is impaired in patients

[43] Nissen SE, Gurley JC, Grines CL, et al. Intravascular ultrasound assessment of lumen

[44] Przybojewski JZ, Becker PH. Angina pectoris and acute myocardial infarction due to

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intravascular ultrasound in the management of spontaneous coronary artery

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sinus during rapid right atrial pacing in patients with slow coronary flow. Int J

**7** 

*Ireland* 

**Clinical Applications of** 

*University College Hospital Galway* 

**Intravascular Ultrasound** 

Dermot Phelan, Sajjad Matiullah and Faisal Sharif

Intravascular Ultrasound (IVUS) is an invasive grey scale tomographic imaging modality providing cross-sectional images of the vessel wall. The reflected or scattered ultrasound signal received at the transducer is converted to a voltage. This voltage is known as radiofrequency data or backscattered signal. The time delay and amplitude of these emitting pulses provides 256 such backscattered signals or A-scans to produce one image. For IVUS imaging, high ultrasound frequencies typically centred between 25-50 MHz are used. The size of conventional IVUS catheter is 2.9 and 3.5 Fr and has a typical pullback speed of 0.5 mm/s and a frame rate of 30 images per second. At 30 MHz the wavelength is 50 m, which yields a spatial resolution of >150m allowing detail evaluation of the blood vessel wall. IVUS imaging is complementary to coronary angiography and allows the simultaneous assessment of lumen and components of the vessel wall. In the IVUS image the catheter is in the centre of the image surrounded by vessel lumen, the three layers of the vessel and surrounding structures (Figure 1). It can assess plaque geometry including plaque burden and size, luminal area, longitudinal extent of the disease, circumferential extent of the

**1. Introduction** 

Fig. 1. IVUS of normal coronary artery

## **Clinical Applications of Intravascular Ultrasound**

Dermot Phelan, Sajjad Matiullah and Faisal Sharif *University College Hospital Galway Ireland* 

#### **1. Introduction**

Intravascular Ultrasound (IVUS) is an invasive grey scale tomographic imaging modality providing cross-sectional images of the vessel wall. The reflected or scattered ultrasound signal received at the transducer is converted to a voltage. This voltage is known as radiofrequency data or backscattered signal. The time delay and amplitude of these emitting pulses provides 256 such backscattered signals or A-scans to produce one image. For IVUS imaging, high ultrasound frequencies typically centred between 25-50 MHz are used. The size of conventional IVUS catheter is 2.9 and 3.5 Fr and has a typical pullback speed of 0.5 mm/s and a frame rate of 30 images per second. At 30 MHz the wavelength is 50 m, which yields a spatial resolution of >150m allowing detail evaluation of the blood vessel wall. IVUS imaging is complementary to coronary angiography and allows the simultaneous

assessment of lumen and components of the vessel wall. In the IVUS image the catheter is in the centre of the image surrounded by vessel lumen, the three layers of the vessel and surrounding structures (Figure 1). It can assess plaque geometry including plaque burden and size, luminal area, longitudinal extent of the disease, circumferential extent of the

Fig. 1. IVUS of normal coronary artery

Clinical Applications of Intravascular Ultrasound 97

In addition to accurate stent sizing, IVUS can be used to evaluate lesion lumen area to predict the presence or absence of myocardial ischemia and/or significant coronary stenosis. There was strong correlation between lesion lumen area of 4.0 mm2 on IVUS and positive stress myocardial perfusion SPECT in seventy native coronary lesions (Nishioka, Amanullah et al. 1999). In another study, IVUS guided deferral of coronary intervention of 248 lesions with luminal area of 4 mm2 resulted in clinical rates of 4.4% and target lesion revascularisation (TLR) of 2.8% at 12 month follow up. (Abizaid, Mintz

Following coronary intervention, the formation of neointimal hyperplasia is mainly responsible for ISR (Figure 3). There is strong correlation with between late lumen loss and the degree of in-stent neointimal growth (r=0.98) (de Jaegere, Mudra et al. 1998; Hoffmann, Mintz et al. 1998). Although drug eluting stents (DES) has significantly reduced the

One of the main factors for ISR is stent **underexpansion** (Figure 4). IVUS can detect vessel stent subtleties not apparent by coronary angiography. In addition to assessing plaque geometry, IVUS can be used to achieve complete stent apposition and adequate geometric expansion within the stented segment. IVUS studies have demonstrated that incomplete stent and vessel wall apposition, residual stenosis and irregular eccentric lumen in the stented segment was present in almost 88% of the patients despite achieving an optimal angiographic result (Nakamura, Colombo et al. 1994) . Clinical trials have shown that patients who have their coronary intervention guided by IVUS have larger post procedure stent areas and significant reductions in TLR as compared to angiography-guided PCI alone (de Jaegere, Mudra et al. 1998; Schiele, Meneveau et al. 1998; Fitzgerald, Oshima et al. 2000; Sonoda, Morino et al. 2004; Hong, Mintz et al. 2006) In addition to detecting stent

incidence of neointimal proliferation, the rate of ISR still remains around 10-15%.

et al. 1998).

**2.2 Assessment of restenosis** 

Fig. 3. IVUS image of in-stent restenosis

plaque, arterial remodelling and plaque vulnerability. Therefore IVUS provides detailed insight to the anatomy of plaque burden and allows the interventional cardiologist to adapt an optimal strategy for percutaneous coronary intervention (PCI) and subsequently assess the success of this strategy. In this chapter we will describe the potential applications of IVUS for every day use in the catheterization laboratory.

#### **2. Clinical applications of IVUS**

#### **2.1 Assessment of vessel size for stent selection and ischemia evaluation**

Standard coronary angiography is intrinsically limited to evaluate three-dimensional anatomical coronary cross sectional area due to planar silhoutte imaging. In addition, the plaque burden, its delineation and constituents cannot be assessed by coronary angiography. With angiography, the severity of stenosis is assessed by minimal lumen diameter at the lesion site, in comparison with an adjacent normal appearing reference. However, it is well documented that atherosclerosis is diffuse in nature and may appear normal in a small calibre coronary artery with concentric plaque (Figure 2)(Grondin, Dyrda et al. 1974; Roberts and Jones 1979). IVUS provides a complete 360 degrees tomographic view that allows accurate lumen measurements. In fact direct comparison of atherosclerotic disease by angiography and IVUS are frequently discrepant often as a result of eccentric plaque.(Figure 2) IVUS studies have clearly demonstrated that there is no correlation between the size of the atheroma and the size of the lumen(Topol and Nissen 1995) . This difference can be explained by positive (expansive) remodelling where lumen size is maintained due to plaque accumulation within in the vessel wall and resulting vessel wall expansion. It is claimed that these positive plaques are more unstable and vulnerable to rupture than negative (constrictive) plaques and also responsible for in-stent restenosis (ISR) following coronary intervention.(Schoenhagen, Ziada et al. 2000).

Fig. 2. IVUS images of A) concentric plaque and B) eccentric plaque

plaque, arterial remodelling and plaque vulnerability. Therefore IVUS provides detailed insight to the anatomy of plaque burden and allows the interventional cardiologist to adapt an optimal strategy for percutaneous coronary intervention (PCI) and subsequently assess the success of this strategy. In this chapter we will describe the potential applications of

Standard coronary angiography is intrinsically limited to evaluate three-dimensional anatomical coronary cross sectional area due to planar silhoutte imaging. In addition, the plaque burden, its delineation and constituents cannot be assessed by coronary angiography. With angiography, the severity of stenosis is assessed by minimal lumen diameter at the lesion site, in comparison with an adjacent normal appearing reference. However, it is well documented that atherosclerosis is diffuse in nature and may appear normal in a small calibre coronary artery with concentric plaque (Figure 2)(Grondin, Dyrda et al. 1974; Roberts and Jones 1979). IVUS provides a complete 360 degrees tomographic view that allows accurate lumen measurements. In fact direct comparison of atherosclerotic disease by angiography and IVUS are frequently discrepant often as a result of eccentric plaque.(Figure 2) IVUS studies have clearly demonstrated that there is no correlation between the size of the atheroma and the size of the lumen(Topol and Nissen 1995) . This difference can be explained by positive (expansive) remodelling where lumen size is maintained due to plaque accumulation within in the vessel wall and resulting vessel wall expansion. It is claimed that these positive plaques are more unstable and vulnerable to rupture than negative (constrictive) plaques and also responsible for in-stent restenosis (ISR)

Fig. 2. IVUS images of A) concentric plaque and B) eccentric plaque

**2.1 Assessment of vessel size for stent selection and ischemia evaluation** 

IVUS for every day use in the catheterization laboratory.

following coronary intervention.(Schoenhagen, Ziada et al. 2000).

A A B

**2. Clinical applications of IVUS** 

In addition to accurate stent sizing, IVUS can be used to evaluate lesion lumen area to predict the presence or absence of myocardial ischemia and/or significant coronary stenosis. There was strong correlation between lesion lumen area of 4.0 mm2 on IVUS and positive stress myocardial perfusion SPECT in seventy native coronary lesions (Nishioka, Amanullah et al. 1999). In another study, IVUS guided deferral of coronary intervention of 248 lesions with luminal area of 4 mm2 resulted in clinical rates of 4.4% and target lesion revascularisation (TLR) of 2.8% at 12 month follow up. (Abizaid, Mintz et al. 1998).

#### **2.2 Assessment of restenosis**

Following coronary intervention, the formation of neointimal hyperplasia is mainly responsible for ISR (Figure 3). There is strong correlation with between late lumen loss and the degree of in-stent neointimal growth (r=0.98) (de Jaegere, Mudra et al. 1998; Hoffmann, Mintz et al. 1998). Although drug eluting stents (DES) has significantly reduced the incidence of neointimal proliferation, the rate of ISR still remains around 10-15%.

Fig. 3. IVUS image of in-stent restenosis

One of the main factors for ISR is stent **underexpansion** (Figure 4). IVUS can detect vessel stent subtleties not apparent by coronary angiography. In addition to assessing plaque geometry, IVUS can be used to achieve complete stent apposition and adequate geometric expansion within the stented segment. IVUS studies have demonstrated that incomplete stent and vessel wall apposition, residual stenosis and irregular eccentric lumen in the stented segment was present in almost 88% of the patients despite achieving an optimal angiographic result (Nakamura, Colombo et al. 1994) . Clinical trials have shown that patients who have their coronary intervention guided by IVUS have larger post procedure stent areas and significant reductions in TLR as compared to angiography-guided PCI alone (de Jaegere, Mudra et al. 1998; Schiele, Meneveau et al. 1998; Fitzgerald, Oshima et al. 2000; Sonoda, Morino et al. 2004; Hong, Mintz et al. 2006) In addition to detecting stent

Clinical Applications of Intravascular Ultrasound 99

treatment of a lesion which may appear severe angiographically but in fact has minimal plaque burden or failure to treat lesions which are mis-labelled as mild-to-moderate (Mintz

Moreover, IVUS is an ideal method for confirming the presence of significant left main disease and also for guiding selection of stent size, assessing the presence and extent of calcification and especially evaluating the distal left main vessel and its branches. IVUS assessment pre and post left main intervention is very important to evaluate larger lumen area of the ostial and midshaft left main and adequate post dilatation post stenting. In comparison to native coronary vessels, a minimal luminal area of <6.0 mm2 is a commonly used threshold for significant left main disease (Sano, Mintz et al. 2007). While there are no randomized trials to inform practice in this area, registry data has shown a trend toward

CTOs are the most complex lesions that are considered for percutaneous coronary revascularization. PCI of CTO results in symptomatic improvement, improved left ventricle function and reduction in adverse remodelling. In addition recanalization of CTO leads to long-term survival benefit and avoidance of bypass surgery (Melchior, Doriot et al. 1987; Ivanhoe, Weintraub et al. 1992; Chung, Nakamura et al. 2003; Cheng, Selvanayagam et al. 2008). The number of CTO interventions has risen gradually due to better operator experience, technical improvements, and newer procedural techniques (these include contra-lateral coronary injection, "parallel" wire techniques, subintimal tracking and re-entry (STAR), retrograde approach with control antegrade retrograde tracking (CART), reverse CART). Despite these advances, the success rate of CTO interventions remains low (<60%)(Di Mario, Werner et al. 2007), largely due to difficulty crossing the occlusion with the guidewire and entering the true distal lumen beyond the occlusion (Safian, McCabe et al. 1988; Kinoshita, Katoh et al. 1995). In most instances of failed CTO intervention, the guidewire enters the false lumen (subintimal space) at the site of occlusion, often making it impossible to re-enter the true lumen (Figure 5). CTO interventions can be performed via an antegrade approach or

reduced mortality in IVUS guided UPLM PCI.(Park, Kim et al. 2009)

retrograde approach using septal collaterals (Surmely, Tsuchikane et al. 2006).

CTO intervention is limited only to experienced operators.

IVUS studies provide insights into the anatomy of the CTO lesion. In one report IVUS demonstrated presence of calcium mostly across the side branch take-off, especially in abrupt-origin CTOs (Fujii, Mintz et al. 2006). This anatomical variance can explain the preferential entry of the guidewire into the side branch at the point of occlusion. The use of IVUS for CTO interventions can be extremely useful especially in ensuring that the guidewire is positioned within the coronary lumen (true or false), and also helps to identify the optimal entry point within the CTO cap(Ochiai, Ogata et al. 2006). IVUS can help to avoid subintimal stenting during CTO intervention as this has been reported to result in stent thrombosis and stent mal-apposition due to the formation of multiple aneurysms (Erlich, Strauss et al. 2006; Tsujita, Maehara et al. 2009). IVUS imaging for CTO can also detect vessel wall haematoma, dissection and small perforations that are not detected by routine coronary angiography. Further advances in IVUS technology especially the development of 'forward facing IVUS' will significantly improve our anatomical understanding of the chronically occluded lumen. Although IVUS guided intervention of chronic occlusions may enhance procedural outcome, the current use of this technology for

**2.4 Guidance for Chronic Total Occlusion (CTO) intervention** 

and Maehara 2009).

underexpansion, IVUS can also assist in achieving optimal stent expansion, exclude stent edge dissections and plaque protrusion (Hong, Jeong et al. 2008).

Fig. 4. IVUS demonstrating A) stent well apposed to vessel wall and B) stent mal-apposition

#### **2.3 Guidance for left main stem intervention**

Coronary interventions of unprotected left main coronary artery (UPLM) with bare metal stents in the 1990s were associated with high rates of revascularization (25% to 30%) due to restenosis (Black, Cortina et al. 2001; Park, Hong et al. 2001; Takagi, Stankovic et al. 2002). Although the use of DES for UPLM PCI have significantly reduced the rate of revascularization as compared with bare metal stents (BMS), the long term outcomes remain less favourable. Most of the poor outcomes following UPLM PCI relates to distal bifurcation intervention, which is a technically complex procedure. The current American College of Cardiology (ACC)/American Heart association (AHA) practice guidelines for PCI categorize UPLM stenting as a class IIb indication or IIa indication in selected patients without co-existing multivessel disease. At present there is a paucity of randomized control trial data comparing Coronary artery bypass grafting (CABG) to PCI in patients with UPLM. The best available evidence comes from the SYNTAX trial (SYNergy between Percutaneous Coronary Intervention with TAXus and Cardiac Surgery), which randomly assigned 1800 patients with either UPLM (n=705) or multivessel CAD not involving the left main stem (n=1095) (Ong, Serruys et al. 2006) . The major adverse cardiac or cerebrovascular events were not significantly different between the CABG and PCI groups (13.7 vs 15.8%). However, the rate of revascularization was significantly higher in those treated with PCI (11.8 vs 6.5 %). One of the main limitations of the SYNTAX trial was felt to be the lack of use of IVUS for UPLM in the PCI group.

While the European Society of Cardiology guidelines give IVUS-guided stenting of the UPLM a Class IIb recommendation we feel IVUS interrogation of the UPLM pre and post intervention should be used in all cases. Not least because IVUS interrogation has been demonstrated to, frequently prove angiographic assessment of the UPLM as inaccurate. This obviously may have significant impact on patient management resulting in either erroneous

underexpansion, IVUS can also assist in achieving optimal stent expansion, exclude stent

Fig. 4. IVUS demonstrating A) stent well apposed to vessel wall and B) stent mal-apposition

Coronary interventions of unprotected left main coronary artery (UPLM) with bare metal stents in the 1990s were associated with high rates of revascularization (25% to 30%) due to restenosis (Black, Cortina et al. 2001; Park, Hong et al. 2001; Takagi, Stankovic et al. 2002). Although the use of DES for UPLM PCI have significantly reduced the rate of revascularization as compared with bare metal stents (BMS), the long term outcomes remain less favourable. Most of the poor outcomes following UPLM PCI relates to distal bifurcation intervention, which is a technically complex procedure. The current American College of Cardiology (ACC)/American Heart association (AHA) practice guidelines for PCI categorize UPLM stenting as a class IIb indication or IIa indication in selected patients without co-existing multivessel disease. At present there is a paucity of randomized control trial data comparing Coronary artery bypass grafting (CABG) to PCI in patients with UPLM. The best available evidence comes from the SYNTAX trial (SYNergy between Percutaneous Coronary Intervention with TAXus and Cardiac Surgery), which randomly assigned 1800 patients with either UPLM (n=705) or multivessel CAD not involving the left main stem (n=1095) (Ong, Serruys et al. 2006) . The major adverse cardiac or cerebrovascular events were not significantly different between the CABG and PCI groups (13.7 vs 15.8%). However, the rate of revascularization was significantly higher in those treated with PCI (11.8 vs 6.5 %). One of the main limitations of the SYNTAX trial was felt to be the lack of use

While the European Society of Cardiology guidelines give IVUS-guided stenting of the UPLM a Class IIb recommendation we feel IVUS interrogation of the UPLM pre and post intervention should be used in all cases. Not least because IVUS interrogation has been demonstrated to, frequently prove angiographic assessment of the UPLM as inaccurate. This obviously may have significant impact on patient management resulting in either erroneous

edge dissections and plaque protrusion (Hong, Jeong et al. 2008).

A B

**2.3 Guidance for left main stem intervention** 

of IVUS for UPLM in the PCI group.

treatment of a lesion which may appear severe angiographically but in fact has minimal plaque burden or failure to treat lesions which are mis-labelled as mild-to-moderate (Mintz and Maehara 2009).

Moreover, IVUS is an ideal method for confirming the presence of significant left main disease and also for guiding selection of stent size, assessing the presence and extent of calcification and especially evaluating the distal left main vessel and its branches. IVUS assessment pre and post left main intervention is very important to evaluate larger lumen area of the ostial and midshaft left main and adequate post dilatation post stenting. In comparison to native coronary vessels, a minimal luminal area of <6.0 mm2 is a commonly used threshold for significant left main disease (Sano, Mintz et al. 2007). While there are no randomized trials to inform practice in this area, registry data has shown a trend toward reduced mortality in IVUS guided UPLM PCI.(Park, Kim et al. 2009)

#### **2.4 Guidance for Chronic Total Occlusion (CTO) intervention**

CTOs are the most complex lesions that are considered for percutaneous coronary revascularization. PCI of CTO results in symptomatic improvement, improved left ventricle function and reduction in adverse remodelling. In addition recanalization of CTO leads to long-term survival benefit and avoidance of bypass surgery (Melchior, Doriot et al. 1987; Ivanhoe, Weintraub et al. 1992; Chung, Nakamura et al. 2003; Cheng, Selvanayagam et al. 2008). The number of CTO interventions has risen gradually due to better operator experience, technical improvements, and newer procedural techniques (these include contra-lateral coronary injection, "parallel" wire techniques, subintimal tracking and re-entry (STAR), retrograde approach with control antegrade retrograde tracking (CART), reverse CART). Despite these advances, the success rate of CTO interventions remains low (<60%)(Di Mario, Werner et al. 2007), largely due to difficulty crossing the occlusion with the guidewire and entering the true distal lumen beyond the occlusion (Safian, McCabe et al. 1988; Kinoshita, Katoh et al. 1995). In most instances of failed CTO intervention, the guidewire enters the false lumen (subintimal space) at the site of occlusion, often making it impossible to re-enter the true lumen (Figure 5). CTO interventions can be performed via an antegrade approach or retrograde approach using septal collaterals (Surmely, Tsuchikane et al. 2006).

IVUS studies provide insights into the anatomy of the CTO lesion. In one report IVUS demonstrated presence of calcium mostly across the side branch take-off, especially in abrupt-origin CTOs (Fujii, Mintz et al. 2006). This anatomical variance can explain the preferential entry of the guidewire into the side branch at the point of occlusion. The use of IVUS for CTO interventions can be extremely useful especially in ensuring that the guidewire is positioned within the coronary lumen (true or false), and also helps to identify the optimal entry point within the CTO cap(Ochiai, Ogata et al. 2006). IVUS can help to avoid subintimal stenting during CTO intervention as this has been reported to result in stent thrombosis and stent mal-apposition due to the formation of multiple aneurysms (Erlich, Strauss et al. 2006; Tsujita, Maehara et al. 2009). IVUS imaging for CTO can also detect vessel wall haematoma, dissection and small perforations that are not detected by routine coronary angiography. Further advances in IVUS technology especially the development of 'forward facing IVUS' will significantly improve our anatomical understanding of the chronically occluded lumen. Although IVUS guided intervention of chronic occlusions may enhance procedural outcome, the current use of this technology for CTO intervention is limited only to experienced operators.

Clinical Applications of Intravascular Ultrasound 101

Ultrasound provides some information about the morphological features of atherosclerotic plaque. The American College of Cardiology Clinical Expert Consensus Document for IVUS imaging has described that a vulnerable plaque can appear as an 'echolucent' plaque (Mintz, Nissen et al. 2001). Frequently these echolucent plaques have a prominent echogenic border at the lumen-intima interface. This may correspond to the TCFA. However, it should be emphasized that the fibrous cap of TCFA is <65 m and therefore could not be detected using this modality. Imaging IVUS provides limited insight into the chemical composition of the plaque and is dependent on simple interpretation of acoustic reflections. Lipid-laden echolucent plaques can be detected with a sensitivity of between 78% and 95% and specificity of 30% (Mallery, Tobis et al. 1990; Potkin, Bartorelli et al. 1990). Furthermore, reduced echogenicity may also be observed in large necrotic zones, intramural hemorrhage

Echodense plaques have an intermediate echogenicity between echolucent and highly echogenic calcified plaques. The echodensity of plaques correlate well with plaque fibrosis in histological studies. The identification of echolucent plaques is subjective and no prospective clinical trials are available. In an IVUS based study, echolucent plaque was identified in 31 patients from a total of 144 patients. Of these 31 patients, 23 patients (74%) presented with unstable angina. Plaque rupture was confirmed by injecting contrast with subsequent filling of the plaque cavity on IVUS (Ge, Haude et al. 1995). In another study, IVUS images of 114 coronary lesions with <50% stenosis were recorded and followed up for two years.(Yamagishi, Terashima et al. 2000). The patients who developed Acute coronary syndrome during the follow up were identified and events correlated with large echolucent zones in the eccentric plaques at the time of their first IVUS study. These plaques had histological features similar to vulnerable plaques and were associated with increased risk of instability. In addition, IVUS can also identify vulnerable plaques at high risk of rupture

IVUS has excellent blood penetration and in the absence of calcium is able to visualize and calculate plaque area, volume and eccentricity. The use of IVUS to identify TCFA and lipid pool is at present limited. It suffers from signal attenuation and geometric effects that result in different backscatter signal properties from similar tissues due to differences in tissue

in vessels with adaptive remodelling (von Birgelen, Klinkhart et al. 2001).

Fig. 6. IVUS image of atherosclerotic plaque

or a thrombus.

Fig. 5. IVUS image of false lumen

#### **2.5 Guidance for bifurcation lesion intervention**

PCI of bifurcation lesions have been associated with lower procedural success rate and worse clinical outcome than when used to treated non-bifurcation lesions. This is largely related to the complexity of the bifurcation lesions, significant anatomical variation of the bifurcation lesion, and lack of standard guidelines for the treatment of bifurcation lesions. The current therapeutic strategies for bifurcation lesions have mainly stemmed from personal clinical experience of the operators. (Suzuki, Angiolillo et al. 2007). In recent years there has been better understanding of bifurcation lesions especially with use of DES, acceptance of provisional stenting (acceptance of a suboptimal result in a small side branch SB), specific treatment of bifurcation lesions with a two-stent strategy and increasing use of final kissing balloon. The use of IVUS for bifurcation lesions can provide valuable information especially in anatomical evaluation of plaque burden, plaque location, angle assessment, lumen size of main branch [MB] and [SB]. In addition post PCI, IVUS can assist in evaluation of plaque shift, change in carina angle, dissection, and above all optimal stent deployment (Costa, Mintz et al. 2005). We feel that IVUS guided optimization of the bifurcation lesion post intervention, especially the ostium of a large side branch will enhance long term outcome of these technically challenging subset of lesions.

#### **2.6 Vulnerable plaque assessment**

The composition of atherosclerotic plaque is heterogeneous by nature and contains 1) fibrocellular components (extracellular matrix and smooth muscle cells), 2) lipid-cellular components (crystalline cholesterol and cholesterol esters mixed with macrophages), 3) thrombotic components (platelets and fibrin) and 4) calcium (Figure 6) (Fuster, Badimon et al. 1992; Fuster, Badimon et al. 1992; Stary 2000; Virmani, Kolodgie et al. 2000). Vulnerable plaques that result in rupture have been now well described as thin cap fibroatheroma (TCFA).

PCI of bifurcation lesions have been associated with lower procedural success rate and worse clinical outcome than when used to treated non-bifurcation lesions. This is largely related to the complexity of the bifurcation lesions, significant anatomical variation of the bifurcation lesion, and lack of standard guidelines for the treatment of bifurcation lesions. The current therapeutic strategies for bifurcation lesions have mainly stemmed from personal clinical experience of the operators. (Suzuki, Angiolillo et al. 2007). In recent years there has been better understanding of bifurcation lesions especially with use of DES, acceptance of provisional stenting (acceptance of a suboptimal result in a small side branch SB), specific treatment of bifurcation lesions with a two-stent strategy and increasing use of final kissing balloon. The use of IVUS for bifurcation lesions can provide valuable information especially in anatomical evaluation of plaque burden, plaque location, angle assessment, lumen size of main branch [MB] and [SB]. In addition post PCI, IVUS can assist in evaluation of plaque shift, change in carina angle, dissection, and above all optimal stent deployment (Costa, Mintz et al. 2005). We feel that IVUS guided optimization of the bifurcation lesion post intervention, especially the ostium of a large side branch will

enhance long term outcome of these technically challenging subset of lesions.

The composition of atherosclerotic plaque is heterogeneous by nature and contains 1) fibrocellular components (extracellular matrix and smooth muscle cells), 2) lipid-cellular components (crystalline cholesterol and cholesterol esters mixed with macrophages), 3) thrombotic components (platelets and fibrin) and 4) calcium (Figure 6) (Fuster, Badimon et al. 1992; Fuster, Badimon et al. 1992; Stary 2000; Virmani, Kolodgie et al. 2000). Vulnerable plaques that result in rupture have been now well described as thin cap fibroatheroma

Fig. 5. IVUS image of false lumen

**2.6 Vulnerable plaque assessment** 

(TCFA).

**2.5 Guidance for bifurcation lesion intervention** 

Fig. 6. IVUS image of atherosclerotic plaque

Ultrasound provides some information about the morphological features of atherosclerotic plaque. The American College of Cardiology Clinical Expert Consensus Document for IVUS imaging has described that a vulnerable plaque can appear as an 'echolucent' plaque (Mintz, Nissen et al. 2001). Frequently these echolucent plaques have a prominent echogenic border at the lumen-intima interface. This may correspond to the TCFA. However, it should be emphasized that the fibrous cap of TCFA is <65 m and therefore could not be detected using this modality. Imaging IVUS provides limited insight into the chemical composition of the plaque and is dependent on simple interpretation of acoustic reflections. Lipid-laden echolucent plaques can be detected with a sensitivity of between 78% and 95% and specificity of 30% (Mallery, Tobis et al. 1990; Potkin, Bartorelli et al. 1990). Furthermore, reduced echogenicity may also be observed in large necrotic zones, intramural hemorrhage or a thrombus.

Echodense plaques have an intermediate echogenicity between echolucent and highly echogenic calcified plaques. The echodensity of plaques correlate well with plaque fibrosis in histological studies. The identification of echolucent plaques is subjective and no prospective clinical trials are available. In an IVUS based study, echolucent plaque was identified in 31 patients from a total of 144 patients. Of these 31 patients, 23 patients (74%) presented with unstable angina. Plaque rupture was confirmed by injecting contrast with subsequent filling of the plaque cavity on IVUS (Ge, Haude et al. 1995). In another study, IVUS images of 114 coronary lesions with <50% stenosis were recorded and followed up for two years.(Yamagishi, Terashima et al. 2000). The patients who developed Acute coronary syndrome during the follow up were identified and events correlated with large echolucent zones in the eccentric plaques at the time of their first IVUS study. These plaques had histological features similar to vulnerable plaques and were associated with increased risk of instability. In addition, IVUS can also identify vulnerable plaques at high risk of rupture in vessels with adaptive remodelling (von Birgelen, Klinkhart et al. 2001).

IVUS has excellent blood penetration and in the absence of calcium is able to visualize and calculate plaque area, volume and eccentricity. The use of IVUS to identify TCFA and lipid pool is at present limited. It suffers from signal attenuation and geometric effects that result in different backscatter signal properties from similar tissues due to differences in tissue

Clinical Applications of Intravascular Ultrasound 103

coronary intervention. IVUS is a validated clinical tool that allows precise evaluation of angiographically stenotic lesions helping guide the cardiologist's approach to revascualisation and assess complications and sub-optimal results post-procedure. In addition it provides important information regarding non-critical but vulnerable plaque which is not appreciable by traditional coronary angiography. In an era of more complex and ambitious coronary intervention IVUS is a vitally important addition to the interventionalist's armamentarium. In this chapter we have briefly described the various

Abizaid, A., G. S. Mintz, et al. (1998). "Clinical, intravascular ultrasound, and quantitative

percutaneous transluminal coronary angioplasty." *Am J Cardiol* 82(4): 423-8. Black, A., R. Cortina, et al. (2001). "Unprotected left main coronary artery stenting: correlates

Cheng, A. S., J. B. Selvanayagam, et al. (2008). "Percutaneous treatment of chronic total

Chung, C. M., S. Nakamura, et al. (2003). "Effect of recanalization of chronic total occlusions

Di Mario, C., G. S. Werner, et al. (2007). "European perspective in the recanalisation of

Erlich, I., B. H. Strauss, et al. (2006). "Stent thrombosis following the STAR technique in a complex RCA chronic total occlusion." *Catheter Cardiovasc Interv* 68(5): 708-12. Fitzgerald, P. J., A. Oshima, et al. (2000). "Final results of the Can Routine Ultrasound Influence Stent Expansion (CRUISE) study." *Circulation* 102(5): 523-30. Fujii, K., G. S. Mintz, et al. (2006). "Intravascular ultrasound profile analysis of ruptured

Fuster, V., L. Badimon, et al. (1992). "The pathogenesis of coronary artery disease and the

Fuster, V., L. Badimon, et al. (1992). "The pathogenesis of coronary artery disease and the

Ge, J., M. Haude, et al. (1995). "Silent healing of spontaneous plaque disruption demonstrated by intracoronary ultrasound." *Eur Heart J* 16(8): 1149-51. Grondin, C. M., I. Dyrda, et al. (1974). "Discrepancies between cineangiographic and

postmortem findings in patients with coronary artery disease and recent

previous myocardial infarction." *Catheter Cardiovasc Interv* 60(3): 368-74. Costa, R. A., G. S. Mintz, et al. (2005). "Bifurcation coronary lesions treated with the "crush" technique: an intravascular ultrasound analysis." *J Am Coll Cardiol* 46(4): 599-605. de Jaegere, P., H. Mudra, et al. (1998). "Intravascular ultrasound-guided optimized stent

angiographic determinants of the coronary flow reserve before and after

of midterm survival and impact of patient selection." *J Am Coll Cardiol* 37(3): 832-8.

coronary occlusions improves regional hyperemic myocardial blood flow and contractility: insights from quantitative cardiovascular magnetic resonance

on global and regional left ventricular function in patients with or without

deployment. Immediate and 6 months clinical and angiographic results from the Multicenter Ultrasound Stenting in Coronaries Study (MUSIC Study)." *Eur Heart J*

Chronic Total Occlusions (CTO): consensus document from the EuroCTO Club."

potential uses of IVUS and their clinical application.

imaging." *JACC Cardiovasc Interv* 1(1): 44-53.

coronary plaques." *Am J Cardiol* 98(4): 429-35.

acute coronary syndromes (1)." *N Engl J Med* 326(4): 242-50.

acute coronary syndromes (2)." *N Engl J Med* 326(5): 310-8.

myocardial revascularization." *Circulation* 49(4): 703-8.

**4. References** 

19(8): 1214-23.

*EuroIntervention* 3(1): 30-43.

orientation and position relative to the imaging transducer. Ultra- high frequency catheters can be employed to achieve high resolution and visualize subluminal fibrous cap, while low-resolution components can be used for better penetration of the plaque to assess plaque components.

The conventional IVUS image undergoes considerable processing such as envelope detection, time-gain compensation, and logarithmic compression to create real time imaging. However, this processing significantly reduces the ability to characterize the imaged tissue, the echogenicity of the imaged tissue is difficult to repeat and interpret quantitatively. The reflected unprocessed ultrasound signal in the form of A-scan or individual backscattered signals (256 A scans for an image) is called the radiofrequency data and it is the analysis of these individual A-scans that holds potential for tissue characterization. This imaging modality is known as IVUS virtual histology (IVUS –VH) or IVUS radiofrequency (IVUS-RF).

*Ex-vivo* studies have demonstrated that raw backscattered ultrasound signal allows a more detailed analysis of the vessel components with scope to identify different tissue morphology (Moore, Spencer et al. 1998). IVUS-VH uses spectral analysis of radiofrequency data to construct tissue maps that classify plaque into four major components (fibrous [labeled green], fibrolipidic [labeled greenish-yellow], necrotic core [labeled red] and calcium [labeled white]) which were correlated with a specific spectrum of the radiofrequency signal and assigned color codes (Nair, Kuban et al. 2001). In a clinical study, IVUS-VH was used to investigate the presence of IVUS-derived thin cap fibroatheroma (IDTCFA) in non-culprit, non-obstructive (<50%) lesions in 55 patients who presented with acute coronary syndrome (Rodriguez-Granillo, Garcia-Garcia et al. 2005). The axial resolution of the IVUS-VH is between 100 to 150 m and therefore in this study the authors assumed that the absence of visible atheroma tissue overlying a necrotic core would suggest a cap thickness of below 100 to 150 m and used the absence of such tissue to define a thin fibrous cap. In this study, IDTCFA was defined and identified as a lesion with a necrotic core ≥10% without evident overlying fibrous tissue and percent atheroma volume (PAV) ≥40%. In this study significantly higher prevalence of IDTCFA was observed in patients with Acute coronary syndrome in comparison with controls [(3.0 IQR 0.0 to 5.0 vs. 1.0 IQR 1.0 to 2.8) p=0.018]. The large multicenter PROSPECT trial (700 patients with Acute coronary syndrome) looked at long-term outcomes of non-culprit lesions (based on IVUS-VH) at the time of Percutaneous coronary intervention of the culprit lesions. The investigators reported that only 11 percent of the patients had high event rate (i.e. 17%) in association with thincapped fibroatheromas with minimal luminal area (MLA) 4 mm2 and plaque burden 70%. Although high-risk focal sites can be detected with IVUS-VH, the predictive power (significantly higher numbers of vulnerable plaques than clinical events) of vulnerable plaque to cause a clinical event remains low.

IVUS-RF data acquisition and real time processing with three dimensional imaging and spectral analysis is a potential tool to assess vulnerable plaque *in vivo*. This imaging tool provides detailed volumetric assessment of the histological components of the plaque *in vivo* and therefore may represent a unique technique to identify the vulnerable plaque in future.

#### **3. Conclusion**

Over the past decade there has been a significant technological advance in cardiovascular imaging that has changed the way we assess coronary atherosclerosis and approach coronary intervention. IVUS is a validated clinical tool that allows precise evaluation of angiographically stenotic lesions helping guide the cardiologist's approach to revascualisation and assess complications and sub-optimal results post-procedure. In addition it provides important information regarding non-critical but vulnerable plaque which is not appreciable by traditional coronary angiography. In an era of more complex and ambitious coronary intervention IVUS is a vitally important addition to the interventionalist's armamentarium. In this chapter we have briefly described the various potential uses of IVUS and their clinical application.

#### **4. References**

102 Intravascular Ultrasound

orientation and position relative to the imaging transducer. Ultra- high frequency catheters can be employed to achieve high resolution and visualize subluminal fibrous cap, while low-resolution components can be used for better penetration of the plaque to assess plaque

The conventional IVUS image undergoes considerable processing such as envelope detection, time-gain compensation, and logarithmic compression to create real time imaging. However, this processing significantly reduces the ability to characterize the imaged tissue, the echogenicity of the imaged tissue is difficult to repeat and interpret quantitatively. The reflected unprocessed ultrasound signal in the form of A-scan or individual backscattered signals (256 A scans for an image) is called the radiofrequency data and it is the analysis of these individual A-scans that holds potential for tissue characterization. This imaging modality is known as IVUS virtual histology (IVUS –VH) or

*Ex-vivo* studies have demonstrated that raw backscattered ultrasound signal allows a more detailed analysis of the vessel components with scope to identify different tissue morphology (Moore, Spencer et al. 1998). IVUS-VH uses spectral analysis of radiofrequency data to construct tissue maps that classify plaque into four major components (fibrous [labeled green], fibrolipidic [labeled greenish-yellow], necrotic core [labeled red] and calcium [labeled white]) which were correlated with a specific spectrum of the radiofrequency signal and assigned color codes (Nair, Kuban et al. 2001). In a clinical study, IVUS-VH was used to investigate the presence of IVUS-derived thin cap fibroatheroma (IDTCFA) in non-culprit, non-obstructive (<50%) lesions in 55 patients who presented with acute coronary syndrome (Rodriguez-Granillo, Garcia-Garcia et al. 2005). The axial resolution of the IVUS-VH is between 100 to 150 m and therefore in this study the authors assumed that the absence of visible atheroma tissue overlying a necrotic core would suggest a cap thickness of below 100 to 150 m and used the absence of such tissue to define a thin fibrous cap. In this study, IDTCFA was defined and identified as a lesion with a necrotic core ≥10% without evident overlying fibrous tissue and percent atheroma volume (PAV) ≥40%. In this study significantly higher prevalence of IDTCFA was observed in patients with Acute coronary syndrome in comparison with controls [(3.0 IQR 0.0 to 5.0 vs. 1.0 IQR 1.0 to 2.8) p=0.018]. The large multicenter PROSPECT trial (700 patients with Acute coronary syndrome) looked at long-term outcomes of non-culprit lesions (based on IVUS-VH) at the time of Percutaneous coronary intervention of the culprit lesions. The investigators reported that only 11 percent of the patients had high event rate (i.e. 17%) in association with thincapped fibroatheromas with minimal luminal area (MLA) 4 mm2 and plaque burden 70%. Although high-risk focal sites can be detected with IVUS-VH, the predictive power (significantly higher numbers of vulnerable plaques than clinical events) of vulnerable

IVUS-RF data acquisition and real time processing with three dimensional imaging and spectral analysis is a potential tool to assess vulnerable plaque *in vivo*. This imaging tool provides detailed volumetric assessment of the histological components of the plaque *in vivo* and therefore may represent a unique technique to identify the vulnerable plaque in future.

Over the past decade there has been a significant technological advance in cardiovascular imaging that has changed the way we assess coronary atherosclerosis and approach

components.

IVUS radiofrequency (IVUS-RF).

plaque to cause a clinical event remains low.

**3. Conclusion** 


Clinical Applications of Intravascular Ultrasound 105

Park, S. J., M. K. Hong, et al. (2001). "Elective stenting of unprotected left main coronary

Park, S. J., Y. H. Kim, et al. (2009). "Impact of intravascular ultrasound guidance on long-

Potkin, B. N., A. L. Bartorelli, et al. (1990). "Coronary artery imaging with intravascular

Roberts, W. C. and A. A. Jones (1979). "Quantitation of coronary arterial narrowing at

Rodriguez-Granillo, G. A., H. M. Garcia-Garcia, et al. (2005). "In vivo intravascular

Safian, R. D., C. H. McCabe, et al. (1988). "Initial success and long-term follow-up of

Sano, K., G. S. Mintz, et al. (2007). "Assessing intermediate left main coronary lesions using

Schiele, F., N. Meneveau, et al. (1998). "Impact of intravascular ultrasound guidance in stent

Schoenhagen, P., K. M. Ziada, et al. (2000). "Extent and direction of arterial remodeling in

Sonoda, S., Y. Morino, et al. (2004). "Impact of final stent dimensions on long-term results

Stary, H. C. (2000). "Natural history and histological classification of atherosclerotic lesions:

Surmely, J. F., E. Tsuchikane, et al. (2006). "New concept for CTO recanalization using

Suzuki, N., D. J. Angiolillo, et al. (2007). "Percutaneous coronary intervention of bifurcation

Takagi, T., G. Stankovic, et al. (2002). "Results and long-term predictors of adverse clinical

Topol, E. J. and S. E. Nissen (1995). "Our preoccupation with coronary luminology. The

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*Cardiovasc Interv* 2(3): 167-77.

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intervention with TAXus and cardiac surgery (SYNTAX) study: design, rationale,


**8** 

**IVUS Guided PCI** 

T. Kovarnik and J. Horak

*Czech Republic* 

*General University Hospital in Prague,* 

*2nd Department of Medicine - Department of Cardiovascular Medicine,* 

Intravascular ultrasound is a clinical tool that has been used in a complimentary manner to contrast angiography in order to enhance the procedure success rate and patient outcomes. Particularly, there are some specific situations where IVUS can be very useful and information from IVUS overcome angiography limitations. These situations can be divided into three parts:

Pre-interventional use of IVUS can help with assessment of hemodynamic significance of stenosis (in this place must be emphasized, that IVUS can estimate hemodynamic significance only non directly, but with acceptable correlation with fractional flow reserve and nuclear stress test), precise anatomic analysis (type of bifurcation, plaque burden in ostial part of side branch or left main) and can help with device selection: precise measurement of diameters in reference segments for better sizing of balloon or stent, type of lesion preparation such as dilatation with cutting balloon or atherectomy devices in bulky lesions, drug eluting stent for

IVUS can be used during intervention for assessment of lesion preparation (proper position of wire; especially it's relation to stent struts, effect of predilatation, assessment of side branch ostium) for guiding in more complicated intervention (left main stenting, navigation

Post-interventional use of IVUS can answer questions about result adequacy (stent expansion, stent apposition), angiographic filling defects ("hazy lesions") after PCI (edge dissection, thrombus formation, inadequate stent expansion, prominent calcification) and diagnosis of complications (dissection, geographic mismatch, plaque protrusion inside the stent, inadequate stent expansion or apposition). IVUS can in most cases also reveal the reasons behind development of complications after PCI such is in stent thrombosis (mainly inadequate stent expansion or edge troubles such as dissection, or uncovered lesion) or

IVUS is a mandatory tool in the cardiac catheterization laboratory today. Like all medical equipments it should be used by an experienced investigator for better understanding of PCI mechanisms, prevention and solution of complications. Nowadays it is possible to use many semi-automatic softwares for border detection, but all of them must be corrected

lesions with high probability of small in stent area achievement.

of wires during PCI of chronic total occlusion, trifurcation PCI).

unexpected early in stent restenosis (inadequate stent expansion).

**1. Introduction** 


*First Faculty of Medicine, Charles University in Prague and* 

stent fractures, and a newly formed stent gap between previously overlapped stents." *JACC Cardiovasc Interv* 2(2): 156-8.


## **IVUS Guided PCI**

#### T. Kovarnik and J. Horak

*2nd Department of Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Czech Republic* 

#### **1. Introduction**

106 Intravascular Ultrasound

Virmani, R., F. D. Kolodgie, et al. (2000). "Lessons from sudden coronary death: a

Von Birgelen, C., W. Klinkhart, et al. (2001). "Plaque distribution and vascular remodeling of

Yamagishi, M., M. Terashima, et al. (2000). "Morphology of vulnerable coronary plaque:

Wu, X., Maehara A, et al. (2010). "Virtual histology intravascular ultrasound analysis of non-

patients with acute coronary syndromes." *J Am Coll Cardiol* 105(1):48-53. Gregg W. Stone., Akiko Maehara, et al. (2011). " A Prospective Natural-History Study of

stents." *JACC Cardiovasc Interv* 2(2): 156-8.

*Arterioscler Thromb Vasc Biol* 20(5): 1262-75.

ultrasound study in vivo." *J Am Coll Cardiol* 37(7): 1864-70.

acute coronary syndrome." *J Am Coll Cardiol* 35(1): 106-11.

Coronary Atherosclerosis". *N Engl J Med* 364:226-35.

stent fractures, and a newly formed stent gap between previously overlapped

comprehensive morphological classification scheme for atherosclerotic lesions."

ruptured and nonruptured coronary plaques in the same vessel: an intravascular

insights from follow-up of patients examined by intravascular ultrasound before an

culprit attenuated plaques detected by grayscale intravascular ultrasound in

Intravascular ultrasound is a clinical tool that has been used in a complimentary manner to contrast angiography in order to enhance the procedure success rate and patient outcomes. Particularly, there are some specific situations where IVUS can be very useful and information from IVUS overcome angiography limitations. These situations can be divided into three parts:


Pre-interventional use of IVUS can help with assessment of hemodynamic significance of stenosis (in this place must be emphasized, that IVUS can estimate hemodynamic significance only non directly, but with acceptable correlation with fractional flow reserve and nuclear stress test), precise anatomic analysis (type of bifurcation, plaque burden in ostial part of side branch or left main) and can help with device selection: precise measurement of diameters in reference segments for better sizing of balloon or stent, type of lesion preparation such as dilatation with cutting balloon or atherectomy devices in bulky lesions, drug eluting stent for lesions with high probability of small in stent area achievement.

IVUS can be used during intervention for assessment of lesion preparation (proper position of wire; especially it's relation to stent struts, effect of predilatation, assessment of side branch ostium) for guiding in more complicated intervention (left main stenting, navigation of wires during PCI of chronic total occlusion, trifurcation PCI).

Post-interventional use of IVUS can answer questions about result adequacy (stent expansion, stent apposition), angiographic filling defects ("hazy lesions") after PCI (edge dissection, thrombus formation, inadequate stent expansion, prominent calcification) and diagnosis of complications (dissection, geographic mismatch, plaque protrusion inside the stent, inadequate stent expansion or apposition). IVUS can in most cases also reveal the reasons behind development of complications after PCI such is in stent thrombosis (mainly inadequate stent expansion or edge troubles such as dissection, or uncovered lesion) or unexpected early in stent restenosis (inadequate stent expansion).

IVUS is a mandatory tool in the cardiac catheterization laboratory today. Like all medical equipments it should be used by an experienced investigator for better understanding of PCI mechanisms, prevention and solution of complications. Nowadays it is possible to use many semi-automatic softwares for border detection, but all of them must be corrected

IVUS Guided PCI 109

IVUS vs. FFR

IVUS vs. CFR

IVUS vs. myocardial SPECT

IVUS vs. FFR

IVUS vs. FFR

IVUS vs. FFR

FFR

IVUS vs. FFR

IVUS vs. SPECT

IVUS and MACE

Table 1. Studies with IVUS evaluation of hemodynamic significance

Abbreviations: CFR - coronary flow reserve, MACE – major cardiac adverse event, MLA – minimal lumen area, MLD – minimal lumen diameter, PB - plaque burden, PCI- percutaneous coronary interventions, QCA – quantitative coronary angiography, SPECT – single photon emission computed

Abizaid11 IVUS deferred PCI IVUS 300 *Safe deferral of PCI correlates with:* 

**patients**

73 *CFR* 

**Results** 

43 *FFR < 0.75 correlates with:* - MLA ≤ 4 mm2 - MLD ≤ 1.8 mm - PB > 70%

> - MLA ≥ 4 mm2 - MLD ≥ 2 mm

79 *Positive scan correlates with:*  - MLA ≤ 4 mm2 - PB > 73% - LAS >59%

42 *FFR <0.75 correlates with:* - MLA ≤ 3 mm2 - LAS > 60%

94 *FFR < 0.75 correlates with:* - MLA ≤ 2.0 mm2 - PB ≥ 80%

> - MLA ≥ 4 mm2 - MLD ≥ 2 mm

55 *FFR < 0.75 correlates with:* - MLA ≤ 5.9 mm2 - MLD ≤ 2.8 mm


201 *FFR <0.80 correlates with:* - MLA 2.4 mm2 - PB ≥79%

84 *FFR < 0.8 correlates with:* 

2.5-3.0 mm

150 *Positive scan correlates with*: - MLA 2.1 mm2

700 *Predictors for MACE:* - PB > 70% - MLA < 4 mm2 - TCFA



IVUS 122 *MACE predictor :*


≥


 *2 correlates with:* 

**Author Description Methods No of** 

Briguori6 angiographic stenosis 40-70%

Abizaid7 patients indicated for PCI

examinations

examinations

Nishioka8 consecutive IVUS

Takagi9 consecutive IVUS

Lee10 vessels smaller than 3 mm

Jasti12 ambiguous left main stenosis

stenosis

borderline left main

Kang 14 Consecutive patients IVUS vs.

intermediate lesion during QCA

with SPECT and

Abizaid13 patients with

Ben Dor15 patients with

Ahn16 consecutive patients

IVUS

tomography, TCFA thin cap fibroatheroma

PROSPECT17 clinical follow-up after ACS

manually to avoid serious mistakes and misunderstanding. The best way how to do that is just routine use of IVUS.

#### **1.1 Limitation of angiography**

Angiography is a gold standard for assessment of atherosclerotic impairment of coronary arteries and for guiding of coronary intervention. On the other hand it has many limitations. Widely accepted decision making point for diagnosis of flow-limiting lesion is lumen diameter less than 50% of the reference segment. However, it has been proven that there is no correlation between angiography assessment and functional measurement by fractional flow reserve (FFR) in intermediate lesions between 40-70%1.

Based on autopsy studies we know, that atherosclerosis is more often diffuse than focal process affecting coronary arteries. These findings are in good correlation with intravascular ultrasound. The reference segment, which is angiographically normal often contains atherosclerotic plaques visible on IVUS. From this point of view we are comparing less affected segments with more affected ones during angiography and thus underestimate stenosis significance2,3. Other challenging issues are assessment of ostial lesions and bifurcations.

#### **2. Quantitative lesion assessment**

#### **2.1 Technique**

The most important parameter for quantitative lesion assessment is minimal lumen area (MLA), which has the best correlation with presence of ischemia (see below).Common misunderstanding comes from the assessment of relative severity of stenosis in percentage of "normal" reference diameter. Angiographic stenosis assessment is based on comparison of lumen diameter in reference segment and lumen diameter in the lesion. The most corresponding IVUS parameter is lumen area stenosis (LAS), which is calculated as minimal lumen area in reference segment – minimal lumen area in lesion / minimal lumen are in reference segment. More frequently used description of stenosis is plaque burden (PB), computed as external elastic membrane area – lumen area / external elastic membrane area4. We must interrogate each frame and look for the smallest lumen area, use routinely nitrates before IVUS probe insertion for avoiding spasms. In case of uncertainty in lumen measurement, especially in present of soft plaque it is recommended to flush guiding catheter by saline for clearing of picture. Using of automatic pullback devices is not necessary for quantitative lesion assessment, but allows us to perform longitudinal diameters or volumetric analysis. Manual pullback is better for analysis of a precise part of plaque, where we can stop IVUS probe to obtain more frames from the region of interest. For imaging of aorto-ostial lesions it is necessary to retract the guiding catheter back into the aorta and verify that the path of the IVUS probe is still coaxial with the ostium of the vessel5.

#### **2.2 Indication for coronary intervention**

The main indication for coronary intervention is lesion producing myocardial ischemia, which can be detect either non-invasively by stress myocardial perfusion imaging (SPECT) or invasively by measurement of pressure gradient across stenosis (fraction flow reserve, FFR). IVUS measurement correlates with both of them (table one).

manually to avoid serious mistakes and misunderstanding. The best way how to do that is

Angiography is a gold standard for assessment of atherosclerotic impairment of coronary arteries and for guiding of coronary intervention. On the other hand it has many limitations. Widely accepted decision making point for diagnosis of flow-limiting lesion is lumen diameter less than 50% of the reference segment. However, it has been proven that there is no correlation between angiography assessment and functional measurement by fractional

Based on autopsy studies we know, that atherosclerosis is more often diffuse than focal process affecting coronary arteries. These findings are in good correlation with intravascular ultrasound. The reference segment, which is angiographically normal often contains atherosclerotic plaques visible on IVUS. From this point of view we are comparing less affected segments with more affected ones during angiography and thus underestimate stenosis significance2,3. Other challenging issues are assessment of ostial lesions and

The most important parameter for quantitative lesion assessment is minimal lumen area (MLA), which has the best correlation with presence of ischemia (see below).Common misunderstanding comes from the assessment of relative severity of stenosis in percentage of "normal" reference diameter. Angiographic stenosis assessment is based on comparison of lumen diameter in reference segment and lumen diameter in the lesion. The most corresponding IVUS parameter is lumen area stenosis (LAS), which is calculated as minimal lumen area in reference segment – minimal lumen area in lesion / minimal lumen are in reference segment. More frequently used description of stenosis is plaque burden (PB), computed as external elastic membrane area – lumen area / external elastic membrane area4. We must interrogate each frame and look for the smallest lumen area, use routinely nitrates before IVUS probe insertion for avoiding spasms. In case of uncertainty in lumen measurement, especially in present of soft plaque it is recommended to flush guiding catheter by saline for clearing of picture. Using of automatic pullback devices is not necessary for quantitative lesion assessment, but allows us to perform longitudinal diameters or volumetric analysis. Manual pullback is better for analysis of a precise part of plaque, where we can stop IVUS probe to obtain more frames from the region of interest. For imaging of aorto-ostial lesions it is necessary to retract the guiding catheter back into the aorta and verify that the path of the IVUS probe is still coaxial with

The main indication for coronary intervention is lesion producing myocardial ischemia, which can be detect either non-invasively by stress myocardial perfusion imaging (SPECT) or invasively by measurement of pressure gradient across stenosis (fraction flow reserve,

just routine use of IVUS.

bifurcations.

**2.1 Technique** 

the ostium of the vessel5.

**2.2 Indication for coronary intervention** 

FFR). IVUS measurement correlates with both of them (table one).

**1.1 Limitation of angiography** 

**2. Quantitative lesion assessment** 

flow reserve (FFR) in intermediate lesions between 40-70%1.


Abbreviations: CFR - coronary flow reserve, MACE – major cardiac adverse event, MLA – minimal lumen area, MLD – minimal lumen diameter, PB - plaque burden, PCI- percutaneous coronary interventions, QCA – quantitative coronary angiography, SPECT – single photon emission computed tomography, TCFA thin cap fibroatheroma

Table 1. Studies with IVUS evaluation of hemodynamic significance

IVUS Guided PCI 111

because oblique view can overestimates lumen area25. The main target in left main bifurcation (like in other bifurcation) is to make a decision between one or two stent strategy. Pullback from just one daughter artery can answer the question whether the ostium of second branch is affected or not. For a more precise evaluation of minimal lumen

The precise coaxial position of guiding catheter is important for measurement or ostial left main stenosis, other than coaxial position of guiding catheter overestimates the lumen area. This type of inappropriate measurement can be detected by elliptical instead of spherical

The ostium of LM can be influenced not only by atherosclerosis but also by external compression between enlarged pulmonary artery and aorta. This compression occur during systolic phase and lumen is enlarged during diastolic phase (*figure 1,2*). This finding can be

According to our experience we recommend to perform all PCI´s of LM with IVUS guidance. This is supported by results of MAIN-COMPARE registry, where IVUS guidance

Fig. 1. External compression of left main during systolic phase of cardiac cycle. "Kmen ACS"

Fig. 2. No evidence of left main compression during diastolic phase of cardiac cycle.

area it is necessary to perform pullback from both daughter branches.

seen in patients with severe pulmonary artery hypertension

of left main PCI was superior to angiographic guidance26.

shape of ostial left main.

means left main coronary artery.

Based on older studies the following recommendations for IVUS detection of significant stenosis were established:

Main epicardial artery:


Left main:


However, recently published studies do not support these cut-off values. Instead of clear cut-off points there are number of different recommended values, which do not seem to be useful for routine practice. Based on these findings we must conclude that IVUS is not suitable for assessment of haemodynamic significance of intermediate lesions. IVUS can be only used for exclusion of haemodynamicly significant lesion with MLA more than 4 mm2 for main epicardial arteries and more than 6 mm2 for left main. The haemodynamic significance of each lesion is caused not only by lumen area, but also by amount of viable myocardium supplied by this vessel and by presence or absence of collaterales. These facts simply cannot be examined solely by a morphologic modality like IVUS. On the other hand the PROSPECT trial17 with clinical endpoints confirmed, that large plaque compromising lumen to 4 mm2 and less, especially together with higher content of necrotic tissue is a risk factor for future events. These issues will be matter of further studies.

There are no data about IVUS criteria for hemodynamic significance in saphenous vein graft, but it is recommend to use a cut-off point MLA 4 mm2 for graft supplying one coronary artery and MLA 6 mm2 for graft supplying two arteries.

The precise assessment of hemodynamic significance is a crucial point, because the rate of ischemic events is 5-10% / year in significant lesion and less than 1%/ year in non-ischemic lesion. Performing PCI in non-ischemic lesion increase risk of event to 2-3% / year18 and furthermore increases risk of periprocedural ischemia or myocardial necrosis during PCI.

Very old IVUS-skeptic sentence "If you want to stent, do IVUS" was quite recently supported by the work of Nam et al.19. Authors randomized 167 patients with intermediate coronary lesion between FFR guided (cut-off for PCI was FFR <0.8) and IVUS guided (cutoff MLA< 4.0 mm2) coronary intervention. PCI was performed in 33.7% lesion in FFR arm and in 91.5% in IVUS arm. This difference was highly statisticaly significant (p<0.001). On the other hand we ourselves have a different experience with IVUS assessment in borderline lesions. We estimate that we are performing PCI in 40-50% of borderline lesions based on IVUS criteria, which is closer to FRR guided arm in this study. The finding of 91.5% frequency of MLA < 4 mm2 in lesion between 40-70% is in our eyes unrealistic.

#### **2.3 Assessment of left main (LM)**

Left main stenosis is a very important predictor for future cardiac events20. Angiographic assessment of LM is often complicated for overlapping branches and short or no reference segment and can lead to inappropriate estimates of lesion severity21. IVUS is more sensitive for left main atherosclerosis than angiography22. Suter et al.23 found that in half of the patients with an inconclusive angiogram IVUS detects a significant stenosis. There is no difference for left main assessment during pullback from left anterior descending artery (LAD) or left circumflex artery (LCX)24. On the other hand for accurate assessment of ostial part of LAD and LCX is necessary to perform two pullbacks from both daughter vessels,

Based on older studies the following recommendations for IVUS detection of significant

However, recently published studies do not support these cut-off values. Instead of clear cut-off points there are number of different recommended values, which do not seem to be useful for routine practice. Based on these findings we must conclude that IVUS is not suitable for assessment of haemodynamic significance of intermediate lesions. IVUS can be only used for exclusion of haemodynamicly significant lesion with MLA more than 4 mm2 for main epicardial arteries and more than 6 mm2 for left main. The haemodynamic significance of each lesion is caused not only by lumen area, but also by amount of viable myocardium supplied by this vessel and by presence or absence of collaterales. These facts simply cannot be examined solely by a morphologic modality like IVUS. On the other hand the PROSPECT trial17 with clinical endpoints confirmed, that large plaque compromising lumen to 4 mm2 and less, especially together with higher content of necrotic tissue is a risk

There are no data about IVUS criteria for hemodynamic significance in saphenous vein graft, but it is recommend to use a cut-off point MLA 4 mm2 for graft supplying one

The precise assessment of hemodynamic significance is a crucial point, because the rate of ischemic events is 5-10% / year in significant lesion and less than 1%/ year in non-ischemic lesion. Performing PCI in non-ischemic lesion increase risk of event to 2-3% / year18 and furthermore increases risk of periprocedural ischemia or myocardial necrosis during PCI. Very old IVUS-skeptic sentence "If you want to stent, do IVUS" was quite recently supported by the work of Nam et al.19. Authors randomized 167 patients with intermediate coronary lesion between FFR guided (cut-off for PCI was FFR <0.8) and IVUS guided (cutoff MLA< 4.0 mm2) coronary intervention. PCI was performed in 33.7% lesion in FFR arm and in 91.5% in IVUS arm. This difference was highly statisticaly significant (p<0.001). On the other hand we ourselves have a different experience with IVUS assessment in borderline lesions. We estimate that we are performing PCI in 40-50% of borderline lesions based on IVUS criteria, which is closer to FRR guided arm in this study. The finding of 91.5%

Left main stenosis is a very important predictor for future cardiac events20. Angiographic assessment of LM is often complicated for overlapping branches and short or no reference segment and can lead to inappropriate estimates of lesion severity21. IVUS is more sensitive for left main atherosclerosis than angiography22. Suter et al.23 found that in half of the patients with an inconclusive angiogram IVUS detects a significant stenosis. There is no difference for left main assessment during pullback from left anterior descending artery (LAD) or left circumflex artery (LCX)24. On the other hand for accurate assessment of ostial part of LAD and LCX is necessary to perform two pullbacks from both daughter vessels,

factor for future events. These issues will be matter of further studies.

frequency of MLA < 4 mm2 in lesion between 40-70% is in our eyes unrealistic.

**2.3 Assessment of left main (LM)** 

coronary artery and MLA 6 mm2 for graft supplying two arteries.

stenosis were established: Main epicardial artery: - MLA < 4 mm2 - MLD < 2 mm

Left main:


because oblique view can overestimates lumen area25. The main target in left main bifurcation (like in other bifurcation) is to make a decision between one or two stent strategy. Pullback from just one daughter artery can answer the question whether the ostium of second branch is affected or not. For a more precise evaluation of minimal lumen area it is necessary to perform pullback from both daughter branches.

The precise coaxial position of guiding catheter is important for measurement or ostial left main stenosis, other than coaxial position of guiding catheter overestimates the lumen area. This type of inappropriate measurement can be detected by elliptical instead of spherical shape of ostial left main.

The ostium of LM can be influenced not only by atherosclerosis but also by external compression between enlarged pulmonary artery and aorta. This compression occur during systolic phase and lumen is enlarged during diastolic phase (*figure 1,2*). This finding can be seen in patients with severe pulmonary artery hypertension

According to our experience we recommend to perform all PCI´s of LM with IVUS guidance. This is supported by results of MAIN-COMPARE registry, where IVUS guidance of left main PCI was superior to angiographic guidance26.

Fig. 1. External compression of left main during systolic phase of cardiac cycle. "Kmen ACS" means left main coronary artery.

Fig. 2. No evidence of left main compression during diastolic phase of cardiac cycle.

IVUS Guided PCI 113

Fig. 5. Huge thrombus located on very small plaque causing acute coronary syndrome. Left side is cross sectional view, right side is longitudinal view (thrombus is located in the

Fig. 6. Plague rupture with visible cavity after embolization of plaque mass. Patient with

True aneurysm is defined as both an external elastic membrane (EEM) and lumen area 50% larger than the proximal reference segment with intact three layers of vessel wall (*figure 7*). Lesions which seem to be the aneurysms from angiographic assessment are an true aneurysm in 37% of such findings. The rest are normal segments adjacent to plaque (53%), complex atherosclerotic plaque (16%) and pseudoaneurysm (4%)31. Coronary pseudoaneurysm is due to rupture of vessel wall and in IVUS picture the three layers of vessel are not present, the shape of pseudoaneurysm is often irregular. From a practical point of view, pseudoaneurysms

are seen only after coronary interventions causing trauma of vessel wall.

circle).

acute myocardial infarction.

**3.2 Aneurysms** 

### **3. Lesion morphology**

#### **3.1 IVUS in lesion with angiographic filling defect "hazy lesions"**

The main finding in so called hazy lesions is a defect in the contrast filling of coronary artery. The reasons for this include:


Thrombus is the most dangerous cause and many hazy lesions are treated like thrombuscontaining lesions with administration of IIbIIIa glycoprotein inhibitors, use of embolic protection devices or covered stents. However, real presence of intracoronary thrombosis is 50-60% of all hazy lesions27. Sensitivity of IVUS for thrombus is low (about 50%), so from IVUS picture we simply cannot rule out the presence of thrombus (the highest sensitivity for thrombus has optical coherence tomography), but IVUS can confirm other causes and mainly causes which are not indicated fore PCI. This strategy decreases frequency of PCI in hazy lesions to 15-20%28-30

Fig. 3. Eccentric calcification.

Fig. 4. Dissection with visible tear (arrow) and small thrombus (in circle).

The main finding in so called hazy lesions is a defect in the contrast filling of coronary

Thrombus is the most dangerous cause and many hazy lesions are treated like thrombuscontaining lesions with administration of IIbIIIa glycoprotein inhibitors, use of embolic protection devices or covered stents. However, real presence of intracoronary thrombosis is 50-60% of all hazy lesions27. Sensitivity of IVUS for thrombus is low (about 50%), so from IVUS picture we simply cannot rule out the presence of thrombus (the highest sensitivity for thrombus has optical coherence tomography), but IVUS can confirm other causes and mainly causes which are not indicated fore PCI. This strategy decreases frequency of PCI in


Fig. 4. Dissection with visible tear (arrow) and small thrombus (in circle).

**3.1 IVUS in lesion with angiographic filling defect "hazy lesions"** 

**3. Lesion morphology** 


hazy lesions to 15-20%28-30

Fig. 3. Eccentric calcification.

artery. The reasons for this include: - eccentric calcification (*figure 3*)

Fig. 5. Huge thrombus located on very small plaque causing acute coronary syndrome. Left side is cross sectional view, right side is longitudinal view (thrombus is located in the circle).

Fig. 6. Plague rupture with visible cavity after embolization of plaque mass. Patient with acute myocardial infarction.

#### **3.2 Aneurysms**

True aneurysm is defined as both an external elastic membrane (EEM) and lumen area 50% larger than the proximal reference segment with intact three layers of vessel wall (*figure 7*). Lesions which seem to be the aneurysms from angiographic assessment are an true aneurysm in 37% of such findings. The rest are normal segments adjacent to plaque (53%), complex atherosclerotic plaque (16%) and pseudoaneurysm (4%)31. Coronary pseudoaneurysm is due to rupture of vessel wall and in IVUS picture the three layers of vessel are not present, the shape of pseudoaneurysm is often irregular. From a practical point of view, pseudoaneurysms are seen only after coronary interventions causing trauma of vessel wall.

IVUS Guided PCI 115

Several studies have been conducted in this field. Their results are summarized in table 2.

not declared 1.9%\*

12<sup>+</sup>

14<sup>+</sup>

8%<sup>+</sup>

16%♣ – aggressive PCI 20% -stent

30%<sup>∇</sup> IVUS 37% angio

41% angio

31.1% angio

22%♣ IVUS 38% angio (p< 0.05)

 - PCI 11%- stent

plaques compensated by positive remodeling allow use of aggressive dilatation without risk of significant

IVUS decreases number of

low restenosis comparable

"stent like" effect after IVUS guided balloon dilatation has similar rate restenosis like a BMS

IVUS guided aggressive PCI with provisional stenting is safe and with the same results like routine stenting

same restenosis rate. Lower TLR in IVUS group

lower MACE in IVUS guided group, better C/E3 ratio in IVUS group

lower MACE in IVUS guided group, better C/E4 ratio in v IVUS group

Lower restenosis, MACE and number of stents in

IVUS group

2,5 year, C/E cost/effectiveness ratio , <sup>∇</sup> 2 years, TLR: target

dissections

% use of larger balloon than angiographic lumen diameter is safe and with low risk for restenosis

% small dissection are not flow limiting

with BMS

implanted stents

**study target restenosis MACE comments** 

21%<sup>+</sup>

19%<sup>+</sup>

8%<sup>+</sup> - PCI 16% - stent

16.8%♣

aggressive PCI 18.1% stent

29%♣ IVUS, 35% angio

25%♣ IVUS 39% angio (p< 0.05)

not declared 22%• IVUS

not declared 19.8%<sup>∇</sup> IVUS

**4.2 IVUS guided plain balloon PCI** 

using larger balloon than angiographicly measured vessel diameter

IVUS guided balloon dilatation

IVUS guided balloon dilatation

IVUS guided balloon dilatation and stent only in

IVUS guided aggressive PCI (stent only when necessary) vs. routine stenting

IVUS vs. angio guided PCI

IVUS guided vs. angio guided (IVUS controlled) PCI

IVUS guided vs. angio guided PCI

IVUS guided intervention in lesions longer than

15 mm

12 months MACE, ♣ 6 months MACE, •

lesion revascularization, BMS: bare metal stents

Table 2. IVUS guided coronary intervention

\* non randomized study, control group is composed by similar lesions

unsatisfactory result

case of

CLOUT34 102 pts.

Haase35 144 pts.

Schroeder36 252 pts.

Abizaid37 284 pts.

BEST38 254 pts.

SIPS39 269 pts.

Gaster40 108 pts.

Meuller41 C/E analysis of SIPS study

Colombo42\* 130 pts.

+

Fig. 7. Stent located in coronary aneurysm.

#### **3.3 True versus false lumen**

False lumen is created by dissection, either spontaneous or iatrogenic during coronary intervention (wire insertion or after balloon/stent dilatation). Dissections are treated by stent implantation and a flow non limiting dissection can be let to spontaneous healing. Stent insertion to the true lumen is a crucial point for proper treatment of dissection. True lumen can be identified by three-layered appearance and by origin of side branches. False lumen contains more echogenic blood flow5 (*figure 8*).

Fig. 8. Dissection with IVUS probe located in the false lumen with staying blood.

#### **4. Balloon angioplasty**

#### **4.1 The mechanism of balloon PCI**

The main mechanism of lumen enlargement during balloon dilatation is a plaque rupture, which enables lumen dilatation32. This finding was also confirmed by IVUS during *in vivo* studies, mainly in eccentric plaques (which are mainly present in coronary arteries). Another mechanism of lumen enlargement during balloon angioplasty is plaque compression and plaque redistribution, which are the main mechanism in concentric plaques33.

False lumen is created by dissection, either spontaneous or iatrogenic during coronary intervention (wire insertion or after balloon/stent dilatation). Dissections are treated by stent implantation and a flow non limiting dissection can be let to spontaneous healing. Stent insertion to the true lumen is a crucial point for proper treatment of dissection. True lumen can be identified by three-layered appearance and by origin of side branches. False

Fig. 8. Dissection with IVUS probe located in the false lumen with staying blood.

The main mechanism of lumen enlargement during balloon dilatation is a plaque rupture, which enables lumen dilatation32. This finding was also confirmed by IVUS during *in vivo* studies, mainly in eccentric plaques (which are mainly present in coronary arteries). Another mechanism of lumen enlargement during balloon angioplasty is plaque compression and plaque redistribution, which are the main mechanism in concentric

Fig. 7. Stent located in coronary aneurysm.

lumen contains more echogenic blood flow5 (*figure 8*).

**3.3 True versus false lumen** 

**4. Balloon angioplasty** 

plaques33.

**4.1 The mechanism of balloon PCI** 

#### **4.2 IVUS guided plain balloon PCI**

Several studies have been conducted in this field. Their results are summarized in table 2.


+ 12 months MACE, ♣ 6 months MACE, • 2,5 year, C/E cost/effectiveness ratio , <sup>∇</sup> 2 years, TLR: target lesion revascularization, BMS: bare metal stents

\* non randomized study, control group is composed by similar lesions

Table 2. IVUS guided coronary intervention

IVUS Guided PCI 117

1. Using of larger balloons (balloon/artery ratio more than 1 according to angiographic assessment) is safe and without increased risk for acute severe complications. In hospital MACE were 1.4-3.9%. Occurrence of significant dissection varies in large range, probably for different definition of this kind of complication. However, all

2. The rate of in stent restenosis is consistently low in all studies. It means that it is safe to avoid stent implantation after fulfilling of IVUS criteria for adequate results after balloon dilation. Surprisingly, higher in stent restenosis and higher MACE were found in some studies in patients with stent implantation compared to plain balloon dilatation. The reason for this finding is probably for bias; according to the study design stents were implanted to lesions with non satisfactory results after balloon dilatation or for treatment of complications after balloon dilatation. Higher occurrence of in stent

3. The dark side of IVUS guided balloon angioplasty is a prolonged procedural time (5-13 minutes), increased X-ray time (2-3.6 minutes) and higher amount of contrast dye (12-34

4. Routine IVUS guided intervention can be beneficial from financial point of view. Optimal decision making decreases number of implanted stent and frequency of in stent restenosis and avoids peri-procedural complications from non-indicated coronary

5. IVUS guided intervention should be used for avoiding stent implantation in patients

The most important mechanisms are plaque redistribution (inside stent) and plaque extrusion (outside stent) to the reference segments (more frequently to the distal one)43. Plaque redistribution and extrusion play role during restenosis in edge segment of stent44. Less important factors are plaque compression, plaque embolization and vessel enlargement

Final stent diameter is a result of interplay between pressure during implantation and vessel wall resistance. Declared stent diameters for different pressures during dilatation do not correlate with real stent diameter after implantation. These numbers for stent diameter come from *in vitro* tests in water and do not reflect real situation in the vessel. Costa et al.45 compared 200 drug eluting stent diameters from IVUS measurement immediately after implantation and declared stent diameter for nominal pressure. At least 90% of minimal lumen diameter for nominal pressure was reached only in 4% of stents. In stent area can be decreased immediately after implantation also by protrusion of plaque material through the

It is important to distinguish between stent expansion and stent apposition. Expansion means ratio between minimal stent area (MSA) and lumen area in reference segment. Inadequate expansion (*figure 10*) can be improved by high pressure postdilatation. Apposition reflects contact between stent struts and vessel wall. Inadequate apposition

(*figure 11*) can be solved by low pressure dilatation with a bigger balloon.

Based on these studies with IVUS guided balloon dilatation we can summarize:

authors declare low risk for sever acute dissection.

restenosis and MACE is expected in these types of lesions.

**5.1 Mechanism of lumen enlargement during stent implantation** 

ml)38-41

struts46 (*figure9*).

interventions40,41.

unsuitable for dual antiplatelet therapy.

(more in vessel with negative remodeling before PCI)43.

**5. Bare-metal stent implantation** 


The table 3 summarizes the strategy for choosing balloon diameter, acute complications and frequency of stenting in aforesaid studies.

Abbreviations: ref – reference segment, refprox - reference proximal segment, refdist – reference distal segment , \* angiographic, \*\* IVUS, B/A - balloon artery ratio, mean MLAref – mean lumen in reference segments, QCA = quantitative coronary angiography - EEMmaxlesion – maximal EEM in lesions, EEM minlesion – minimal EEM in lesions, ° long lesion intervention

Table 3. Different strategies for choosing of balloon diameter.

The most frequent formula for choosing of balloon diameter is (EEMrefprox + EEMrefdist ) / 2 coming form BEST study or just EEMrefdist, which is adapted form the study SIPS. IVUS criteria for optimal result after balloon dilatation are listed in table 4.


Abbreviations: mean MLAref - mean minimal lumen area in reference segment, QCA - quantitative coronary angiography, \* long lesion intervention

Table 4. IVUS criteria of optimal result after balloon dilatation.

The table 3 summarizes the strategy for choosing balloon diameter, acute complications and

**acute severe dissection** 

 3% IVUS, 3.2% angio

12% 2%

mean MLDref + mean MVDref / 2 5% not declared

(MLArefprox + MLArefdist) / 2 not declared 85% angio,

not declared not declared 49.5% angio,

**stenting** 

group)

49.5% angio, 49.7% IVUS

87% IVUS

49.7% IVUS

**study B/A ratio equation for balloon diameter occurrence of** 

Haase35 0.8-1 \*\* EEM in lesion 11% 0%

(2xEEM refprox + 2xEEMrefdist +

Abizaid37 1.34 \* (EEMmaxlesion + EEM minlesion) / 2 28% 53%

MLDref + MVDref / 2 (in smallest

Colombo42 ° 1.23 \*\* EEM in lesion 4.6% 51.5% Abbreviations: ref – reference segment, refprox - reference proximal segment, refdist – reference distal segment , \* angiographic, \*\* IVUS, B/A - balloon artery ratio, mean MLAref – mean lumen in reference segments, QCA = quantitative coronary angiography - EEMmaxlesion – maximal EEM in lesions, EEM

coming form BEST study or just EEMrefdist, which is adapted form the study SIPS. IVUS criteria for optimal result after balloon dilatation are listed in table 4.

CLOUT34 MLA ≥ 65% mean MLAref, no signs of flow limiting disection

SIPS39 MLA ≥ 65% mean MLAref, no signs of flow limiting disection

The most frequent formula for choosing of balloon diameter is (EEMrefprox + EEMrefdist ) / 2

Haase35 increasing of MLA by at least 20% of EEM, no signs of flow limiting disection Abizaid37 MLA ≥ 65% mean MLAref, or MLA ≥ 6mm2, no signs of flow limiting disection BEST38 residual stenosis < 30% (IVUS and angio), MLA > 6mm2, no signs of flow

Mueller41 residual stenosis ≤ 35%, MLA > 65% meanMLAref, no signs of flow limiting

Abbreviations: mean MLAref - mean minimal lumen area in reference segment, QCA - quantitative

BEST38 1.25 \* (EEM refprox + EEMrefdist) / 2 18% 44% (in IVUS

2xEEM lesion)/ 6

ref. segment)

minlesion – minimal EEM in lesions, ° long lesion intervention

limiting disection

coronary angiography, \* long lesion intervention

Colombo42\* MLA ≥ 50% EEMlesion , MLA ≥ 5.5 mm2

Table 4. IVUS criteria of optimal result after balloon dilatation.

disection

Table 3. Different strategies for choosing of balloon diameter.

frequency of stenting in aforesaid studies.

0.8-1\*\*

0.88\*\*

IVUS\* 1.03 angio

declared

declared

CLOUT34 1.3 \*

Schroeder36 1.4 \*

SIPS39 1.23

Gaster40 not

Meuller41 not

**study criteria**

Based on these studies with IVUS guided balloon dilatation we can summarize:


#### **5. Bare-metal stent implantation**

#### **5.1 Mechanism of lumen enlargement during stent implantation**

The most important mechanisms are plaque redistribution (inside stent) and plaque extrusion (outside stent) to the reference segments (more frequently to the distal one)43. Plaque redistribution and extrusion play role during restenosis in edge segment of stent44. Less important factors are plaque compression, plaque embolization and vessel enlargement (more in vessel with negative remodeling before PCI)43.

Final stent diameter is a result of interplay between pressure during implantation and vessel wall resistance. Declared stent diameters for different pressures during dilatation do not correlate with real stent diameter after implantation. These numbers for stent diameter come from *in vitro* tests in water and do not reflect real situation in the vessel. Costa et al.45 compared 200 drug eluting stent diameters from IVUS measurement immediately after implantation and declared stent diameter for nominal pressure. At least 90% of minimal lumen diameter for nominal pressure was reached only in 4% of stents. In stent area can be decreased immediately after implantation also by protrusion of plaque material through the struts46 (*figure9*).

It is important to distinguish between stent expansion and stent apposition. Expansion means ratio between minimal stent area (MSA) and lumen area in reference segment. Inadequate expansion (*figure 10*) can be improved by high pressure postdilatation. Apposition reflects contact between stent struts and vessel wall. Inadequate apposition (*figure 11*) can be solved by low pressure dilatation with a bigger balloon.

IVUS Guided PCI 119

high pressure dilatation, which (together with dual antiagregation) decreased the rate of subacute stent thrombosis to 0.9%47. Routine use of high pressure dilatation (up to 20 atm.) improves stent expansion and apposition without increasing acute complications48. Choi et al.49 found, that only 54% of angiographically adequatly expanded stents fulfill IVUS criteria for optimal stent expansion. Authors performed high pressure postdilatation and final MACE was only 11% in 6 months. This study confirms minimal stent area (MSA) as the

There are many studies focusing on impact of IVUS guidance on stent implantation. They

Different criteria for optimal stent expansion were used in published trials, details are

9.7% 12.1% <sup>+</sup> the second lowest

restenosis rate in studies

fulfilling IVUS criteria

with BMS

not analyzed Restenosis 13.5% in stent

**study name study goal restenosis MACE comments** 

20.9% IVUS 29.9% angio (p=0.033) \*\*

most important risk factor of restenosis (*figure 12*).

Fig. 12. In stent restenosis

are summarized in table 5.

summarized in table 6.

MUSIC50 161 pts.

Blasini51 105 pts.

**5.3 IVUS guided stent implantation** 

restenosis during IVUS guided stent implantation

IVUS vs. angio\* guided stent implantation

Fig. 9. Plaque protrusion through the struts to the lumen.

Fig. 10. Inadequate stent expansion.

#### **5.2 High pressure stent dilatation**

The first implantations of Palmaz-Schatz and Gianturco-Roubin stents were complicated by high occurrence of subacute stent thrombosis. Colombo and coworkers started IVUS guided

The first implantations of Palmaz-Schatz and Gianturco-Roubin stents were complicated by high occurrence of subacute stent thrombosis. Colombo and coworkers started IVUS guided

Fig. 9. Plaque protrusion through the struts to the lumen.

Fig. 10. Inadequate stent expansion.

Fig. 11. Inadequate stent aposition

**5.2 High pressure stent dilatation** 

high pressure dilatation, which (together with dual antiagregation) decreased the rate of subacute stent thrombosis to 0.9%47. Routine use of high pressure dilatation (up to 20 atm.) improves stent expansion and apposition without increasing acute complications48. Choi et al.49 found, that only 54% of angiographically adequatly expanded stents fulfill IVUS criteria for optimal stent expansion. Authors performed high pressure postdilatation and final MACE was only 11% in 6 months. This study confirms minimal stent area (MSA) as the most important risk factor of restenosis (*figure 12*).

Fig. 12. In stent restenosis

#### **5.3 IVUS guided stent implantation**

There are many studies focusing on impact of IVUS guidance on stent implantation. They are summarized in table 5.

Different criteria for optimal stent expansion were used in published trials, details are summarized in table 6.


IVUS Guided PCI 121

Katritsis61 full stent apposition, MSA ≥ 90% meanMLAref, symmetrical expansion (min

Hanekamp63 full stent apposition, MSA ≥ 90% meanMLAref, or MSA ≥ 100% minMLAref,

Choi49 complete stent apposition, MSA ≥ 80% distalMLAref , symmetrical expansion

Colombo47 full stent apposition , MSA ≥ minMLAref, MLA > 60% MLAref in edge regions

Ahmed44 complete stent apposition, MSA ≥ 80% meanMLAref or MSA 7.5 mm2 MUSIC50\* - complete stent apposition, MSA ≥ 90 meanMLAref or ≥ 100 minMLAref

MSA ≥ 80% meanMLAref or ≥ 90% minMLAref MSA in proximal part of stent ≥ 90% proxMLAref symmetrical expansion (minSD/maxSD > 0.7) Blasini51 full stent apposition, MSA > 8 mm2, or MSA ≥ 90% meanMLAref, complete

OPTICUS53 MUSIC criteria, residual stenosis les than 10% (angiographically)

AVID55 full stent apposition, residual stenosis < 10%, no signs of dissection

**criteria restenosis rate** 

MSA > 9 mm2 11% MSA > 9 mm2 a MSA ≥ 80% meanMLAref 12.5% MSA ≥ 55% meanEEMref 17% MSA ≥ 90% meanMLAref 21% MSA ≥ 90% distal MLAref 22%

Table 7. Risk of ISR and achievement of different IVUS parameters.

TULIP56 complete stent apposition, MSD ≥ 80% meanMLDref , MSA ≥ 90% distalMLAref Abbreviations: SD - stent diameter, meanMLAref - mean minimal lumen area in reference segments, minMLAref minimal - minimal lumen area i reference segments, MSD – minimal stent diameter, MSA –

\* all criteria were fulfilled in 81% patients and these patients were treated only with acetylosalycilic acid

The main goal for IVUS guidance of stent implantation is a larger minimal stent diameter and minimal stent area. Further improvement is seen in strut apposition. Minimal stent area is the most important risk factor for development of in stent restenosis (ISR). The cut-off point for risk of ISR is 8mm2 in vessel ≥ 3 mm and 6 mm2 in vessel < 3mm64. The rate of in stent restenosis according to achievement of different IVUS parameters is summarized in table 7.

symetrical expansion (minSD/maxSD > 0.7), (correlation with FFR 0.94)

SD/maxSD > 0.7) (correlation with FFR 0.94)

Gorge48 symmetrical stent expansion, MSD ≥ 3 mm, full apposition

**study criteria for optimal expanded stent** 

Fearon62 MSA 7 mm2 (correlates with FFR 0.96)

(minSD/maxSD > 0.8)


coverage of dissection

CRUISE54 residual stenosis < 10% (angiographically)

RESIST52 MSA ≥ 80% meanMLAref

and rate of subacute stent thrombosis was 1.3%

Abbrevation: MSA – minimal stent area

Table 6. Different criteria for optimal stent expansion.

minimal stent area


\* non randomized trial, angio group is a historic control, \*\* IVUS criteria was fulfilled in 49.5% patients and in these ones was restenosis 13.5%, <sup>+</sup> 6 months, ♣ 12 months, • 9 months, TVR - target vessel revascularization

Table 5. Trials assessing IVUS guided stent implantation.

not declared IVUS guidance does not

restenosis

MACE

17.9%♣ IVUS 15.3% angio (p=0.4)

8.5%• in IVUS group 15.3% in angio group (p=0.019)

IVUS 19% angio (p=0,11)

19% angio

 IVUS 20% angio (p=0.01)

IVUS 12.2% angio (p=0.9)

7.3% IVUS 16% angio

22% IVUS 41% angio

6%<sup>+</sup>

decrease rate of in stent

IVUS guiding do not decrease neither rate of in stent restenosis nor

IVUS guided stenting leads to lower TVR

IVUS leads to lower periprocedural complications with a trend for lower TVR in IVUS group(p=0.08)

IVUS leads to larger lumen, but without any effect on 30 days and 12

months MACE

Better clinical and angiographic results in IVUS group despite more

implanted stents

discretion

trial

saving

9 months, TVR - target vessel

Larger MLD in IVUS group, but without difference in MACE. Criteria for adequate IVUS stent expansion was let only on operators

Best results for IVUS guided in randomized

IVUS guiding is cost

**study name study goal restenosis MACE comments** 

22.5% IVUS 28.8% angio (p=0.25)

24.5% IVUS 22.5% angio (p=0.68)

not declared TVR

not declared 12%<sup>+</sup>

23%<sup>+</sup>

 IVUS 46% angio (p=0.008)

10% IVUS 27%

\* non randomized trial, angio group is a historic control, \*\* IVUS criteria was fulfilled in 49.5% patients

6 months, ♣ 12 months, •

angio

16% IVUS 25% angio

not declared 18% IVUS

not declared TVR 13.8%

IVUS vs. angio guided (IVUS controlled) stent implantation

IVUS vs. angio guided stent implantation

IVUS vs. angio guided (IVUS controlled) stent implantation

IVUS vs. angio guided stent implantation

IVUS vs. angio guided stent implantation

IVUS vs. angio guided stenting of long lesions

IVUS vs. angio guided stenting

IVUS vs. angio guided stenting

IVUS vs. angio guided stenting

Table 5. Trials assessing IVUS guided stent implantation.

and in these ones was restenosis 13.5%, <sup>+</sup>

RESIST52 study 155 pts.

OPTICUS53 550 pts.

CRUISE54 499 pts.

Choi49 278 pts.

AVID55 800 pts.

TULIP56 150 pts.

PRESTO57 796 pts with IVUS vs. 8274 with angio

DIPOL58 163

Gaster55,60 108 pts

revascularization

pts.


Abbreviations: SD - stent diameter, meanMLAref - mean minimal lumen area in reference segments, minMLAref minimal - minimal lumen area i reference segments, MSD – minimal stent diameter, MSA – minimal stent area

\* all criteria were fulfilled in 81% patients and these patients were treated only with acetylosalycilic acid and rate of subacute stent thrombosis was 1.3%

Table 6. Different criteria for optimal stent expansion.

The main goal for IVUS guidance of stent implantation is a larger minimal stent diameter and minimal stent area. Further improvement is seen in strut apposition. Minimal stent area is the most important risk factor for development of in stent restenosis (ISR). The cut-off point for risk of ISR is 8mm2 in vessel ≥ 3 mm and 6 mm2 in vessel < 3mm64. The rate of in stent restenosis according to achievement of different IVUS parameters is summarized in table 7.


Abbrevation: MSA – minimal stent area

Table 7. Risk of ISR and achievement of different IVUS parameters.

IVUS Guided PCI 123

recognized as further risk factors for IST development86,87. The occurrence of IST in BMS is

The risk factors for IST development can be revealed by IVUS control after stent implantation. Roy et al.89 published study, where IVUS guidance of DES implantation reduced development of IST in 30 days (0.5% in IVUS vs. 1.5% in angio guided group) and 12 month (0.7% in IVUS vs. 2.0% in angio guided group), as well as decreased need for revascularization and MACE in 30 day. Unfortunately, there were no clear criteria for adequate stent deployment in this study. Claessen et al.90 published a study comparing angio and IVUS guidance in 1504 sirolimus eluting stent implantation in the MATRIX (Comprehensive Assessment of Sirolimus-Eluting Stents in Complex Lesions) registry. They found significantly lower occurrence of myocardial infarction and combined endpoint of myocardial infarction and death in IVUS guided group. Hur et al.91 published their enormous registry of angio (3744 patients) versus IVUS (4627 patients) guided stent implantation. The main finding of this study is lower mortality in IVUS guided group. This result was seen mainly in DES implantation, because mortality in BMS group was the same. However, the explanation of this interesting finding is not clear, because the occurrence of myocardial infarction, target vessel revascularization and in stent thrombosis was without significance differences between angio and IVUS group. Based on aforesaid trials we can conclude, that IVUS guidance of DES implantation probably improves patient's outcome,

but further trials are needed for better understanding of this phenomenon.

not known, several mechanisms are thought:

(OR 6,51).



patients needed revascularization in a study done by Alfonso et al.100.

Important phenomenon in DES implantation is incomplete stent apposition (ISA), which means, that at least one strut is not adequately apposed to vessel wall. One should distinguish between acute stent malapposition, which is present immediately after stent implantation, late stent malapposition (LSM), which can be persistent , it means that acute malapposition is not healed and late-acquired stent malapposition (LASM), which develops despite normal finding after stent implantation. The mechanism of LASM development is


The frequency of LSM is not clear, a quite broad range for this phenomenon was published (4-21%)92,93. LSM is not found only in DES, but also in BMS, where it's incidence is 4.4- 5.4%94,95. Empty space behind stent struts can lead to decrease of blood flow in this region and cause development of thrombosis. However, this theoretic concept was not proved in any study following the natural course of patients with LSM. Hong et al.96,97 did not find any clinical adverse event in patient with LSM during 10 months follow up. On the other hand Cook et al.98 published correlation between LSM and very late IST. Moreover, Hassan et al.99 published meta-analysis of 17 randomized trials focusing on LSM in BMS as well as DES. They found four times higher risk of LASM in patients with DES compared to BMS and LSM (acquired or persistent) increased significantly risk for (very) late in stent thrombosis

A rare complication (1.25%) of DES implantation is development of coronary aneurysm. The definition of aneurysm is focal enlargement of vessel lumen, which is 50% larger than adjacent reference vessel. Coronary aneurysm is not a benign finding as up to 40% of

estimated at 0.9%88.

The lowest rate of ISR is in stents with MSA > 9mm2. However, for achievement of this MSA it is necessary to use a 3.5mm stent (with ideal stent area 9.6mm2), because 3mm stent has an ideal stent area 7.1mm2. MSA 8 mm2 as a sufficient post-stenting area was confirmed by Hoffmann et al65. They found a mean MSA in stent with ISR 7.1mm2 and 8.1mm2 in stents without development of ISR. This cut-off MSA is also a predictor for development of ISR in long stents66. Further predictors for ISR are:


MSA is the most important factor for development of in stent thrombosis (IST)74. The incidence of this feared complication is less than 0.5%74.

Parise et al.75 published recently a meta-analysis of all randomized studies comparing IVUS guided vs. angio guided stenting in pre-drug-eluting stent era. They concluded that IVUS guided stenting significantly lowered the 6-month angiographic restenosis rates, 12-month revascularization and MACE rate. They did not find any effect of IVUS guidance on death or myocardial infarction.

### **6. Drug-eluting stent implantation**

Drug eluting stents (DES) significantly reduce the risk of in stent restenosis compared to BMS76-78. IVUS guidance seemed to be needless for DES excellent results. However, several issues are still a problem even with the use of DES and some of them, like in stent thrombosis, seem to be more important than in BMS .

In stent restenosis still exists and it´s incidence is 5-10% in selected populations79-80. It seems to be more pronounced in paclitaxel eluting stent than sirolimus eluting stents81. Minimum stent area that best separates restenosis from no restenosis in DES is between 5.0-6.0 mm2 82,83.

The occurrence of in stent thrombosis (IST) in DES is 1-1.5%84. The main cause of IST is stent under expansion. DES with further IST development showed significantly lower MSA (4.3- 4.6 mm2). Further risk factor for IST development is residual edge stenosis, defined as a MLA < 4 mm2 and a plaque burden > 70%85,74. These risk factors remain the same like in BMS, where the presence of dissection, thrombus or tissue prolaps into the stent were

The lowest rate of ISR is in stents with MSA > 9mm2. However, for achievement of this MSA it is necessary to use a 3.5mm stent (with ideal stent area 9.6mm2), because 3mm stent has an ideal stent area 7.1mm2. MSA 8 mm2 as a sufficient post-stenting area was confirmed by Hoffmann et al65. They found a mean MSA in stent with ISR 7.1mm2 and 8.1mm2 in stents without development of ISR. This cut-off MSA is also a predictor for development of ISR in

MSA is the most important factor for development of in stent thrombosis (IST)74. The

Parise et al.75 published recently a meta-analysis of all randomized studies comparing IVUS guided vs. angio guided stenting in pre-drug-eluting stent era. They concluded that IVUS guided stenting significantly lowered the 6-month angiographic restenosis rates, 12-month revascularization and MACE rate. They did not find any effect of IVUS guidance on death

Drug eluting stents (DES) significantly reduce the risk of in stent restenosis compared to BMS76-78. IVUS guidance seemed to be needless for DES excellent results. However, several issues are still a problem even with the use of DES and some of them, like in stent

In stent restenosis still exists and it´s incidence is 5-10% in selected populations79-80. It seems to be more pronounced in paclitaxel eluting stent than sirolimus eluting stents81. Minimum stent area that best separates restenosis from no restenosis in DES is between 5.0-6.0 mm2 82,83. The occurrence of in stent thrombosis (IST) in DES is 1-1.5%84. The main cause of IST is stent under expansion. DES with further IST development showed significantly lower MSA (4.3- 4.6 mm2). Further risk factor for IST development is residual edge stenosis, defined as a MLA < 4 mm2 and a plaque burden > 70%85,74. These risk factors remain the same like in BMS, where the presence of dissection, thrombus or tissue prolaps into the stent were


long stents66. Further predictors for ISR are:


incidence of this feared complication is less than 0.5%74.

Fig. 13. Large plaque compensated by positive vessel remodeling

**6. Drug-eluting stent implantation** 

thrombosis, seem to be more important than in BMS .


or myocardial infarction.

recognized as further risk factors for IST development86,87. The occurrence of IST in BMS is estimated at 0.9%88.

The risk factors for IST development can be revealed by IVUS control after stent implantation. Roy et al.89 published study, where IVUS guidance of DES implantation reduced development of IST in 30 days (0.5% in IVUS vs. 1.5% in angio guided group) and 12 month (0.7% in IVUS vs. 2.0% in angio guided group), as well as decreased need for revascularization and MACE in 30 day. Unfortunately, there were no clear criteria for adequate stent deployment in this study. Claessen et al.90 published a study comparing angio and IVUS guidance in 1504 sirolimus eluting stent implantation in the MATRIX (Comprehensive Assessment of Sirolimus-Eluting Stents in Complex Lesions) registry. They found significantly lower occurrence of myocardial infarction and combined endpoint of myocardial infarction and death in IVUS guided group. Hur et al.91 published their enormous registry of angio (3744 patients) versus IVUS (4627 patients) guided stent implantation. The main finding of this study is lower mortality in IVUS guided group. This result was seen mainly in DES implantation, because mortality in BMS group was the same. However, the explanation of this interesting finding is not clear, because the occurrence of myocardial infarction, target vessel revascularization and in stent thrombosis was without significance differences between angio and IVUS group. Based on aforesaid trials we can conclude, that IVUS guidance of DES implantation probably improves patient's outcome, but further trials are needed for better understanding of this phenomenon.

Important phenomenon in DES implantation is incomplete stent apposition (ISA), which means, that at least one strut is not adequately apposed to vessel wall. One should distinguish between acute stent malapposition, which is present immediately after stent implantation, late stent malapposition (LSM), which can be persistent , it means that acute malapposition is not healed and late-acquired stent malapposition (LASM), which develops despite normal finding after stent implantation. The mechanism of LASM development is not known, several mechanisms are thought:


The frequency of LSM is not clear, a quite broad range for this phenomenon was published (4-21%)92,93. LSM is not found only in DES, but also in BMS, where it's incidence is 4.4- 5.4%94,95. Empty space behind stent struts can lead to decrease of blood flow in this region and cause development of thrombosis. However, this theoretic concept was not proved in any study following the natural course of patients with LSM. Hong et al.96,97 did not find any clinical adverse event in patient with LSM during 10 months follow up. On the other hand Cook et al.98 published correlation between LSM and very late IST. Moreover, Hassan et al.99 published meta-analysis of 17 randomized trials focusing on LSM in BMS as well as DES. They found four times higher risk of LASM in patients with DES compared to BMS and LSM (acquired or persistent) increased significantly risk for (very) late in stent thrombosis (OR 6,51).

A rare complication (1.25%) of DES implantation is development of coronary aneurysm. The definition of aneurysm is focal enlargement of vessel lumen, which is 50% larger than adjacent reference vessel. Coronary aneurysm is not a benign finding as up to 40% of patients needed revascularization in a study done by Alfonso et al.100.

IVUS Guided PCI 125

Main role of IVUS guidance in bifurcation PCI is precise assessment of atherosclerotic burden of main vessel, carina, ostial part of side branch and the choice of the best strategy based on these findings. IVUS can improve the choice of ideal stent diameter, because bifurcation area is frequently affected by negative remodeling, which is not visible in

IVUS should be used of most cases of uncertain atherosclerotic distribution in bifurcation lesions, because in case of favorable finding in SB ostium a planned complex procedure can

The main disadvantage for IVUS guidance of chronic total occlusion (CTO) interventions is the lateral view of IVUS probe. A prototype of forward-looking IVUS system was developed, but till now it has never been commercialized. IVUS can help during wire introduction to the proximal fibrous cap of CTO in presence of side branch just proximal to occluded segment. IVUS is introduced to this side branch and from this location the wire reaching the origin of total occlusion can be visualized (*figure 15*). IVUS also can help with re-introduction of wire from false lumen to the true lumen, but it is necessary to introduce the IVUS probe to the false lumen after its predilatation with small balloon108. This

routine angiography107.

**8. Complications 8.1 Dissections** 

**7.2 PCI of chronic total occlusion** 

be converted to a simple one with just stenting of MV.

technique unfortunately increases risk of vessel perforation.

Fig. 15. Schema of IVUS guidance during PCI of chronic total occlusion.

Dissections are tears in the plaque that are parallel to the vessel wall with blood flow in the false lumen and tend to occur at the junction of elements with different compliance (plaque and normal vessel wall, edges of stents) (*figure 16, 17*). Dissections can be described as proximal or distal to the lesion; epicardial or myocardial; and according to length, circumferential arc, depth, lumen compromise, bulkiness and mobility of the flap5. The major predictor of an unfavorable prognosis of dissection is a decreased blood flow in affected coronary artery. This situation must be solved immediately. IVUS can also detect dissections, which are not visible on angiography and it is questionable how many of them should be

### **7. Ivus guided pci in specific situation**

#### **7.1 PCI of bifurcation lesions**

PCI in bifurcation is a more challenging procedure with a risk of compromising flow in side branch (SB) and with higher rate of restenosis. The "classical" mechanisms of worsening flow in side branch were thought 101


Fig. 14. Bifurcation with diffuse impairment of side branch ostium.

Plaque in bifurcation is mainly localized in counter carina103. However, Medina et al.104 proved the presence of plaque also in carina. They found plaque in 32% of bifurcations and moreover, in 16% of bifurcations the plaque in the carina was larger than in counter carina area. Furthermore, authors showed, that the mechanism of ostial SB damage after stent implantation in the MV was always due to displacement of the carina and no cases of plaque shifting were found. Further interesting finding of this study is that plaque in the carina was greater in the bifurcations that had maximum stenosis located distal to the carina in the MV. Authors explain this finding by hypothesis of different flow velocity patterns in these lesions. Atheroprotective high shear stress can be transformed into an atero-prone low shear stress. Authors describe less damage of SB ostium after stenting of lesions with plaque at the carina. Plaque probably makes carina more resistant and does not allow carina shifting, which is now thought to be a dominant mechanism causing damage to the SB ostium when a stent is implanted into the MV.

Important contribution for planning of PCI in bifurcations is a study done by Costa et al105. They found that the part of MV just behind the origin of SB (so called "lower diamond" or "polygon of confluence") is more prone for small minimal stent area after dilatation of SB ostium, which is not reverted even after kissing balloon dilatation. Kang et al.106 published a study assessing the IVUS predictors for side branch compromise after single-stent crossover technique and found two predictors for post stenting FFR<0.8: MLA 2.4mm2 and PB > 51% in SB ostium.

PCI in bifurcation is a more challenging procedure with a risk of compromising flow in side branch (SB) and with higher rate of restenosis. The "classical" mechanisms of worsening



Plaque in bifurcation is mainly localized in counter carina103. However, Medina et al.104 proved the presence of plaque also in carina. They found plaque in 32% of bifurcations and moreover, in 16% of bifurcations the plaque in the carina was larger than in counter carina area. Furthermore, authors showed, that the mechanism of ostial SB damage after stent implantation in the MV was always due to displacement of the carina and no cases of plaque shifting were found. Further interesting finding of this study is that plaque in the carina was greater in the bifurcations that had maximum stenosis located distal to the carina in the MV. Authors explain this finding by hypothesis of different flow velocity patterns in these lesions. Atheroprotective high shear stress can be transformed into an atero-prone low shear stress. Authors describe less damage of SB ostium after stenting of lesions with plaque at the carina. Plaque probably makes carina more resistant and does not allow carina shifting, which is now thought to be a dominant mechanism causing damage to the SB

Important contribution for planning of PCI in bifurcations is a study done by Costa et al105. They found that the part of MV just behind the origin of SB (so called "lower diamond" or "polygon of confluence") is more prone for small minimal stent area after dilatation of SB ostium, which is not reverted even after kissing balloon dilatation. Kang et al.106 published a study assessing the IVUS predictors for side branch compromise after single-stent crossover technique and found two predictors for post stenting FFR<0.8: MLA 2.4mm2 and PB > 51%

**7. Ivus guided pci in specific situation** 

than presence of eccentric plaque102


Fig. 14. Bifurcation with diffuse impairment of side branch ostium.

ostium when a stent is implanted into the MV.

in SB ostium.

**7.1 PCI of bifurcation lesions** 

phenomenon)

flow in side branch were thought 101

Main role of IVUS guidance in bifurcation PCI is precise assessment of atherosclerotic burden of main vessel, carina, ostial part of side branch and the choice of the best strategy based on these findings. IVUS can improve the choice of ideal stent diameter, because bifurcation area is frequently affected by negative remodeling, which is not visible in routine angiography107.

IVUS should be used of most cases of uncertain atherosclerotic distribution in bifurcation lesions, because in case of favorable finding in SB ostium a planned complex procedure can be converted to a simple one with just stenting of MV.

#### **7.2 PCI of chronic total occlusion**

The main disadvantage for IVUS guidance of chronic total occlusion (CTO) interventions is the lateral view of IVUS probe. A prototype of forward-looking IVUS system was developed, but till now it has never been commercialized. IVUS can help during wire introduction to the proximal fibrous cap of CTO in presence of side branch just proximal to occluded segment. IVUS is introduced to this side branch and from this location the wire reaching the origin of total occlusion can be visualized (*figure 15*). IVUS also can help with re-introduction of wire from false lumen to the true lumen, but it is necessary to introduce the IVUS probe to the false lumen after its predilatation with small balloon108. This technique unfortunately increases risk of vessel perforation.

Fig. 15. Schema of IVUS guidance during PCI of chronic total occlusion.

#### **8. Complications**

#### **8.1 Dissections**

Dissections are tears in the plaque that are parallel to the vessel wall with blood flow in the false lumen and tend to occur at the junction of elements with different compliance (plaque and normal vessel wall, edges of stents) (*figure 16, 17*). Dissections can be described as proximal or distal to the lesion; epicardial or myocardial; and according to length, circumferential arc, depth, lumen compromise, bulkiness and mobility of the flap5. The major predictor of an unfavorable prognosis of dissection is a decreased blood flow in affected coronary artery. This situation must be solved immediately. IVUS can also detect dissections, which are not visible on angiography and it is questionable how many of them should be

IVUS Guided PCI 127

Fig. 18. Intramural haematoma. Bleeding to the media and adventicia is compromising

recognize an angiographic pseudo complication with normal IVUS finding5.

1. Based on IVUS criteria we can probably safely defer PCI

Based on studies focusing on IVUS guidance of stent implantation we can summarize:

2. Satisfactory IVUS finding after balloon dilatation has same results as a stenting with BMS 3. IVUS guidance decreases angiographic restenosis and consequently the revascularization

IVUS is a very useful tool for diagnosis of underlying processes causing a hazy appearance of lesions after PCI. The most common findings are large residual plaque burden, dissection and plaque protrusion. Rarely stent deformation or intramural hematoma can be found. Intimal wrinkling can occur when a vessel is straightened by a guidewire. It reverses when the wire is removed or when the stiff wire is exchanged for a soft one. A narrowing of the lumen with a straightening of a normal-looking intima, behind which is an echolucent zone can be seen in IVUS picture. Discontinuity of the EEM can be found, which is caused by simultaneously visualized both sides of fold in the artery. Finally, it is important to

lumen.

**8.3 Haziness** 

**9. Conclusions** 

and MACE rate

treated. Nishida et al.109 followed 124 patients with non-flow limiting dissection (65% of them were after stenting). They found that dissection can be let untreated if the residual lumen is more than 6 mm2 and lumen area is more than 40% of the EEM area. The edge dissections after stenting, which can be visualized only by IVUS and are not apparent during angiography, are not indicated for any intervention, because of good prognosis by spontaneous healing110.

Fig. 16. Dissection with tear reaching to the media.

Fig. 17. Complex dissection with IVUS probe in true lumen, one false lumen is located down to true lumen (♣) and another entry to the false lumen is located above the true lumen (∗).

#### **8.2 Intramural hematomas**

Intramural hematoma is a variant of a dissection. The angiographic appearance ranges from a dissection, thrombus, and abrupt closure to non-significant abnormality. The EEM expands outwards and the intima is pushed inwards and straightens to cause lumen compromise (figure 18). Blood accumulates in the space caused by the split in the media and becomes static and echogenic. The hematoma can propagate antegrade or retrograde, but tends to be stopped by branches or severely diseased parts of the vessel (particularly calcified plaques). In a study, which included more than 1000 patients with IVUS control after PCI, an intramural hematoma was found in 6.7 % with a high rate of clinical events5, 111.

treated. Nishida et al.109 followed 124 patients with non-flow limiting dissection (65% of them were after stenting). They found that dissection can be let untreated if the residual lumen is more than 6 mm2 and lumen area is more than 40% of the EEM area. The edge dissections after stenting, which can be visualized only by IVUS and are not apparent during angiography, are not indicated for any intervention, because of good prognosis by spontaneous healing110.

Fig. 17. Complex dissection with IVUS probe in true lumen, one false lumen is located down to true lumen (♣) and another entry to the false lumen is located above the true lumen (∗).

Intramural hematoma is a variant of a dissection. The angiographic appearance ranges from a dissection, thrombus, and abrupt closure to non-significant abnormality. The EEM expands outwards and the intima is pushed inwards and straightens to cause lumen compromise (figure 18). Blood accumulates in the space caused by the split in the media and becomes static and echogenic. The hematoma can propagate antegrade or retrograde, but tends to be stopped by branches or severely diseased parts of the vessel (particularly calcified plaques). In a study, which included more than 1000 patients with IVUS control after PCI, an intramural hematoma was found in 6.7 % with a high rate of clinical events5, 111.

Fig. 16. Dissection with tear reaching to the media.

**8.2 Intramural hematomas** 

Fig. 18. Intramural haematoma. Bleeding to the media and adventicia is compromising lumen.

#### **8.3 Haziness**

IVUS is a very useful tool for diagnosis of underlying processes causing a hazy appearance of lesions after PCI. The most common findings are large residual plaque burden, dissection and plaque protrusion. Rarely stent deformation or intramural hematoma can be found. Intimal wrinkling can occur when a vessel is straightened by a guidewire. It reverses when the wire is removed or when the stiff wire is exchanged for a soft one. A narrowing of the lumen with a straightening of a normal-looking intima, behind which is an echolucent zone can be seen in IVUS picture. Discontinuity of the EEM can be found, which is caused by simultaneously visualized both sides of fold in the artery. Finally, it is important to recognize an angiographic pseudo complication with normal IVUS finding5.

#### **9. Conclusions**

Based on studies focusing on IVUS guidance of stent implantation we can summarize:


IVUS Guided PCI 129

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[20] Ricciardi M, Meyers S, Choi K, et al. Angiographically silent left main disease detected

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Transluminal Coronary Angioplasty Was Not Performed Based on Intravascular

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This summary raises the question why IVUS is not used routinely during all PCI procedures. The answers can be divided into two groups. First there are the lessons we have learned from IVUS and this phenomenon is known as an "IVUS eye". We know that vessels are bigger than they look on angio and we are using bigger stents than before IVUS studies. We know, that without high pressure post dilatation we are not able to achieve sufficient stent diameter despite information derived from manufacturer's compliance charts. These factors dramatically contributed to lowering of in stent restenosis and therefore it is difficult to find statistical significant difference between IVUS and angio guided interventions, like it was described in OPTICUS trial. However, IVUS is still irreplaceable during investigation of unclear finding during angiography (like hazy lesions) or after stenting. IVUS is especially recommended during PCI of left main, the last remaining coronary artery and PCI in patients who are contraindicated for dual antiplatelet therapy for avoiding stent implantation. Furthermore, precise assessment of bifurcation can change the strategy from more complex to simple one in case of low risk profile of ostial part of side branch

The group of arguments against routine use of IVUS during PCI is cost of IVUS catheter, longer procedural time and higher contrast dye consumption. Moreover IVUS guided PCI are more complex and need more skills than angio guided ones. However, in indicated cases IVUS guidance undoubtedly improves short as well as long term of coronary interventions.

#### **10. References**


5. Contraindication for IVUS guidance are small vessels, tortuous vessels and degenerated

This summary raises the question why IVUS is not used routinely during all PCI procedures. The answers can be divided into two groups. First there are the lessons we have learned from IVUS and this phenomenon is known as an "IVUS eye". We know that vessels are bigger than they look on angio and we are using bigger stents than before IVUS studies. We know, that without high pressure post dilatation we are not able to achieve sufficient stent diameter despite information derived from manufacturer's compliance charts. These factors dramatically contributed to lowering of in stent restenosis and therefore it is difficult to find statistical significant difference between IVUS and angio guided interventions, like it was described in OPTICUS trial. However, IVUS is still irreplaceable during investigation of unclear finding during angiography (like hazy lesions) or after stenting. IVUS is especially recommended during PCI of left main, the last remaining coronary artery and PCI in patients who are contraindicated for dual antiplatelet therapy for avoiding stent implantation. Furthermore, precise assessment of bifurcation can change the strategy from

more complex to simple one in case of low risk profile of ostial part of side branch

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sirolimus-eluting VElocity balloon-expandable stent in the treatment of patients with de novo native coronary artery Lesions) trial. *Circulation*. 2002;106:798–803


**9** 

*Italy* 

**Oral Rapamycin to Reduce** 

Carmelo Cernigliaro, Mara Sansa, Federico Nardi and Eugenio Novelli

**Intimal Hyperplasia After Bare** 

*Department of Cardiology, Clinica San Gaudenzio Novara,* 

**Metal Stent Implantation - A Prospective** 

**Randomized Intravascular Ultrasound Study** 

Coronary artery disease is a major health problem throughout the world. Important advances in diagnosis and treatment of atherosclerotic disorders have been made over the last five decades. Coronary angiography, introduced by Mason Sones in 1958 has been very effective on expanding the diagnosis and treatment of coronary lesions. The introduction of conventional balloon percutaneous transluminal coronary angioplasty (PTCA) by Andreas Grüntzig in 1977, represented an innovative and quite efficient non surgical treatment of angina pectoris and acute myocardial infarction. This procedure was however frequently complicated by an abrupt vessel closure, coronary dissections and a high incidence of restenosis (up to 40 – 50 % of cases) (Grüntzig et al., 1979). In 1986 the first coronary Wallstent was implanted in Toulouse by Jacques Puel and Ulrich Sigwart (Sigwart et al., 1987) and in 1994 Palmaz-Schatz stents were approved by FDA in the United States. Coronary stents improved the immediate and long-term results of coronary angioplasty, reducing immediate complications of the procedure like coronary dissection and abrupt closure and the incidence of restenosis. However, despite technical advances in stent delivery systems and design the rate of restenosis after stent implantation remained 20-30% especially in the high risk patients subsets (Serruys et al., 1994; Fischman et al., 1994). To overcome the problem of restenosis the drug eluting stents Cypher and Taxus were approved in 2003 and 2004 respectively. The initial studies with these stents demonstrated a marked major advance in reducing restenosis (Bailey, 1997; Serruys et al., 2002). Later studies however confirmed that despite these advances, in the real world, stent thrombosis (acute, subacute and late) and instent restenosis still remain a great clinical challenge (Daemen et al., 2007). The process of restenosis is complex. Restenosis may ensue mainly because of: a) patients-related factors (diabetes, restenosis after PTCA, chronic renal insufficiency, high serum PCR etc), b) vessel factors (chronic occlusion, vessel involved e.g. LAD, SVG etc, vessel < 3.0mm diameter, lesion length > 30 mm, bifurcation lesion, ostial lesion), c) procedure factors (post-stent MLD < 3mm, multiple stents, stent underexpansion

**1. Introduction** 

or malapposition, stent fracture).


## **Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal Stent Implantation - A Prospective Randomized Intravascular Ultrasound Study**

Carmelo Cernigliaro, Mara Sansa, Federico Nardi and Eugenio Novelli *Department of Cardiology, Clinica San Gaudenzio Novara, Italy* 

#### **1. Introduction**

136 Intravascular Ultrasound

[107] Fujii K, Kobayashi Y, Mintz GS, et al. Dominant contribution of negative remodeling

[108] Ito S, Suzuki T, Ito T, Katoh O, Ojio S, Sato H, Ehara M, Suzuki T,Kawase Y, Myoishi

[109] Nishida T, Colombo A, Briguori C, et al. Outcome of nonobstructive residual

[110] Sheris SJ, Canos MP, Weissman NJ, et al. Natural history of intravascular ultrasound-

[111] Maehara A, Mintz GS, Bui AB, et al. Incidence, morphology, angiographic findings,

an intravascular ultrasound study. *Circulation* 2002;105:2037-2042

intervention. *Am J Cardiol* 2002;89:1257-1262

59-61

1088 –1092

to development of significant coronary bifurcation narrowing. *Am J Cardiol* 2003;92:

M, Kurokawa R, Ishihara Y, Suzuki Y, Sato K, Toyama S, Fukutomi T, Itoh M. Novel Technique Using Intravascular Ultrasound-Guided Guidewire Cross in Coronary Intervention for Uncrossable Chronic Total Occlusions. *Circ J* 2004; 68:

dissections detected by intravascular ultrasound following percutaneous coronary

detected edge dissections from coronary stent deployment. *Am Heart J* 2000;139:59-63

and outcomes of intramural hematomas after percutaneous coronary interventions:

Coronary artery disease is a major health problem throughout the world. Important advances in diagnosis and treatment of atherosclerotic disorders have been made over the last five decades. Coronary angiography, introduced by Mason Sones in 1958 has been very effective on expanding the diagnosis and treatment of coronary lesions. The introduction of conventional balloon percutaneous transluminal coronary angioplasty (PTCA) by Andreas Grüntzig in 1977, represented an innovative and quite efficient non surgical treatment of angina pectoris and acute myocardial infarction. This procedure was however frequently complicated by an abrupt vessel closure, coronary dissections and a high incidence of restenosis (up to 40 – 50 % of cases) (Grüntzig et al., 1979). In 1986 the first coronary Wallstent was implanted in Toulouse by Jacques Puel and Ulrich Sigwart (Sigwart et al., 1987) and in 1994 Palmaz-Schatz stents were approved by FDA in the United States. Coronary stents improved the immediate and long-term results of coronary angioplasty, reducing immediate complications of the procedure like coronary dissection and abrupt closure and the incidence of restenosis. However, despite technical advances in stent delivery systems and design the rate of restenosis after stent implantation remained 20-30% especially in the high risk patients subsets (Serruys et al., 1994; Fischman et al., 1994). To overcome the problem of restenosis the drug eluting stents Cypher and Taxus were approved in 2003 and 2004 respectively. The initial studies with these stents demonstrated a marked major advance in reducing restenosis (Bailey, 1997; Serruys et al., 2002). Later studies however confirmed that despite these advances, in the real world, stent thrombosis (acute, subacute and late) and instent restenosis still remain a great clinical challenge (Daemen et al., 2007). The process of restenosis is complex. Restenosis may ensue mainly because of: a) patients-related factors (diabetes, restenosis after PTCA, chronic renal insufficiency, high serum PCR etc), b) vessel factors (chronic occlusion, vessel involved e.g. LAD, SVG etc, vessel < 3.0mm diameter, lesion length > 30 mm, bifurcation lesion, ostial lesion), c) procedure factors (post-stent MLD < 3mm, multiple stents, stent underexpansion or malapposition, stent fracture).

Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal

periprocedural period of BMS or DES implantation is still needed.

eluting stents was implanted (Jennings & Kalus 2010).

albumin excretion in kidney disease is reduced.

with BMS as an alternative to DES (Fox et al., 2009).

one approach to the other (Torguson et al., 2006).

Stent Implantation - A Prospective Randomized Intravascular Ultrasound Study 139

lesion revascularization are still subjected to failure and restenosis. Interestingly, limited evidence directly comparing DES implantation to vascular brachytherapy (locally applied beta or gamma radiations) in patients with stent restenosis, has shown no direct benefit of

A systemic approach with oral antiproliferative agents like oral sirolimus or newer inhibitors of cytokines could more effectively reduce vascular smooth cell proliferation, migration and invasion process even at a distant site from the injured media (Kuchulakanti & Waksman, 2004). The oral approach has been so far reported in small size studies. The studies suggest that a course of 30 days of oral therapy is both safe an effective and that efficacy is tied to serum blood levels of the drug (Brara et al., 2003; Cernigliaro et al., 2010; Chaves et al., 2005; Fox et al., 2009; Gallo et al., 1999; Guarda et al., 2004; Hausleiter et al., 2004; Munk et al., 2009; Rodriguez et al., 2003; Rodriguez et al., 2005; Rodriguez et al., 2006; Rodriguez, 2009; Rodriguez et al., 2009; Jennings & Kalus 2010; Stojkovic et al., 2010; Waksman et al., 2004; Waksman et al., 2006). Future investigation into the efficacy of oral antiproliferative agents also during the

Recent studies have investigated adjunctive therapies that could potentially reduce stent restenosis. Addition of cilostazol to aspirin and a thienopyridine (triple antiplatelet therapy) demonstrated reduction of angiographic restenosis at 6 months follow-up over patients receiving dual antiplatelet therapy regardless of whether a bare metal stents or a drug-

Oral inhibitors of up-regulated chemokines for reduction of restenosis rates following implantation of BMS without increase in late thrombosis are being utilized in clinical trials. Chemokines have a crucial role in the initiation and progression of neointima formation by controlling the vascular remodelling in response to various noxious stimuli. It has been demonstrated that eliminating the MCP-1 gene or blocking MCP-1 signaling decreases neointimal hyperplasia after balloon and stent induced injury in several animal models. In addition, elevated circulating levels of MCP-1 are observed in patients with restenosis after coronary angioplasty. The induction of MPC-1 correlates with macrophages accumulation and there is strong evidence for an important role of MPC-1 in vascular smooth muscle cells (VSMC) proliferation and migration. One of these oral inhibitors have demonstrated anti-inflammatory activity in a number of experimental diseases, with no induction of systemic immunosuppression and no effect on arachidonic acid metabolism. In vitro it reduces rat vascular smooth muscular proliferation migration, and invasion processes. In a porcine model of in-stent restenosis the product inhibits in-stent neointimal restenosis. Treatment of rats at a dose of 200mg/Kg/day significantly reduces balloon injury-induced intima formation by 39% at day 14 without affecting re-endothelization and reduces the number of medial and neointimal proliferating cells at day 7 by 54% and 30%

respectively. A human Phase II trial of 120 patients receiving BMS is ongoing.

The toxicological profile of the drug is safe and patients with rheumatoid arthritis and lupus nephritis have shown that the product is well tolerated and that urinary MCP-1 and

The drug can be taken in combination with all the drugs taken by cardiological patients. It is administered b.i.d for 6 months after stent implantation and can be used in combination

Regular high intensity exercise training is associated with a significant reduction of late luminal loss following BMS or DES implantation. Patients enrolled into the high-intesitive training group also demonstrated a significantly lower cardiac event rate. The hypothesis surrounding

#### **2. Cellular mechanism of restenosis**

The restenosis process is a combination of inflammatory and reparative reaction at the site of stent implantation that may produce after weeks or months intimal hyperplasia or vascular remodelling.

In the porcine coronary after implantation of a metallic stent, restenotic neointima forms within one month and has a histopathologic appearance similar to human restenosis.

Three distinct stages in the genesis of neointima have been described: thrombosis, cellular recruitment, cellular proliferation.

Thrombosis: the earliest response to arterial injury is the formation of a thrombus, which is pale and platelet-rich microscopically. Erythrocytes and fibrin deposit on platelets and produce a heterogeneous microscopic appearance. By 24 hours the thrombus becomes denser as platelets and erythrocytes lyse and agglutinate. Platelet lysis results in discharge of granules and release of bioactive substances including platelet-derived growth factor (PDFG) (Ross et al., 1986; Williams, 1989).

Cellular recruitment: in this stage the thrombus itself becomes covered by the endothelium. Monocytes and lymphocytes are attracted by the flowing blood to the newly formed endothelial surface and pass through the endothelium into the degenerating fibrin thrombus. The monocytes become macrophages. Both macrophages and lymphocytes release a variety of growth factors and cytokines that are involved in smooth muscle cells migration and proliferation. Macrophages and lymphocytes also elaborate fibrinolytic enzymes. Over time these cells are found at deeper levels within the degenerated thrombus from the luminal (endothelium) direction toward the media of the artery.

Cellular proliferation: in the next stage cells form an intimal cap on the luminal side of the healing mass. The thickness of the cap is proportional to lesion age. Residual thrombus is gradually resorbed and replaced by neointima. An extracellular matrix consisting of collagen and glycosaminoglycans is present presumably secreted by vascular smooth muscle cells.

In early experiments, elimination of smooth muscle cells from media by intraluminal microwave heat energy applied in pig arteries after balloon injury was thought to prevent intimal hyperplasia because no cells would be available to migrate and proliferate. After one month however a large volume of neointima was observed at the burn sites where most of the cells had been killed as if migration of smooth muscle cells into the neointima may still occur from a distant uninjured medial site.

To summarize this interesting information, smooth muscle cells forming neointima do not necessarily originate at the site of medial injury. Endothelized and degenerating thrombus, colonized by monocytes and lymphocytes, provides a matrix where smooth muscle cells migrate and proliferate and synthetize extracellular matrix. The thrombus burden that accumulates at the arterial injury site determines the volume of eventual neointimal volume (Schwartz et al., 1992).

#### **3. Alternative therapies to prevent stent restenosis**

These data would favour a systemic approach with drugs that reduce intracoronary inflammation and neointimal proliferation also at sites distant from that injured by stent implantation. Stents that elute loco-regionally drugs such rapamycin or placlitaxel (DES), even if in multiple large randomized studies, demonstrate superiority over conventional bare metal stents (BMS) with regard to clinical endpoints such as target vessel or target

The restenosis process is a combination of inflammatory and reparative reaction at the site of stent implantation that may produce after weeks or months intimal hyperplasia or

In the porcine coronary after implantation of a metallic stent, restenotic neointima forms

Three distinct stages in the genesis of neointima have been described: thrombosis, cellular

Thrombosis: the earliest response to arterial injury is the formation of a thrombus, which is pale and platelet-rich microscopically. Erythrocytes and fibrin deposit on platelets and produce a heterogeneous microscopic appearance. By 24 hours the thrombus becomes denser as platelets and erythrocytes lyse and agglutinate. Platelet lysis results in discharge of granules and release of bioactive substances including platelet-derived growth factor

Cellular recruitment: in this stage the thrombus itself becomes covered by the endothelium. Monocytes and lymphocytes are attracted by the flowing blood to the newly formed endothelial surface and pass through the endothelium into the degenerating fibrin thrombus. The monocytes become macrophages. Both macrophages and lymphocytes release a variety of growth factors and cytokines that are involved in smooth muscle cells migration and proliferation. Macrophages and lymphocytes also elaborate fibrinolytic enzymes. Over time these cells are found at deeper levels within the degenerated thrombus

Cellular proliferation: in the next stage cells form an intimal cap on the luminal side of the healing mass. The thickness of the cap is proportional to lesion age. Residual thrombus is gradually resorbed and replaced by neointima. An extracellular matrix consisting of collagen and glycosaminoglycans is present presumably secreted by vascular smooth muscle cells. In early experiments, elimination of smooth muscle cells from media by intraluminal microwave heat energy applied in pig arteries after balloon injury was thought to prevent intimal hyperplasia because no cells would be available to migrate and proliferate. After one month however a large volume of neointima was observed at the burn sites where most of the cells had been killed as if migration of smooth muscle cells into the neointima may still

To summarize this interesting information, smooth muscle cells forming neointima do not necessarily originate at the site of medial injury. Endothelized and degenerating thrombus, colonized by monocytes and lymphocytes, provides a matrix where smooth muscle cells migrate and proliferate and synthetize extracellular matrix. The thrombus burden that accumulates at the arterial injury site determines the volume of eventual neointimal volume

These data would favour a systemic approach with drugs that reduce intracoronary inflammation and neointimal proliferation also at sites distant from that injured by stent implantation. Stents that elute loco-regionally drugs such rapamycin or placlitaxel (DES), even if in multiple large randomized studies, demonstrate superiority over conventional bare metal stents (BMS) with regard to clinical endpoints such as target vessel or target

from the luminal (endothelium) direction toward the media of the artery.

within one month and has a histopathologic appearance similar to human restenosis.

**2. Cellular mechanism of restenosis** 

vascular remodelling.

recruitment, cellular proliferation.

(PDFG) (Ross et al., 1986; Williams, 1989).

occur from a distant uninjured medial site.

**3. Alternative therapies to prevent stent restenosis** 

(Schwartz et al., 1992).

lesion revascularization are still subjected to failure and restenosis. Interestingly, limited evidence directly comparing DES implantation to vascular brachytherapy (locally applied beta or gamma radiations) in patients with stent restenosis, has shown no direct benefit of one approach to the other (Torguson et al., 2006).

A systemic approach with oral antiproliferative agents like oral sirolimus or newer inhibitors of cytokines could more effectively reduce vascular smooth cell proliferation, migration and invasion process even at a distant site from the injured media (Kuchulakanti & Waksman, 2004). The oral approach has been so far reported in small size studies. The studies suggest that a course of 30 days of oral therapy is both safe an effective and that efficacy is tied to serum blood levels of the drug (Brara et al., 2003; Cernigliaro et al., 2010; Chaves et al., 2005; Fox et al., 2009; Gallo et al., 1999; Guarda et al., 2004; Hausleiter et al., 2004; Munk et al., 2009; Rodriguez et al., 2003; Rodriguez et al., 2005; Rodriguez et al., 2006; Rodriguez, 2009; Rodriguez et al., 2009; Jennings & Kalus 2010; Stojkovic et al., 2010; Waksman et al., 2004; Waksman et al., 2006). Future investigation into the efficacy of oral antiproliferative agents also during the periprocedural period of BMS or DES implantation is still needed.

Recent studies have investigated adjunctive therapies that could potentially reduce stent restenosis. Addition of cilostazol to aspirin and a thienopyridine (triple antiplatelet therapy) demonstrated reduction of angiographic restenosis at 6 months follow-up over patients receiving dual antiplatelet therapy regardless of whether a bare metal stents or a drugeluting stents was implanted (Jennings & Kalus 2010).

Oral inhibitors of up-regulated chemokines for reduction of restenosis rates following implantation of BMS without increase in late thrombosis are being utilized in clinical trials.

Chemokines have a crucial role in the initiation and progression of neointima formation by controlling the vascular remodelling in response to various noxious stimuli. It has been demonstrated that eliminating the MCP-1 gene or blocking MCP-1 signaling decreases neointimal hyperplasia after balloon and stent induced injury in several animal models.

In addition, elevated circulating levels of MCP-1 are observed in patients with restenosis after coronary angioplasty. The induction of MPC-1 correlates with macrophages accumulation and there is strong evidence for an important role of MPC-1 in vascular smooth muscle cells (VSMC) proliferation and migration. One of these oral inhibitors have demonstrated anti-inflammatory activity in a number of experimental diseases, with no induction of systemic immunosuppression and no effect on arachidonic acid metabolism.

In vitro it reduces rat vascular smooth muscular proliferation migration, and invasion processes. In a porcine model of in-stent restenosis the product inhibits in-stent neointimal restenosis. Treatment of rats at a dose of 200mg/Kg/day significantly reduces balloon injury-induced intima formation by 39% at day 14 without affecting re-endothelization and reduces the number of medial and neointimal proliferating cells at day 7 by 54% and 30% respectively. A human Phase II trial of 120 patients receiving BMS is ongoing.

The toxicological profile of the drug is safe and patients with rheumatoid arthritis and lupus nephritis have shown that the product is well tolerated and that urinary MCP-1 and albumin excretion in kidney disease is reduced.

The drug can be taken in combination with all the drugs taken by cardiological patients. It is administered b.i.d for 6 months after stent implantation and can be used in combination with BMS as an alternative to DES (Fox et al., 2009).

Regular high intensity exercise training is associated with a significant reduction of late luminal loss following BMS or DES implantation. Patients enrolled into the high-intesitive training group also demonstrated a significantly lower cardiac event rate. The hypothesis surrounding

Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal

Stent Implantation - A Prospective Randomized Intravascular Ultrasound Study 141

Fig. 1b) Longitudinal display during monitorized pullback of the same artery

after intervention (Figure 2a, Figure 2b, Figure 2c, Figure 2d).

DES showing proximal intrastent hyperplasia

Both non invasive and invasive methods have been proposed to aid in visualizing vessel morphology. Noninvasive alternatives to IVUS may include magnetic resonance imaging (MRI), computed tomography (CT) and Doppler ultrasound. Studies support IVUS as the "gold" reference standard when planning, guiding and assessing percutaneous coronary interventions. Multislice CT has moderate to good sensitivities and specificities for the visualization of coronary plaques compared with IVUS as the reference standard. Quantitative 64-channel CT angiography obtained with an effective radiation dose to patients in the range of 3 mSv, can obtain reliable measures in multiple views of reference diameter, minimum lumen diameter, and percent stenosis of coronary arteries before and

Fig. 2a) Coronary angiography of a Left Anterior Descending Artery with two overlapped

the potential benefit of a high intensity exercise training is that such activity may be beneficial in minimizing endothelial dysfunction after stent implantation (Munk et al., 2009).

#### **4. Current imaging modalities**

Coronary angiography objectively assess the long-term outcome after stent implantation. It provides a silhouette of the intravascular space of coronary arteries. Many important features of the lesion that could influence intimal hyperplasia development after intervention may however not be identifiable with coronary arteriography alone.

Angioscopy is an invasive technique that allows an operator to visualize directly the interior of the vessel that can be seen through the fiberoptic eyepiece, or, using electronic chip camera technology. This allows improved understanding of the pathophysiology of coronary arteries. It identifies the presence of morphological features like thrombus or mural haemorrhage and disrupted atheromas that protrude into lumen. Such disruptions may appear angiographically as luminal haziness.

Grayscale intravascular ultrasonography (IVUS) is an invasive, catheter-based imaging procedure that uses sound waves to see inside the vessels within the body. IVUS is most commonly performed in conjunction with conventional coronary angiography for evaluating vessel pathology, atherosclerotic burden, and lesion severity. As compared with angiography, IVUS can provide more detail of the vessel architecture, including the crosssectional composition of the lumen and wall and the presence and composition of plaque. Atheroma can be interrogated thouroughly to reveal the nature of the lesion (e.g. soft with high lipid content or fibrotic and calcified). Although IVUS is an invasive imaging modality, reports of major clinical complications are rare despite increasing clinical use. When performed by experienced operators, most major and acute procedural complications associated with IVUS imaging occur during interventional cases. The most frequently encountered complication is coronary spasm, which occurs in approximately 2–3% of patients during interventional and diagnostic procedures and usually responds rapidly to the administration of intracoronary nitroglycerin (Figure 1a, Figure 1b).

Fig. 1a) Cross sectional IVUS image of a coronary artery with colour coding delineating the lumen (red) the external elastic membrane (green) and the atherosclerotic burden of the media

the potential benefit of a high intensity exercise training is that such activity may be beneficial in

Coronary angiography objectively assess the long-term outcome after stent implantation. It provides a silhouette of the intravascular space of coronary arteries. Many important features of the lesion that could influence intimal hyperplasia development after

Angioscopy is an invasive technique that allows an operator to visualize directly the interior of the vessel that can be seen through the fiberoptic eyepiece, or, using electronic chip camera technology. This allows improved understanding of the pathophysiology of coronary arteries. It identifies the presence of morphological features like thrombus or mural haemorrhage and disrupted atheromas that protrude into lumen. Such disruptions

Grayscale intravascular ultrasonography (IVUS) is an invasive, catheter-based imaging procedure that uses sound waves to see inside the vessels within the body. IVUS is most commonly performed in conjunction with conventional coronary angiography for evaluating vessel pathology, atherosclerotic burden, and lesion severity. As compared with angiography, IVUS can provide more detail of the vessel architecture, including the crosssectional composition of the lumen and wall and the presence and composition of plaque. Atheroma can be interrogated thouroughly to reveal the nature of the lesion (e.g. soft with high lipid content or fibrotic and calcified). Although IVUS is an invasive imaging modality, reports of major clinical complications are rare despite increasing clinical use. When performed by experienced operators, most major and acute procedural complications associated with IVUS imaging occur during interventional cases. The most frequently encountered complication is coronary spasm, which occurs in approximately 2–3% of patients during interventional and diagnostic procedures and usually responds rapidly to

Fig. 1a) Cross sectional IVUS image of a coronary artery with colour coding delineating the lumen (red) the external elastic membrane (green) and the atherosclerotic burden of the

minimizing endothelial dysfunction after stent implantation (Munk et al., 2009).

intervention may however not be identifiable with coronary arteriography alone.

the administration of intracoronary nitroglycerin (Figure 1a, Figure 1b).

**4. Current imaging modalities** 

media

may appear angiographically as luminal haziness.

Fig. 1b) Longitudinal display during monitorized pullback of the same artery

Both non invasive and invasive methods have been proposed to aid in visualizing vessel morphology. Noninvasive alternatives to IVUS may include magnetic resonance imaging (MRI), computed tomography (CT) and Doppler ultrasound. Studies support IVUS as the "gold" reference standard when planning, guiding and assessing percutaneous coronary interventions. Multislice CT has moderate to good sensitivities and specificities for the visualization of coronary plaques compared with IVUS as the reference standard. Quantitative 64-channel CT angiography obtained with an effective radiation dose to patients in the range of 3 mSv, can obtain reliable measures in multiple views of reference diameter, minimum lumen diameter, and percent stenosis of coronary arteries before and after intervention (Figure 2a, Figure 2b, Figure 2c, Figure 2d).

Fig. 2a) Coronary angiography of a Left Anterior Descending Artery with two overlapped DES showing proximal intrastent hyperplasia

Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal

Stent Implantation - A Prospective Randomized Intravascular Ultrasound Study 143

Fig. 2d) 64-CT angiography of the same LAD artery. Intimal hyperplasia encroaches the

Novel invasive imaging technologies include optical coherence tomography (OCT), which measures the intensity of back-reflected light in a similar way to that by which IVUS measures acoustic waves; intracoronary thermography; and spectroscopy (reflected light is

Virtual Histology (OCT) analyzes radiofrequency ultrasound signals and provides real-time maps by classifying atherosclerotic plaque into tissue types of fibrous, fibro-fatty, dense calcium, and necrotic-core. VH IVUS is intended to be used in conjunction with imaging catheters during diagnostic ultrasound imaging of the peripheral and coronary vasculature to semi-automatically visualize boundary features and perform spectral analysis of radiofrequency ultrasound signals of vascular features that the user may wish to examine

Coronary arteries architecture consists of an external layer the adventitia, the outer covering of the artery the media, the actual wall of the artery the intima, a layer of endothelial cells that make direct contact with the blood and the lumen. The intima in normal arteries is thin; in diseased arteries is thickened by plaques or other tissue growth often eccentric or asymmetrical. The term intimal hyperplasia applies to any cells that form a multi-layer compartment internally to the elastic membrane of the arterial wall. Standard coronary angiography shows the lumen of the artery and lumen narrowings when present by the injection of contrast dye as well as a dynamic picture of the blood flow. If the intima is thickened by plaques or other tissue growth that are not evenly distributed, coronary angiography will show an eccentric lumen and depending on the angle of the view the artery could show less or more stenosis than it really is. The intima layer is best visualized by the intravascular ultrasound (IVUS) that allows a vision of the coronary artery from the inside-out. The cross-section view obtained by IVUS shows the single circular layers of the artery using shades of gray or colors in real time. In a normal artery the intima will appear thin, in a diseased artery the intima is thickened by plaques as the lumen diameter is reduced. Low-dose quantitative 64-channel CT angiography can be a reasonable alternative

to invasive IVUS to evaluate the extent of intimal hyperplasia (Figure 3a, Figure 3b).

stent struts as islets of tissue imaged as intraluminal black spots by the struts

more closely during routine diagnostic ultrasound imaging examinations.

collected and launched into a spectrometer.)

**5. Intimal hyperplasia imaging** 

Fig. 2b) Cross sectional IVUS image of the same LAD artery with intrastent intimal hyperplasia

Fig. 2c) Longitudinal IVUS image of the same LAD artery: intimal hyperplasia encroaches the stent (yellow line)

Fig. 2b) Cross sectional IVUS image of the same LAD artery with intrastent intimal hyperplasia

Fig. 2c) Longitudinal IVUS image of the same LAD artery: intimal hyperplasia encroaches

the stent (yellow line)

Fig. 2d) 64-CT angiography of the same LAD artery. Intimal hyperplasia encroaches the stent struts as islets of tissue imaged as intraluminal black spots by the struts

Novel invasive imaging technologies include optical coherence tomography (OCT), which measures the intensity of back-reflected light in a similar way to that by which IVUS measures acoustic waves; intracoronary thermography; and spectroscopy (reflected light is collected and launched into a spectrometer.)

Virtual Histology (OCT) analyzes radiofrequency ultrasound signals and provides real-time maps by classifying atherosclerotic plaque into tissue types of fibrous, fibro-fatty, dense calcium, and necrotic-core. VH IVUS is intended to be used in conjunction with imaging catheters during diagnostic ultrasound imaging of the peripheral and coronary vasculature to semi-automatically visualize boundary features and perform spectral analysis of radiofrequency ultrasound signals of vascular features that the user may wish to examine more closely during routine diagnostic ultrasound imaging examinations.

#### **5. Intimal hyperplasia imaging**

Coronary arteries architecture consists of an external layer the adventitia, the outer covering of the artery the media, the actual wall of the artery the intima, a layer of endothelial cells that make direct contact with the blood and the lumen. The intima in normal arteries is thin; in diseased arteries is thickened by plaques or other tissue growth often eccentric or asymmetrical. The term intimal hyperplasia applies to any cells that form a multi-layer compartment internally to the elastic membrane of the arterial wall. Standard coronary angiography shows the lumen of the artery and lumen narrowings when present by the injection of contrast dye as well as a dynamic picture of the blood flow. If the intima is thickened by plaques or other tissue growth that are not evenly distributed, coronary angiography will show an eccentric lumen and depending on the angle of the view the artery could show less or more stenosis than it really is. The intima layer is best visualized by the intravascular ultrasound (IVUS) that allows a vision of the coronary artery from the inside-out. The cross-section view obtained by IVUS shows the single circular layers of the artery using shades of gray or colors in real time. In a normal artery the intima will appear thin, in a diseased artery the intima is thickened by plaques as the lumen diameter is reduced. Low-dose quantitative 64-channel CT angiography can be a reasonable alternative to invasive IVUS to evaluate the extent of intimal hyperplasia (Figure 3a, Figure 3b).

Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal

**6.2 Intravascular ultrasound analysis** 

videotapes for off-line quantitative analysis.

Ultrasound. Volume data was then calculated as

Research, Milan, Italy) blinded to the patients' treatment.

**6.3 Study endpoints and definitions** 

by dividing IH volume by stent volume.

>50%) at 6-month angiographic follow-up.

**6.4 Statistical analysis** 

distributed variables.

analyzed slices.

Stent Implantation - A Prospective Randomized Intravascular Ultrasound Study 145

at follow-up angiography was the primary study endpoint. Restenosis was significantly

Image acquisition was performed in all cases with a 2.6F 40 MHz Atlantis (Boston Scientific, Natick, Ma) mechanical intravascular ultrasound (IVUS) catheter, interfaced to an Insight III ultrasound consolle (Cardio Vascular Imaging Systems, Boston Scientific, Natick, Ma). The guidewire was threaded through a short monorail close to the probe. The imaging catheter was then advanced beyond the stented segment, as far as possible, after intracoronary injection of 200µg nitroglycerin and after administration of heparin 5000 IU. Motorized transducer pullbacks were performed at a speed of 0.5 mm/sec and recorded on S-VHS

Videotaped recordings of IVUS pullbacks were digitalized by using Echo-CMS (Medis, The Netherlands), a Windows-based 3D image acquisition software. The IVUS pullback and frame-grabbing rates were constant, and each segment obtained thus represented a 200µmthick slice. We used QCU-CMS (Medis, The Netherlands), a contour detection program for automated 2D and 3D IVUS analysis of the digitalized segment. Two-dimensional parameters were measured in all slices of the stented segment, and proximal and distal reference segments, according to the ACC Consensus Document for Intravascular

(lumen, stent or vessel), *A* area in each slice, *H* slice thickness, and *n* number of

All IVUS analyses were performed by an independent core lab (Mediolanum Cardio

Intravascular ultrasound end-points were the volume of neointimal hyperplasia, minimum residual stent area and percentage in-stent volume obstruction, obtained after IVUS analysis

The primary end-point was the rate of binary restenosis (percentage diameter stenosis

Additional end-points were the 18-month rates of target vessel failure: death, myocardial infarction (new onset of Q waves on a 12-lead ECG, or CK enzyme elevation > 2 upper limit of normality, with CK-MB fraction >5%), and repeat target vessel revascularization, including coronary artery bypass graft surgery and percutaneous coronary intervention. Intravascular ultrasound end-points were the volume of neointimal hyperplasia, minimum residual stent area, and percentage in-stent volume obstruction, obtained after IVUS

All analyses were performed on an intention-to-treat basis**.** Kolmogorov-Smirnov test was used to assess variables normality. Normally distributed variables were compared by Student's T-test, whereas the Mann-Whitney U-test was utilized for not normally

analysis by dividing IH volume by stent volume (Figure 4a and Figure 4b).

1

, in which*<sup>V</sup>* volume

*n i i V AH* 

reduced from 36.8% in the Placebo group to 14.3% in the Rapamycin group (p=0.003).

Fig. 3a) 64-CT angiography of a BMS stented Obtuse Margin artery. Intimal hyperplasia is represented as less dense islets of tissue imaged as intraluminal black spots by the struts

Fig. 3b) 64-CT angiography of the same Obtuse Margin artery in a cross sectional and a longitudinal (right) view

#### **6. The intravascular ultrasound study of oral rapamycin to reduce restenosis after bare metal stent implantation**

The aim of our study was to verify if rapamycin, an antiproliferative and antiflammatory drug given orally at a dosage of 2 mg/day for one month was capable to reduce intimal hyperplasia in bare metal stents at 6-month after implantation. Intima hyperplasia in the stented segment of the coronary artery was detected and measured using the intravascular ultrasound technique.

#### **6.1 Methods and results**

In this placebo-controlled randomized study, 108 consecutive patients (164 lesions) were enrolled in two groups: oral Rapamycin (54 patients, 83 lesions; 4 mg loading dose on the day of the procedure followed by 2 mg daily for 30 days) and Placebo (54 patients, 81 lesions; 2 mg daily of sodium bicarbonate for 30 days). The angiographic in-segment binary restenosis rate at follow-up angiography was the primary study endpoint. Restenosis was significantly reduced from 36.8% in the Placebo group to 14.3% in the Rapamycin group (p=0.003).

#### **6.2 Intravascular ultrasound analysis**

144 Intravascular Ultrasound

Fig. 3a) 64-CT angiography of a BMS stented Obtuse Margin artery. Intimal hyperplasia is represented as less dense islets of tissue imaged as intraluminal black spots by the struts

Fig. 3b) 64-CT angiography of the same Obtuse Margin artery in a cross sectional and a

**6. The intravascular ultrasound study of oral rapamycin to reduce restenosis** 

The aim of our study was to verify if rapamycin, an antiproliferative and antiflammatory drug given orally at a dosage of 2 mg/day for one month was capable to reduce intimal hyperplasia in bare metal stents at 6-month after implantation. Intima hyperplasia in the stented segment of the coronary artery was detected and measured using the intravascular

In this placebo-controlled randomized study, 108 consecutive patients (164 lesions) were enrolled in two groups: oral Rapamycin (54 patients, 83 lesions; 4 mg loading dose on the day of the procedure followed by 2 mg daily for 30 days) and Placebo (54 patients, 81 lesions; 2 mg daily of sodium bicarbonate for 30 days). The angiographic in-segment binary restenosis rate

longitudinal (right) view

ultrasound technique.

**6.1 Methods and results** 

**after bare metal stent implantation** 

Image acquisition was performed in all cases with a 2.6F 40 MHz Atlantis (Boston Scientific, Natick, Ma) mechanical intravascular ultrasound (IVUS) catheter, interfaced to an Insight III ultrasound consolle (Cardio Vascular Imaging Systems, Boston Scientific, Natick, Ma). The guidewire was threaded through a short monorail close to the probe. The imaging catheter was then advanced beyond the stented segment, as far as possible, after intracoronary injection of 200µg nitroglycerin and after administration of heparin 5000 IU. Motorized transducer pullbacks were performed at a speed of 0.5 mm/sec and recorded on S-VHS videotapes for off-line quantitative analysis.

Videotaped recordings of IVUS pullbacks were digitalized by using Echo-CMS (Medis, The Netherlands), a Windows-based 3D image acquisition software. The IVUS pullback and frame-grabbing rates were constant, and each segment obtained thus represented a 200µmthick slice. We used QCU-CMS (Medis, The Netherlands), a contour detection program for automated 2D and 3D IVUS analysis of the digitalized segment. Two-dimensional parameters were measured in all slices of the stented segment, and proximal and distal reference segments, according to the ACC Consensus Document for Intravascular

#### Ultrasound. Volume data was then calculated as 1 *n i i V AH* , in which*<sup>V</sup>* volume

(lumen, stent or vessel), *A* area in each slice, *H* slice thickness, and *n* number of analyzed slices.

All IVUS analyses were performed by an independent core lab (Mediolanum Cardio Research, Milan, Italy) blinded to the patients' treatment.

#### **6.3 Study endpoints and definitions**

Intravascular ultrasound end-points were the volume of neointimal hyperplasia, minimum residual stent area and percentage in-stent volume obstruction, obtained after IVUS analysis by dividing IH volume by stent volume.

The primary end-point was the rate of binary restenosis (percentage diameter stenosis >50%) at 6-month angiographic follow-up.

Additional end-points were the 18-month rates of target vessel failure: death, myocardial infarction (new onset of Q waves on a 12-lead ECG, or CK enzyme elevation > 2 upper limit of normality, with CK-MB fraction >5%), and repeat target vessel revascularization, including coronary artery bypass graft surgery and percutaneous coronary intervention. Intravascular ultrasound end-points were the volume of neointimal hyperplasia, minimum residual stent area, and percentage in-stent volume obstruction, obtained after IVUS analysis by dividing IH volume by stent volume (Figure 4a and Figure 4b).

#### **6.4 Statistical analysis**

All analyses were performed on an intention-to-treat basis**.** Kolmogorov-Smirnov test was used to assess variables normality. Normally distributed variables were compared by Student's T-test, whereas the Mann-Whitney U-test was utilized for not normally distributed variables.

Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal

Table 1. Results for the IVUS analysis at 6-month follow-up.

CSA: cross-sectional area.

**6.6 Discussion** 

restenosis rate.

**6.7 Conclusion** 

Stent Implantation - A Prospective Randomized Intravascular Ultrasound Study 147

in-stent restenosis was significantly higher in patients with rapamycin blood concentration < 5

Mean Vessel CSA (mm2) 18.70 ± 5.71 16.18 ± 4.32 0.043 Mean Stent CSA (mm2) 8.93 ± 3.13 7.27 ± 2.35 0.007 Minimum Stent CSA (mm2) 7.59 ± 2.94 6.20 ± 1.94 0.033 Stent Length (mm) 15.2 ± 7.58 14.5 ± 5.38 ns Stent Volume (mm3) 139.2 ± 83.1 111.1 ± 62.9 ns Minimum Lumen CSA (mm2) 4.76 ± 2.84 3.68 ± 1.79 0.031 Intimal Hyperplasia Volume (mm3) 28.04 ± 24.9 33.46 ± 32.4 ns % Volume Obstruction 18.06 ± 10.7 27.06 ± 15.7 0.008

There were no serious adverse events during the 18-month period of follow-up. Significant changes in the serum creatinine, cholesterol, triglyceride as well as red and white blood cell counts, fibrinogen, ESR, hepatic enzymes at 15, 30 days and 6 month were not observed. Two patients, one in the Rapamycin group and one in the placebo group, respectively 2 weeks and 3 weeks after treatment, stopped the medication because of severe heartburn.

Purpose of our study was to evaluate the anti-restenotic properties of orally administered Rapamycin after bare metal stent placement, assessed by quantitative angiography and intravascular ultrasound analysis performed at 6 month follow-up angiography, and by assessing the clinical event rates at 5-year follow-up. This study demonstrates that oral administration of Rapamycin at the doses tested results in statistically significant inhibition of neo-intimal hyperplasia, with a reduction in binary restenosis from 36.8% to 14.3% at 6 month follow-up. Percentage volume obstruction at follow-up IVUS was reduced from 27% in the Placebo Group to 18% in the Rapamycin Group. This was associated with a reduction in target vessel failure at 18-month clinical follow-up respectively from 38.8% to 24.1%. Rapamycin is a macrolide analogue that binds to and inhibits mTOR (mammalian Target of Rapamycin), which is a kinase ultimately involved in the phosphorilation of the 40S ribosomal subunit. By inhibiting mTOR, Rapamycin halts cell proliferation by blocking the cell cycle in the G1/S phase. Experimental studies have shown that Rapamycin inhibits vascular smooth muscle cell proliferation, migration, and differentiation, thus leading to an inhibition of intrastent neointimal hyperplasia proliferation, and consequently a reduced

Our study shows that oral adminstration of Rapamycin at the doses tested results in an inhibition of neointimal hyperplasia at 6-month angiographic and IVUS follow-up, after

Rapamycin (n=48 lesions)

Placebo (n=45 lesions) *<sup>p</sup>*

ng/ml than in patients with > 5 ng/ml rapamycin (33.3% vs. 7.7%, p=0.044).

Fig. 4a) Cross sectional IVUS image of a coronary artery of a patient 6 month after BMS implantation and rapamicyn medication: no visible intimal hyperplasia across the stent struts

Fig. 4b) Cross sectional IVUS image of a coronary artery of a patient 6 month after BMS implantation and placebo medication: abundant intimal hyperplasia encroaches the stent struts

Discrete baseline characteristics were compared with the use of the chi-square test, Yates corrected when necessary. Statistical significance was accepted for a value of p<0.05. Data analysis were performed by SPSS statistical software (version 12.0; SPSS Inc, Chicago, IL).

#### **6.5 Results**

Intravascular ultrasound analysis was performed in a total of 93 lesions, 48 in the Rapamycin group and 45 lesions in the Placebo group. The two groups were similar with regard to all baseline clinical and angiographic characteristics. IVUS was attempted but not performed due to inability to advance the catheter across the restenotic lesion in 6 cases (11.1%) in the Rapamycin group and 4 cases (8.2%) in the Placebo group (p=ns). The results for the IVUS analysis at 6-month follow-up are summarized in Table 1.

Serum Rapamycin dosage was performed in a total of 53 patients. Serum Rapamycin levels > 5 ng/ml have been reported to be associated to a lower rate of restenosis. In our series, binary


in-stent restenosis was significantly higher in patients with rapamycin blood concentration < 5 ng/ml than in patients with > 5 ng/ml rapamycin (33.3% vs. 7.7%, p=0.044).

CSA: cross-sectional area.

146 Intravascular Ultrasound

Fig. 4a) Cross sectional IVUS image of a coronary artery of a patient 6 month after BMS implantation and rapamicyn medication: no visible intimal hyperplasia across the stent struts

Fig. 4b) Cross sectional IVUS image of a coronary artery of a patient 6 month after BMS implantation and placebo medication: abundant intimal hyperplasia encroaches the stent

Discrete baseline characteristics were compared with the use of the chi-square test, Yates corrected when necessary. Statistical significance was accepted for a value of p<0.05. Data analysis were performed by SPSS statistical software (version 12.0; SPSS Inc, Chicago, IL).

Intravascular ultrasound analysis was performed in a total of 93 lesions, 48 in the Rapamycin group and 45 lesions in the Placebo group. The two groups were similar with regard to all baseline clinical and angiographic characteristics. IVUS was attempted but not performed due to inability to advance the catheter across the restenotic lesion in 6 cases (11.1%) in the Rapamycin group and 4 cases (8.2%) in the Placebo group (p=ns). The results

Serum Rapamycin dosage was performed in a total of 53 patients. Serum Rapamycin levels > 5 ng/ml have been reported to be associated to a lower rate of restenosis. In our series, binary

for the IVUS analysis at 6-month follow-up are summarized in Table 1.

struts

**6.5 Results** 

Table 1. Results for the IVUS analysis at 6-month follow-up.

There were no serious adverse events during the 18-month period of follow-up. Significant changes in the serum creatinine, cholesterol, triglyceride as well as red and white blood cell counts, fibrinogen, ESR, hepatic enzymes at 15, 30 days and 6 month were not observed. Two patients, one in the Rapamycin group and one in the placebo group, respectively 2 weeks and 3 weeks after treatment, stopped the medication because of severe heartburn.

#### **6.6 Discussion**

Purpose of our study was to evaluate the anti-restenotic properties of orally administered Rapamycin after bare metal stent placement, assessed by quantitative angiography and intravascular ultrasound analysis performed at 6 month follow-up angiography, and by assessing the clinical event rates at 5-year follow-up. This study demonstrates that oral administration of Rapamycin at the doses tested results in statistically significant inhibition of neo-intimal hyperplasia, with a reduction in binary restenosis from 36.8% to 14.3% at 6 month follow-up. Percentage volume obstruction at follow-up IVUS was reduced from 27% in the Placebo Group to 18% in the Rapamycin Group. This was associated with a reduction in target vessel failure at 18-month clinical follow-up respectively from 38.8% to 24.1%.

Rapamycin is a macrolide analogue that binds to and inhibits mTOR (mammalian Target of Rapamycin), which is a kinase ultimately involved in the phosphorilation of the 40S ribosomal subunit. By inhibiting mTOR, Rapamycin halts cell proliferation by blocking the cell cycle in the G1/S phase. Experimental studies have shown that Rapamycin inhibits vascular smooth muscle cell proliferation, migration, and differentiation, thus leading to an inhibition of intrastent neointimal hyperplasia proliferation, and consequently a reduced restenosis rate.

#### **6.7 Conclusion**

Our study shows that oral adminstration of Rapamycin at the doses tested results in an inhibition of neointimal hyperplasia at 6-month angiographic and IVUS follow-up, after

Oral Rapamycin to Reduce Intimal Hyperplasia After Bare Metal

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coronary stent placement for de novo native coronary artery lesions. This leads to a reduction in angiographic restenosis, and clinical events, mainly target lesion revascularization, which persists at 5-year follow-up. The degree of inhibition of NIH achieved by orally administered Rapamycin appears inferior to that achieved by locally delivered Rapamycin from drug-eluting stents. An optimization of the dosage regimen is still necessary. However, oral administration of Rapamycin associated to bare metal stent implantation could be a competitive strategy even in the drug-eluting stent era. Randomized clinical trials comparing these strategies are warranted. Another possible direction is combination therapy between orally administered Rapamycin and drug-eluting stents in patient or lesion subsets at particularly high risk of restenosis.

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**Effects of Thiazolidinediones on In-Stent** 

Patients with metabolic syndrome or type 2 diabetes are at high risk of in-stent-restenosis, although drug-eluting stents reduce the in-stent restenosis rate and target lesion revascularization rate to less than half compared with bare metal stents.(Mintz GS, et al. J Am Coll Cardiol 2006) Most clinical trials of systemic pharmacotherapies with ACE inhibitors, statins and antiplatelet agents to reduce restenosis have yielded disappointing results. Proliferation of vascular smooth muscle cells is the predominant mechanism of neointimal hyperplasia leading to restenosis. Insulin resistance is a major factor in metabolic syndrome and type 2 diabetes, and has been demonstrated to represent an independent risk factor for in-stent-restenosis.(Piatti P, et al. Circulation 2003) Thiazolidinediones are insulinsensitizing agents, and reportedly inhibit proliferation of vascular smooth muscle cells in vitro and in animal studies. Recent studies, including our own, (Katayama et al. Am Heart J 2007; Takagi et al. J Am Coll Cardiol Intv 2009) have highlighted the beneficial effects of thiazolidinediones in reducing neointimal growth after stent implantation. We review herein IVUS studies regarding the effects of thiazolidinedione therapy on in-stent restenosis

Thiazolidinediones activate peroxisome proliferator-activated receptor (PPAR)- in adipose tissue, improving insulin sensitivity and glucose control in patients with type 2 diabetes mellitus and metabolic syndrome. The first thiazolidinedione described, troglitazone, was removed from the market because of hepatotoxic effects. Two glitazones, pioglitazone (Actos; Takeda/Lilly,) and rosiglitazone (Avandia; GlaxoSmithKline) are now commercially available for treatment of diabetes mellitus. Glitazones have been shown to improve specific lipid abnormalities associated with insulin resistance. Treatment with glitazones elevates serum levels of high-density lipoprotein (HDL) cholesterol, decreases triglyceride levels, and changes the size of low-density lipoprotein (LDL) cholesterol from small particles to large ones, less atherogenic particles. (Hanefeld M, et al. Diabetes Care 2004) Beyond the anti-diabetic activity, thiazolidinediones inhibit inflammatory activity, and migration and

**1. Introduction** 

after coronary stent implantation.

**2. Effects of thiazolidinedione beyond anti-diabetic actions** 

**Restenosis: A Review of IVUS Studies** 

Takuji Katayama2 and Masanobu Kawakami2 *1University of the Ryukyus, Graduate School of Medicine, 2Saitama Medical Center, Jichi Medical University,* 

Takanori Yasu1, Hiroto Ueba2,


## **Effects of Thiazolidinediones on In-Stent Restenosis: A Review of IVUS Studies**

Takanori Yasu1, Hiroto Ueba2,

Takuji Katayama2 and Masanobu Kawakami2 *1University of the Ryukyus, Graduate School of Medicine, 2Saitama Medical Center, Jichi Medical University, Japan* 

#### **1. Introduction**

150 Intravascular Ultrasound

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Optimal dosing and duration of oral everolimus to inhibit in-stent neointimal

Patients with metabolic syndrome or type 2 diabetes are at high risk of in-stent-restenosis, although drug-eluting stents reduce the in-stent restenosis rate and target lesion revascularization rate to less than half compared with bare metal stents.(Mintz GS, et al. J Am Coll Cardiol 2006) Most clinical trials of systemic pharmacotherapies with ACE inhibitors, statins and antiplatelet agents to reduce restenosis have yielded disappointing results. Proliferation of vascular smooth muscle cells is the predominant mechanism of neointimal hyperplasia leading to restenosis. Insulin resistance is a major factor in metabolic syndrome and type 2 diabetes, and has been demonstrated to represent an independent risk factor for in-stent-restenosis.(Piatti P, et al. Circulation 2003) Thiazolidinediones are insulinsensitizing agents, and reportedly inhibit proliferation of vascular smooth muscle cells in vitro and in animal studies. Recent studies, including our own, (Katayama et al. Am Heart J 2007; Takagi et al. J Am Coll Cardiol Intv 2009) have highlighted the beneficial effects of thiazolidinediones in reducing neointimal growth after stent implantation. We review herein IVUS studies regarding the effects of thiazolidinedione therapy on in-stent restenosis after coronary stent implantation.

#### **2. Effects of thiazolidinedione beyond anti-diabetic actions**

Thiazolidinediones activate peroxisome proliferator-activated receptor (PPAR)- in adipose tissue, improving insulin sensitivity and glucose control in patients with type 2 diabetes mellitus and metabolic syndrome. The first thiazolidinedione described, troglitazone, was removed from the market because of hepatotoxic effects. Two glitazones, pioglitazone (Actos; Takeda/Lilly,) and rosiglitazone (Avandia; GlaxoSmithKline) are now commercially available for treatment of diabetes mellitus. Glitazones have been shown to improve specific lipid abnormalities associated with insulin resistance. Treatment with glitazones elevates serum levels of high-density lipoprotein (HDL) cholesterol, decreases triglyceride levels, and changes the size of low-density lipoprotein (LDL) cholesterol from small particles to large ones, less atherogenic particles. (Hanefeld M, et al. Diabetes Care 2004) Beyond the anti-diabetic activity, thiazolidinediones inhibit inflammatory activity, and migration and

Effects of Thiazolidinediones on In-Stent Restenosis: A Review of IVUS Studies 153

controlled study. (Katayama, et al. Am Heart J 2007) Before coronary stenting, 32 patients were randomly assigned to two treatment groups: the pioglitazone group; and the control group. All patients were successfully treated using IVUS-guided coronary stenting. After coronary stenting, patients in the pioglitazone group were treated with 30 mg/day of pioglitazone in addition to standard medications for 6 months, whereas patients in the control group were treated using only standard medications. After intracoronary administration of isosorbide dinitrate, a 40-MHz IVUS catheter was advanced to the distal side beyond the target lesion, and IVUS images were recorded using automatic pullback (0.5 mm/s). The lesion was defined as the site with smallest lumen, and the reference points were defined as the sites with the largest lumen within 10 mm proximal and distal to the lesion. Bare metal stents were implanted based on IVUS measurements. In accordance with the American College of Cardiology Task Force on Clinical Expert Consensus Documents on IVUS, (Mintz S, et al. J Am Coll Cardiol 2001) quantitative IVUS measurements were performed by a single observer who was blinded to the treatment assignments of patients.

Fig. 1. The following parameters of IVUS were measured at 0.5-mm intervals through the stent site immediately and 6 months after stent implantation. 1) External elastic membrane cross-sectional lumen areas (mm2); 2) Stent cross-sectional lumen areas (mm2); 3) Lumen cross-sectional lumen areas (mm2). Intimal area was calculated as the stent cross-sectional lumen area minus the lumen cross-sectional lumen areas, and the intimal index was defined

as the intimal area divided by the stent cross-sectional lumen areas.

(Figure 1)

proliferation of vascular smooth muscle cells by decreasing matrix metalloproteinase production and inducing cell cycle arrest or apoptosis and atherosclerotic effects in vascular cells in vitro and in diseased animal models. (Marx N, et al. Circ Res 2004)

#### **2.1 Effects of thiazolidinedione on atherosclerosis and cardiovascular events**

In the PROactive study, a double-blinded, placebo-controlled investigation, pioglitazone significantly reduced the composite of all-cause mortality, non-fatal myocardial infarction, and stroke in patients with type 2 diabetes, who have a high risk of macrovascular events. (Dormandy JA, et al. Lancet 2005) Nissen et al. conducted a double-blinded, randomized, multicenter trial in 543 patients with coronary disease and type 2 diabetes to compare the effects of an insulin sensitizer, pioglitazone, with an insulin secretagogue, glimepiride, on the progression of coronary atherosclerosis in patients with type 2 diabetes. (Nissen SE, et al. JAMA 2008) Treatment with pioglitazone resulted in a significantly lower rate of progression of coronary atherosclerosis as assessed by intravascular ultrasound (IVUS) compared with glimepiride in patients with type 2 diabetes and coronary artery disease. A meta-analysis showed that pioglitazone did not increase the risk of myocardial infarction or cardiovascular mortality. (Lincoff, et al. JAMA 2007)

In contrast, controversy persists regarding the effects of rosiglitazone therapy on myocardial infarction and cardiovascular mortality. A meta-analysis of 4 randomized controlled trials (N=14 291, including 6421 receiving rosiglitazone and 7870 receiving control therapy, with a follow-up duration of 1-4 years) showed that rosiglitazone use for 12 months is associated with a 42% increased risk of acute myocardial infarction and a doubling in the risk of heart failure among patients with impaired glucose tolerance or type 2 diabetes. (Singh S, et al. JAMA 2007) The most recent systematic review by Nissen and Wollski reported that rosiglitazone therapy significantly increased the risk of myocardial infarction (odds ratio (OR), 1.28; 95% confidence interval (CI), 1.02-1.63; P=.04), but not cardiovascular mortality (OR, 1.03; 95% CI, 0.78-1.36; P=.86). (Nissen SE, et al. Arch Intern Med 2010)

Both thiazolidinediones have been shown to increase the risk of heart failure compared with treatment with placebo or other antidiabetes medications. In order to compare the risk of serious cardiovascular harm by rosiglitazone and by pioglitazone, Graham DJ et al. conducted a nationwide, observational, retrospective, inception cohort of 227, 571 Medicare beneficiaries aged 65 years or older who initiated treatment with rosiglitazone or pioglitazone. The adjusted hazard ratio for rosiglitazone compared with pioglitazone was 1.06 (95% confidence interval [CI], 0.96-1.18) for AMI; 1.27 (95% CI, 1.12-1.45) for stroke; 1.25 (95% CI, 1.16-1.34) for heart failure; 1.14 (95% CI, 1.05-1.24) for death; and 1.18 (95% CI, 1.12- 1.23) for the composite of AMI, stroke, heart failure, or death. Compared with prescription of pioglitazone, prescription of rosiglitazone was associated with an increased risk of stroke, heart failure, and all-cause mortality and an increased risk of the composite of AMI, stroke, heart failure, or all-cause mortality in patients 65 years or older. (Graham DJ et al. JAMA. 2010)

#### **2.2 Effects of pioglitazone on in-stent restenosis in metabolic syndrome**

We first demonstrated that treatment with pioglitazone reduces intimal index as assessed by IVUS as a parameter of neointimal hyperplasia after bare metal stent implantation in patients with non-diabetic metabolic syndrome using an open-labeled randomized

proliferation of vascular smooth muscle cells by decreasing matrix metalloproteinase production and inducing cell cycle arrest or apoptosis and atherosclerotic effects in vascular

In the PROactive study, a double-blinded, placebo-controlled investigation, pioglitazone significantly reduced the composite of all-cause mortality, non-fatal myocardial infarction, and stroke in patients with type 2 diabetes, who have a high risk of macrovascular events. (Dormandy JA, et al. Lancet 2005) Nissen et al. conducted a double-blinded, randomized, multicenter trial in 543 patients with coronary disease and type 2 diabetes to compare the effects of an insulin sensitizer, pioglitazone, with an insulin secretagogue, glimepiride, on the progression of coronary atherosclerosis in patients with type 2 diabetes. (Nissen SE, et al. JAMA 2008) Treatment with pioglitazone resulted in a significantly lower rate of progression of coronary atherosclerosis as assessed by intravascular ultrasound (IVUS) compared with glimepiride in patients with type 2 diabetes and coronary artery disease. A meta-analysis showed that pioglitazone did not increase the risk of myocardial infarction or

In contrast, controversy persists regarding the effects of rosiglitazone therapy on myocardial infarction and cardiovascular mortality. A meta-analysis of 4 randomized controlled trials (N=14 291, including 6421 receiving rosiglitazone and 7870 receiving control therapy, with a follow-up duration of 1-4 years) showed that rosiglitazone use for 12 months is associated with a 42% increased risk of acute myocardial infarction and a doubling in the risk of heart failure among patients with impaired glucose tolerance or type 2 diabetes. (Singh S, et al. JAMA 2007) The most recent systematic review by Nissen and Wollski reported that rosiglitazone therapy significantly increased the risk of myocardial infarction (odds ratio (OR), 1.28; 95% confidence interval (CI), 1.02-1.63; P=.04), but not cardiovascular mortality

Both thiazolidinediones have been shown to increase the risk of heart failure compared with treatment with placebo or other antidiabetes medications. In order to compare the risk of serious cardiovascular harm by rosiglitazone and by pioglitazone, Graham DJ et al. conducted a nationwide, observational, retrospective, inception cohort of 227, 571 Medicare beneficiaries aged 65 years or older who initiated treatment with rosiglitazone or pioglitazone. The adjusted hazard ratio for rosiglitazone compared with pioglitazone was 1.06 (95% confidence interval [CI], 0.96-1.18) for AMI; 1.27 (95% CI, 1.12-1.45) for stroke; 1.25 (95% CI, 1.16-1.34) for heart failure; 1.14 (95% CI, 1.05-1.24) for death; and 1.18 (95% CI, 1.12- 1.23) for the composite of AMI, stroke, heart failure, or death. Compared with prescription of pioglitazone, prescription of rosiglitazone was associated with an increased risk of stroke, heart failure, and all-cause mortality and an increased risk of the composite of AMI, stroke, heart failure, or all-cause mortality in patients 65 years or older. (Graham DJ et al. JAMA.

(OR, 1.03; 95% CI, 0.78-1.36; P=.86). (Nissen SE, et al. Arch Intern Med 2010)

**2.2 Effects of pioglitazone on in-stent restenosis in metabolic syndrome** 

We first demonstrated that treatment with pioglitazone reduces intimal index as assessed by IVUS as a parameter of neointimal hyperplasia after bare metal stent implantation in patients with non-diabetic metabolic syndrome using an open-labeled randomized

cells in vitro and in diseased animal models. (Marx N, et al. Circ Res 2004)

cardiovascular mortality. (Lincoff, et al. JAMA 2007)

2010)

**2.1 Effects of thiazolidinedione on atherosclerosis and cardiovascular events** 

controlled study. (Katayama, et al. Am Heart J 2007) Before coronary stenting, 32 patients were randomly assigned to two treatment groups: the pioglitazone group; and the control group. All patients were successfully treated using IVUS-guided coronary stenting. After coronary stenting, patients in the pioglitazone group were treated with 30 mg/day of pioglitazone in addition to standard medications for 6 months, whereas patients in the control group were treated using only standard medications. After intracoronary administration of isosorbide dinitrate, a 40-MHz IVUS catheter was advanced to the distal side beyond the target lesion, and IVUS images were recorded using automatic pullback (0.5 mm/s). The lesion was defined as the site with smallest lumen, and the reference points were defined as the sites with the largest lumen within 10 mm proximal and distal to the lesion. Bare metal stents were implanted based on IVUS measurements. In accordance with the American College of Cardiology Task Force on Clinical Expert Consensus Documents on IVUS, (Mintz S, et al. J Am Coll Cardiol 2001) quantitative IVUS measurements were performed by a single observer who was blinded to the treatment assignments of patients. (Figure 1)

Fig. 1. The following parameters of IVUS were measured at 0.5-mm intervals through the stent site immediately and 6 months after stent implantation. 1) External elastic membrane cross-sectional lumen areas (mm2); 2) Stent cross-sectional lumen areas (mm2); 3) Lumen cross-sectional lumen areas (mm2). Intimal area was calculated as the stent cross-sectional lumen area minus the lumen cross-sectional lumen areas, and the intimal index was defined as the intimal area divided by the stent cross-sectional lumen areas.

Effects of Thiazolidinediones on In-Stent Restenosis: A Review of IVUS Studies 155

Fig. 2. Intimal index (a) and intimal area (b) as measured by IVUS and late loss (c) and diameter stenosis (d) as assessed by coronary angiography at 6-month follow-up. Mean intimal index and maximal intimal index (a) were significantly reduced in the patient group

treated using pioglitazone (n=14) compared with controls (n=14). A non-significant reduction in intimal area was seen in the pioglitazone group compared with controls (b). Late loss of minimum lumen diameter and percentage diameter stenosis as assessed by quantitative coronary arteriography at 6-month follow-up. Late loss of minimum lumen diameter (c) and percentage diameter stenosis (d) were significantly decreased in the

pioglitazone group compared with controls.

Two-dimensional tomographic images from IVUS allowed direct visualization of the 360 characterization of the coronary arterial lumen and neointimal hyperplasia at stent sites. IVUS is a safe, accurate and reproducible method and has thus been recognized as the reference method for quantification of restenosis in trials of anti-restenosis therapeutic interventions. Conversely, angiographic studies of progression/regression are limited because angiography shows the opacified silhouette of only the lumen. Furthermore, the variability of vascular remodeling prevents reliable assessment of plaque dimensions on the basis of lumen narrowing.

The primary end point of this study was the reduction of neointimal hyperplasia as evaluated by intimal index, a prespecified parameter for evaluating neointimal hyperplasia by IVUS. (Katayama, et al. Am Heart J 2007) Intimal index rather than intimal area is considered as a more reliable parameter for the assessment of neointimal hyperplasia. (Mintz GS, et al. J Am Coll Cardiol 2006) Secondary end points were intimal area, late loss of minimal lumen diameter, percentage diameter stenosis, binary restenosis rate, and target vessel revascularization.

Mean intimal index and maximal intimal index by IVUS were significantly reduced in the pioglitazone group compared with controls (Figure 2, panel a). Mean intimal area and maximal intimal area also tended to be reduced in the pioglitazone group compared with controls, but this difference was not significant (Figure 2, panel b). Late loss of minimal lumen diameter and percentage diameter stenosis by quantitative coronary angiography were significantly decreased in the pioglitazone group compared with controls (Figure 2, panels c, d).

The binary restenosis rate was 0% in the pioglitazone group, compared to 31% in controls (P=.043). Three patients in the control group underwent target vessel revascularization, whereas no patients in the pioglitazone group required such interventions. No significant differences in fasting plasma glucose levels, 2-h plasma glucose levels, or hemoglobin (Hb)A1c levels at baseline or follow-up were seen between the 2 groups. On the other hand, fasting insulin levels at baseline were significantly higher in the pioglitazone group compared with controls, and 2-h insulin levels at follow-up were lower in the pioglitazone group than in controls (67.1 ± 28.8 μU/mL vs. 151.9 ± 185.7 μU/mL; P=.027). Visceral fat areas as measured by abdominal computed tomography were significantly decreased at follow-up in the pioglitazone group compared with controls, although no significant differences in plasma lipid profiles (including total cholesterol, LDL, HDL and triglyceride levels) between groups. Pioglitazone treatment improved insulin resistance and decreased visceral fat accumulation, which is closely associated with insulin resistance, without significant changes in glucose or HbA1c levels, or lipid profiles. Our results indicate that reductions in neointimal hyperplasia by pioglitazone in non-diabetic patients with metabolic syndrome are likely attributable to improvements in insulin resistance. Our findings are consistent with previous reports of randomized controlled trials and metaanalyses in patients with impaired glucose tolerance or type 2 diabetes. However, no RCTs have demonstrated that rosiglitazone significantly reduces the risk of repeat target vessel revascularization following implantation of bare metal stents. A meta-analysis by Nishio et al. showed that rosiglitazone does not reduce the risk of repeat target vessel revascularization following PCI (Nishio et al. Cardiovasc Revasc Med 2010). The reasons behind these differing results for prevention of in-stent-restenosis by two thiazolidinediones remain unclear.

Two-dimensional tomographic images from IVUS allowed direct visualization of the 360 characterization of the coronary arterial lumen and neointimal hyperplasia at stent sites. IVUS is a safe, accurate and reproducible method and has thus been recognized as the reference method for quantification of restenosis in trials of anti-restenosis therapeutic interventions. Conversely, angiographic studies of progression/regression are limited because angiography shows the opacified silhouette of only the lumen. Furthermore, the variability of vascular remodeling prevents reliable assessment of plaque dimensions on the

The primary end point of this study was the reduction of neointimal hyperplasia as evaluated by intimal index, a prespecified parameter for evaluating neointimal hyperplasia by IVUS. (Katayama, et al. Am Heart J 2007) Intimal index rather than intimal area is considered as a more reliable parameter for the assessment of neointimal hyperplasia. (Mintz GS, et al. J Am Coll Cardiol 2006) Secondary end points were intimal area, late loss of minimal lumen diameter, percentage diameter stenosis, binary restenosis rate, and target

Mean intimal index and maximal intimal index by IVUS were significantly reduced in the pioglitazone group compared with controls (Figure 2, panel a). Mean intimal area and maximal intimal area also tended to be reduced in the pioglitazone group compared with controls, but this difference was not significant (Figure 2, panel b). Late loss of minimal lumen diameter and percentage diameter stenosis by quantitative coronary angiography were significantly decreased in the pioglitazone group compared with controls (Figure 2,

The binary restenosis rate was 0% in the pioglitazone group, compared to 31% in controls (P=.043). Three patients in the control group underwent target vessel revascularization, whereas no patients in the pioglitazone group required such interventions. No significant differences in fasting plasma glucose levels, 2-h plasma glucose levels, or hemoglobin (Hb)A1c levels at baseline or follow-up were seen between the 2 groups. On the other hand, fasting insulin levels at baseline were significantly higher in the pioglitazone group compared with controls, and 2-h insulin levels at follow-up were lower in the pioglitazone group than in controls (67.1 ± 28.8 μU/mL vs. 151.9 ± 185.7 μU/mL; P=.027). Visceral fat areas as measured by abdominal computed tomography were significantly decreased at follow-up in the pioglitazone group compared with controls, although no significant differences in plasma lipid profiles (including total cholesterol, LDL, HDL and triglyceride levels) between groups. Pioglitazone treatment improved insulin resistance and decreased visceral fat accumulation, which is closely associated with insulin resistance, without significant changes in glucose or HbA1c levels, or lipid profiles. Our results indicate that reductions in neointimal hyperplasia by pioglitazone in non-diabetic patients with metabolic syndrome are likely attributable to improvements in insulin resistance. Our findings are consistent with previous reports of randomized controlled trials and metaanalyses in patients with impaired glucose tolerance or type 2 diabetes. However, no RCTs have demonstrated that rosiglitazone significantly reduces the risk of repeat target vessel revascularization following implantation of bare metal stents. A meta-analysis by Nishio et al. showed that rosiglitazone does not reduce the risk of repeat target vessel revascularization following PCI (Nishio et al. Cardiovasc Revasc Med 2010). The reasons behind these differing results for prevention of in-stent-restenosis by two thiazolidinediones

basis of lumen narrowing.

vessel revascularization.

panels c, d).

remain unclear.

Fig. 2. Intimal index (a) and intimal area (b) as measured by IVUS and late loss (c) and diameter stenosis (d) as assessed by coronary angiography at 6-month follow-up. Mean intimal index and maximal intimal index (a) were significantly reduced in the patient group treated using pioglitazone (n=14) compared with controls (n=14). A non-significant reduction in intimal area was seen in the pioglitazone group compared with controls (b). Late loss of minimum lumen diameter and percentage diameter stenosis as assessed by quantitative coronary arteriography at 6-month follow-up. Late loss of minimum lumen diameter (c) and percentage diameter stenosis (d) were significantly decreased in the pioglitazone group compared with controls.

Effects of Thiazolidinediones on In-Stent Restenosis: A Review of IVUS Studies 157

Marx N, Duez H, Fruchart JC, Staels B. (2004) Peroxisome proliferator-activated receptors

Mintz GS, Nissen SE, Anderson WD, Bailey SR, Erbel R, Fitzgerald PJ, Pinto FJ, Rosenfield

Marx N, Wohrle J, Nusser T, Walcher D, Rinker A, Hombach V, Koenig W, Hoher M, (2005)

Dormandy JA, Charbonnel B, Eckland DJ, Erdmann E, Massi-Benedetti M, Moules IK, Skene

Nissen SE, Nicholls SJ, Wolski K, Nesto R, Kupfer S, Perez A, Jure H, De Larochellière R,

Lincoff AM, Wolski K, Nicholls SJ, Nissen SE. Pioglitazone and risk of cardiovascular events

Singh S, Loke YK, Furberg CD.(2007) Long-term risk of cardiovascular events with

Nissen SE, Wolski K. (2010) Rosiglitazone revisited: An updated meta-analysis of risk for

Graham DJ, Ouellet-Hellstrom R, MaCurdy TE, Ali F, Sholley C, Worrall C, Kelman JA.

Riche DM, Valderrama R, Henyan NN. (2007) Thiazolidinediones and risk of repeat target

1178.

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*Circulation* 112: 2792–2798.

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analysis. *Diabetes Care.* 30:384-388.

1201.

418.

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randomized controlled trial, *JAMA*; 299:1561–1573.

rosiglitazone: a meta-analysis. *JAMA*.298:1189-1195.

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K, Siegel RJ, Tuzcu EM, Yock PG.(2001) American College of Cardiology Clinical Expert Consensus Document on Standards for Acquisition, Measurement and Reporting of Intravascular Ultrasound Studies (IVUS). A report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents. *J Am* 

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AM, Tan MH, Lefèbvre PJ, Murray GD, Standl E, Wilcox RG, Wilhelmsen L, Betteridge J, Birkeland K, Golay A, Heine RJ, Korányi L, Laakso M, Mokán M, Norkus A, Pirags V, Podar T, Scheen A, Scherbaum W, Schernthaner G, Schmitz O, Skrha J, Smith U, Taton J; PROactive investigators. (2005) Secondary prevention of macrovascular events in patients with type 2 diabetes in the PROactive Study (PROspective pioglitAzone Clinical Trial In macroVascular Events): a randomised

Staniloae CS, Mavromatis K, Saw J, Hu B, Lincoff AM, Tuzcu EM; PERISCOPE Investigators. (2008) Comparison of pioglitazone vs glimepiride on progression of coronary atherosclerosis in patients with type 2 diabetes: the PERISCOPE

in patients with type 2 diabetes mellitus: a meta-analysis of randomized trials.

myocardial infarction and cardiovascular mortality. *Arch Intern Med.* 170:1191-

(2010) Risk of acute myocardial infarction, stroke, heart failure, and death in elderly medicare patients treated with rosiglitazone or pioglitazone*. JAMA*.304:411-

vessel revascularization following percutaneous coronary intervention: a meta-

#### **3. Conclusion**

Thiazolidinediones, agonists of peroxisome proliferator-activated receptor (PPAR)-, improve insulin sensitivity in patients with type II diabetes mellitus and metabolic syndrome. Beyond the anti-diabetic actions, thiazolidinediones exert anti-inflammatory and anti-atherosclerotic effects in vascular cells in vitro and in diseased animal models. Pioglitazone shows reductions in neointimal hyperplasia leading to in-stent-restenosis after implantation of bare metal stents in patients with type 2 diabetes and metabolic syndrome by IVUS, without unfavorable effects such as increases in myocardial infarction or cardiovascular death. Rosiglitazone shows not only no significant reduction of in-stentrestenosis, but also a strong possibility of increased risk of myocardial infarction and cardiovascular death.

Two-dimensional tomographic imaging by IVUS allows direct visualization of the 360 characterization of coronary arterial lumen and neointimal hyperplasia at the stent sites. IVUS is a safe, accurate and reproducible method and has thus been recognized as the reference method for quantification of restenosis in trials of anti-restenosis therapeutic interventions.

#### **4. References**


Thiazolidinediones, agonists of peroxisome proliferator-activated receptor (PPAR)-, improve insulin sensitivity in patients with type II diabetes mellitus and metabolic syndrome. Beyond the anti-diabetic actions, thiazolidinediones exert anti-inflammatory and anti-atherosclerotic effects in vascular cells in vitro and in diseased animal models. Pioglitazone shows reductions in neointimal hyperplasia leading to in-stent-restenosis after implantation of bare metal stents in patients with type 2 diabetes and metabolic syndrome by IVUS, without unfavorable effects such as increases in myocardial infarction or cardiovascular death. Rosiglitazone shows not only no significant reduction of in-stentrestenosis, but also a strong possibility of increased risk of myocardial infarction and

Two-dimensional tomographic imaging by IVUS allows direct visualization of the 360 characterization of coronary arterial lumen and neointimal hyperplasia at the stent sites. IVUS is a safe, accurate and reproducible method and has thus been recognized as the reference method for quantification of restenosis in trials of anti-restenosis therapeutic

Mintz GS, Weissman NJ. (2006) Intravascular ultrasound in the drug eluting stent era. *J Am* 

Piatti P, Di Mario C, Monti LD, Fragasso G, Sgura F, Caumo A, Setola E, Lucotti P,

Katayama T, Ueba H, Tsuboi K, Kubo N, Yasu T, Kuroki M, Saito M, Momomura S,

Takagi T, Okura H, Kobayashi Y, Kataoka T, Taguchi H, Toda I, Tamita K, Yamamuro

Hanefeld M, Brunetti P, Schernthaner GH, Matthews DR, Charbonnel BH, the QUARTET

Galluccio E, Ronchi C, Origgi A, Zavaroni I, Margonato A, Colombo A. (2003) Association of insulin resistance, hyperleptinemia, and impaired nitric oxide release with in-stent restenosis in patients undergoing coronary stenting.

Kawakami M. (2007) Reduction of neointimal hyperplasia after coronary stenting by pioglitazone in nondiabetic patients with metabolic syndrome, *Am Heart J* 153:

A, Sakanoue Y, Ito A, Yanagi S, Shimeno K, Waseda K, Yamasaki M, Fitzgerald PJ, Ikeno F, Honda Y, Yoshiyama M, Yoshikawa J; POPPS Investigators (2009) prospective, multicenter, randomized trial to assess efficacy of pioglitazone on in-stent neointimal suppression in type 2 diabetes: POPPS (Prevention of Instent Neointimal Proliferation by Pioglitazone Study) *J Am Coll Cardiol Intv* 

study group: (2004) One-year glycemic control with a sulfonylurea plus pioglitazone versus a sulfonylurea plus metformin in patients with type 2 diabetes.

**3. Conclusion** 

cardiovascular death.

interventions.

**4. References** 

*Coll Cardiol* 48:421 -429.

*Circulation* 108:2074 - 2081.

762.e1–762.e7.

2:524–531.

*Diabetes Care* 27:141–147.


**Part 3** 

**Technical Developments** 

Nishio K, Kobayashi Y. (2010) Different effects of thiazolidinediones on target vessel revascularization with bare metal stents: a meta-analysis. *Cardiovasc Revasc Med.* 11:227-231.

**Part 3** 

**Technical Developments** 

158 Intravascular Ultrasound

Nishio K, Kobayashi Y. (2010) Different effects of thiazolidinediones on target vessel

11:227-231.

revascularization with bare metal stents: a meta-analysis. *Cardiovasc Revasc Med.*

**11** 

*USA* 

**Arterial Plaque Characterization Using** 

The reported yearly worldwide death tolls and especially in the US about cardio-vascular disease is the leading factor that motivated scientists to invest time and money in order to find innovative ways that enable accurate and early detection of such diseases (American Heart Association [AHA], 2006; AHA, 2008). Since CVD occurs within the human body, imaging modalities were invented to present a picture of the artery as close as possible to its real status. These imaging methods accompanied with continuous developments have helped tremendously in the improvement of proactive health care and early interventions before aggravations. Intravascular Ultrasound (IVUS) is one of the cost effective modalities that have been extensively used for diagnostics purposes (Gaster et al., 2003; Mueller et al., 2003). Although IVUS has the advantage of differentiating between all the artery crosssection components in terms of geometry (Nissen & Yock, 2001), the composition and mechanical properties of each component is still a subject of discussion and research. In fact, an objective classification of plaques based on both mechanical and acoustic properties is not reached yet. For instance, echogenicity of luminal tissue in most cases is the same for a plaque composed of high lipid depositions (Stary, 1992; Stary et al., 1994; Stary et al., 1995). Thus ultrasound wave propagation and transmission should be studied fundamentally in the human tissues and specifically through the artery cross-sections. The only way these ultrasonic waves could be studied meticulously is by solving the propagation governing equations, i.e., through the wave equation. Finding the analytical solution of these waves contributes definitely in understanding the propagation fashion and behavior inside the medium. Finding analytical solution of the wave equation is highly dependent on the medium. In the case of artery cross-section in a human body, there exist numerous geometric irregularities. These irregular shaped components of the artery make the wave equation unsolvable analytically. Consequently numerical methods are employed to find

The inability of discriminating most plaque types from the grayscale images has fostered researchers to think about the content and information that the IVUS backscattered radiofrequency (RF) ultrasound waves could offer. Studies have shown that RF signals possess valuable information in terms of plaque composition (Normal, fatty, fibro-fatty, fibrous, fibrous with calcification). It has been noticed that there is a difference between these RF

**1. Introduction** 

discrete solutions of the ultrasound waves.

echoes coming from various plaque types (Urbani et al., 1993).

**IVUS Radio-Frequency Time Echoes** 

*University of Houston, Department of Mechanical Engineering* 

Rafik Borji and Matthew A. Franchek

## **Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes**

Rafik Borji and Matthew A. Franchek *University of Houston, Department of Mechanical Engineering USA* 

#### **1. Introduction**

The reported yearly worldwide death tolls and especially in the US about cardio-vascular disease is the leading factor that motivated scientists to invest time and money in order to find innovative ways that enable accurate and early detection of such diseases (American Heart Association [AHA], 2006; AHA, 2008). Since CVD occurs within the human body, imaging modalities were invented to present a picture of the artery as close as possible to its real status. These imaging methods accompanied with continuous developments have helped tremendously in the improvement of proactive health care and early interventions before aggravations. Intravascular Ultrasound (IVUS) is one of the cost effective modalities that have been extensively used for diagnostics purposes (Gaster et al., 2003; Mueller et al., 2003). Although IVUS has the advantage of differentiating between all the artery crosssection components in terms of geometry (Nissen & Yock, 2001), the composition and mechanical properties of each component is still a subject of discussion and research. In fact, an objective classification of plaques based on both mechanical and acoustic properties is not reached yet. For instance, echogenicity of luminal tissue in most cases is the same for a plaque composed of high lipid depositions (Stary, 1992; Stary et al., 1994; Stary et al., 1995). Thus ultrasound wave propagation and transmission should be studied fundamentally in the human tissues and specifically through the artery cross-sections. The only way these ultrasonic waves could be studied meticulously is by solving the propagation governing equations, i.e., through the wave equation. Finding the analytical solution of these waves contributes definitely in understanding the propagation fashion and behavior inside the medium. Finding analytical solution of the wave equation is highly dependent on the medium. In the case of artery cross-section in a human body, there exist numerous geometric irregularities. These irregular shaped components of the artery make the wave equation unsolvable analytically. Consequently numerical methods are employed to find discrete solutions of the ultrasound waves.

The inability of discriminating most plaque types from the grayscale images has fostered researchers to think about the content and information that the IVUS backscattered radiofrequency (RF) ultrasound waves could offer. Studies have shown that RF signals possess valuable information in terms of plaque composition (Normal, fatty, fibro-fatty, fibrous, fibrous with calcification). It has been noticed that there is a difference between these RF echoes coming from various plaque types (Urbani et al., 1993).

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 163

Nonlinear propagation mathematical models have been introduced. The most widely used model for modeling finite amplitude sound beam propagation is the so-called Khokhlov, Zabolotskaya and Kuznetsov (KZK) equation (Kuznestov, 1971). Numerous methods to solve this non-linear model have been proposed (Lee & Hamilton, 1995; Tavakkoli et al., 1998). One of the difficulties for these numerical models was the computational aspect. Huge memory and supercomputing machines have to be allocated for the implementation of such nonlinear models. Even using advanced equipments in terms of performance, the computation process of these models can take several hours and even days. This is far from

Given the complexity in solving these nonlinear models, other groups of researchers have resorted to the adoption of simple linear wave equation models (Kendall & Weimin, 2001). In fact ultrasound that is propagating in biological tissues generates small fluctuations. The propagation of these fluctuations is governed by what is called the wave equation. The closed form solution of the wave equation here above is unavailable. Thus two main numerical methods were proposed; which are the finite differences and the finite element methods (Guenther & John, 1996; Kendall & Weimin, 2001). The complexity of the models

A reduced order model called Transmission Line matrix (TLM) method is developed in this chapter to simulate the ultrasound wave propagation. The foundation of the computational method (Transmission Line Matrix Method) that is used to model IVUS in a simple regular medium (rectangular shape) is first developed. A new TLM model in polar coordinates (circular shape to model the artery cross-section) is then outlined. The TLM model will subsequently be modified to model IVUS. The system identification methodology used to construct a parametric model that characterizes a plaque for specific mechanical and

The idea of using electrical circuits for TLM came from the analogy that was established between the current or voltage propagating in this line from one point to another and the electromagnetic field (EMF) governing equations (Christos, 1995). Besides this analogy, TLM was based on the Huygens principle where each point of a wave front is regarded as a secondary wave source point and the surface tangent to the secondary wave fronts is used

presented problems in terms of real time simulation and computational burden.

acoustic properties is demonstrated in the last part of the chapter.

Fig. 1. A simple transmission line circuit between points x and x+Δx

to determine the future position of wave front (Fig. 2).

Transmission Line Matrix concept was based on transmission lines (Fig. 1).

**2. TLM model** 

simulating a real time propagation of the ultrasonic waves.

Integrated backscatter IVUS (IB IVUS) was introduced and calculated based on these RF signals. Despite the accurate differentiation between all plaque types (calcification, mixed lesion, fibrous tissue, lipid core and thrombus) using IB IVUS, the angle dependency between ROI's and catheter axis makes this classification unstable and sensitive (Urbani et al., 1993; Picano et al., 1983; Sarnelli et al.,1986; Landini et al., 1986; Barzilai et al., 1987; De Kroon et al., 1991; Picano et al., 1994). Moreover the high resolution dictated for plaque detection necessitates high frequency ultrasound signals which affect the penetration depth of these transmitted ultrasonic pulses.

In addition to the use of IB as a determinant parameter by which plaques were classified, new research directions has been inspired from the elastic property that could characterize each plaque type. This gave rise to what is called **intravascular elastography** (also known as **IVUS elastography**) (Cespedes et al., 1991). In fact, investigators have taken advantage of the possibility of recording the RF echoes to use them for displacements or strain determination (Ryan & Foster, 1997; De Korte et al., 1998; Schaar et al., 2003; Saijo et al., 2004; Shapo et al., 1996). Despite the striking difference of the strain values for various plaques, most of the studies were performed in vitro where the temperature is different from in vivo case. Additionally excised arteries were used after freezing and thawing which influences the values of elastic modulus. Elastography has also been criticized for its inability of discriminating between normal artery and Fibrous caps (De Korte et al., 2000).

The use of the RF echoes content has also been used further. A method called **virtual histology** (also called **VH IVUS**) based on these IVUS-RF-ultrasonic waves has been developed. This tissue characterization technique is based on the frequency spectrum analysis (Koenig & Klauss, 2007; Nair et al., 2002). Several limitations accompanied the development of VH IVUS. In fact, virtual histology gives an axial resolution which is too low to detect fibrous cap thickness. In addition the detection between soft plaque material and thrombus is not possible.

Despite this simplicity of image construction from IVUS and the development of some signal processing procedures to overcome the lack of plaque characterization, there are significant challenges which limited the accuracy and clarity of the images produced via IVUS. These challenges are always present in the imaging process. For example, the omnipresence of noise related to the acquisition of the ultrasound waves (due to electronic devices) plays an important role on hiding useful information during the detection process. Moreover uncertainties due to sound speed variation, eccentricity of the transducer as well as scattering (related to small particles such as cells, and irregular surfaces) are important factors which contribute to the limitations of the developed IVUS techniques for the identification of vulnerable plaques. This certainly influences the issues of resolution and inability to adequately discriminate between fibrous and lipid-rich plaques.

The nature of this imaging modality (irregularities in the geometry of the tissues and movement of the catheter tips) and the sensitivity of the recorded RF echoes have motivated other research groups to work on modeling the ultrasound wave propagation in biological tissues and specifically IVUS.

Since the IVUS imaging method is based on ultrasound wave propagation, the only way to sketch a model for this propagation will be dictated from the constitutive laws that govern these waves. To know the complete behavior of the waves towards each tissue component, a solution should be found in time and space for these signals.

Nonlinear propagation mathematical models have been introduced. The most widely used model for modeling finite amplitude sound beam propagation is the so-called Khokhlov, Zabolotskaya and Kuznetsov (KZK) equation (Kuznestov, 1971). Numerous methods to solve this non-linear model have been proposed (Lee & Hamilton, 1995; Tavakkoli et al., 1998). One of the difficulties for these numerical models was the computational aspect. Huge memory and supercomputing machines have to be allocated for the implementation of such nonlinear models. Even using advanced equipments in terms of performance, the computation process of these models can take several hours and even days. This is far from simulating a real time propagation of the ultrasonic waves.

Given the complexity in solving these nonlinear models, other groups of researchers have resorted to the adoption of simple linear wave equation models (Kendall & Weimin, 2001). In fact ultrasound that is propagating in biological tissues generates small fluctuations. The propagation of these fluctuations is governed by what is called the wave equation. The closed form solution of the wave equation here above is unavailable. Thus two main numerical methods were proposed; which are the finite differences and the finite element methods (Guenther & John, 1996; Kendall & Weimin, 2001). The complexity of the models presented problems in terms of real time simulation and computational burden.

A reduced order model called Transmission Line matrix (TLM) method is developed in this chapter to simulate the ultrasound wave propagation. The foundation of the computational method (Transmission Line Matrix Method) that is used to model IVUS in a simple regular medium (rectangular shape) is first developed. A new TLM model in polar coordinates (circular shape to model the artery cross-section) is then outlined. The TLM model will subsequently be modified to model IVUS. The system identification methodology used to construct a parametric model that characterizes a plaque for specific mechanical and acoustic properties is demonstrated in the last part of the chapter.

#### **2. TLM model**

162 Intravascular Ultrasound

Integrated backscatter IVUS (IB IVUS) was introduced and calculated based on these RF signals. Despite the accurate differentiation between all plaque types (calcification, mixed lesion, fibrous tissue, lipid core and thrombus) using IB IVUS, the angle dependency between ROI's and catheter axis makes this classification unstable and sensitive (Urbani et al., 1993; Picano et al., 1983; Sarnelli et al.,1986; Landini et al., 1986; Barzilai et al., 1987; De Kroon et al., 1991; Picano et al., 1994). Moreover the high resolution dictated for plaque detection necessitates high frequency ultrasound signals which affect the penetration depth

In addition to the use of IB as a determinant parameter by which plaques were classified, new research directions has been inspired from the elastic property that could characterize each plaque type. This gave rise to what is called **intravascular elastography** (also known as **IVUS elastography**) (Cespedes et al., 1991). In fact, investigators have taken advantage of the possibility of recording the RF echoes to use them for displacements or strain determination (Ryan & Foster, 1997; De Korte et al., 1998; Schaar et al., 2003; Saijo et al., 2004; Shapo et al., 1996). Despite the striking difference of the strain values for various plaques, most of the studies were performed in vitro where the temperature is different from in vivo case. Additionally excised arteries were used after freezing and thawing which influences the values of elastic modulus. Elastography has also been criticized for its inability of discriminating between normal artery and Fibrous caps (De Korte et al., 2000). The use of the RF echoes content has also been used further. A method called **virtual histology** (also called **VH IVUS**) based on these IVUS-RF-ultrasonic waves has been developed. This tissue characterization technique is based on the frequency spectrum analysis (Koenig & Klauss, 2007; Nair et al., 2002). Several limitations accompanied the development of VH IVUS. In fact, virtual histology gives an axial resolution which is too low to detect fibrous cap thickness. In addition the detection between soft plaque material

Despite this simplicity of image construction from IVUS and the development of some signal processing procedures to overcome the lack of plaque characterization, there are significant challenges which limited the accuracy and clarity of the images produced via IVUS. These challenges are always present in the imaging process. For example, the omnipresence of noise related to the acquisition of the ultrasound waves (due to electronic devices) plays an important role on hiding useful information during the detection process. Moreover uncertainties due to sound speed variation, eccentricity of the transducer as well as scattering (related to small particles such as cells, and irregular surfaces) are important factors which contribute to the limitations of the developed IVUS techniques for the identification of vulnerable plaques. This certainly influences the issues of resolution and

The nature of this imaging modality (irregularities in the geometry of the tissues and movement of the catheter tips) and the sensitivity of the recorded RF echoes have motivated other research groups to work on modeling the ultrasound wave propagation in biological

Since the IVUS imaging method is based on ultrasound wave propagation, the only way to sketch a model for this propagation will be dictated from the constitutive laws that govern these waves. To know the complete behavior of the waves towards each tissue component, a

inability to adequately discriminate between fibrous and lipid-rich plaques.

solution should be found in time and space for these signals.

of these transmitted ultrasonic pulses.

and thrombus is not possible.

tissues and specifically IVUS.

Transmission Line Matrix concept was based on transmission lines (Fig. 1).

Fig. 1. A simple transmission line circuit between points x and x+Δx

The idea of using electrical circuits for TLM came from the analogy that was established between the current or voltage propagating in this line from one point to another and the electromagnetic field (EMF) governing equations (Christos, 1995). Besides this analogy, TLM was based on the Huygens principle where each point of a wave front is regarded as a secondary wave source point and the surface tangent to the secondary wave fronts is used to determine the future position of wave front (Fig. 2).

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 165

*z xx*

*V LI x ut V L I y vt*

∂ ∂ = − ∂ ∂

<sup>∂</sup> <sup>∂</sup> = − ∂ ∂

Sound wave problems in the 2-D configuration are the following.

The system of equations in (1) is transformed to equation (4)

medium.

*y y z*

*y x z*

, (1)

. (2)

. (3)

. (4)

*<sup>I</sup> I V uvC x y t*

where *xI* and *yI* are the current traveling in the lines in *x* and *y* directions respectively and *Vz* is the total voltage in the element. Recall that the governing equations for EMF and

*y z*

*E H x t E H y t H Hx E x y t*

<sup>∂</sup> <sup>∂</sup> = μ ∂ ∂

∂ ∂ = −μ ∂ ∂

*P U x t P U y t*

<sup>∂</sup> <sup>∂</sup> = −ρ ∂ ∂

<sup>∂</sup> <sup>∂</sup> = −ρ ∂ ∂

*z x*

<sup>∂</sup> <sup>∂</sup> <sup>∂</sup> − =ε ∂∂ ∂

*y z*

*x*

*y*

*U U P x y t*

*y x*

<sup>∂</sup> <sup>∂</sup> <sup>∂</sup> − − =σ ∂∂ ∂

Where *E* and *H* are the Electric and magnetic fields, μ and ε are the permeability and permittivity of the space. *P* is the pressure, *Ux* and *Uy* are the pressure velocity components in *x* and *y* directions, ρ is the density of the medium and σ is the compressibility of the

> *z x x*

*V I w v L v x uw t I V w L u u y vw t*

∂ ∂− <sup>=</sup> ∂ ∂

<sup>∂</sup> <sup>∂</sup> = − ∂ ∂

*<sup>y</sup> <sup>z</sup> y*

*<sup>y</sup> x z*

*I I V v w u Cw x y uv t*

∂ − <sup>∂</sup> <sup>∂</sup> − = ∂∂ ∂

∂ ∂ <sup>∂</sup> −− = ∂∂ ∂

Fig. 2. Schematics of the Huygens principle for wave propagation (CliffsNotes. Wave Optics, 2010)

TLM models this physics principle by discretizing the medium into a mesh grid and replacing the wave amplitudes by voltages and currents traveling from one node to another (Fig. 3).

Fig. 3. Propagation in TLM model

#### **2.1 Rectangular TLM**

The 2-D TLM method has been widely developed and studied in the literature because of its importance in terms of treating wave propagation in the two dimensional space (Christos, 1995; De Cogan et al., 2006). As mentioned previously the use of TLM method for wave propagation purposes was first inspired from the analogy that was found between the electric circuit variables and the EMF problem. A two dimensional element of a medium of dimensions *u* and *v* , is represented by a node intersected by two transmission lines in the *x* and *y* directions (Fig. 4).

Fig. 4. Shunt TLM node

If*C* is the total capacitance of this element and *Lx* , *Ly* are the total inductances for the two lines in *x* and *y* directions respectively, then the voltage/current differential equations are

Fig. 2. Schematics of the Huygens principle for wave propagation (CliffsNotes. Wave Optics,

TLM models this physics principle by discretizing the medium into a mesh grid and replacing the wave amplitudes by voltages and currents traveling from one node to another (Fig. 3).

The 2-D TLM method has been widely developed and studied in the literature because of its importance in terms of treating wave propagation in the two dimensional space (Christos, 1995; De Cogan et al., 2006). As mentioned previously the use of TLM method for wave propagation purposes was first inspired from the analogy that was found between the electric circuit variables and the EMF problem. A two dimensional element of a medium of dimensions *u* and *v* , is represented by a node intersected by two transmission lines in the *x*

3 *I*

3 *V*

*<sup>4</sup>* <sup>4</sup> *<sup>I</sup>*

*3*

*x*

*z*

*u*

*y*

2 *Lx*

> 2 *Ly*

If*C* is the total capacitance of this element and *Lx* , *Ly* are the total inductances for the two lines in *x* and *y* directions respectively, then the voltage/current differential equations are

4 *V*

*Vz*

*v*

*C*

2010)

Fig. 3. Propagation in TLM model

**2.1 Rectangular TLM** 

and *y* directions (Fig. 4).

Fig. 4. Shunt TLM node

1*I*

*1*

*w*

*2*

2 *V*

1 *V*

2 *I*

2 *Lx*

2 *Ly*

$$\begin{cases} \frac{\partial V\_z}{\partial x} = -\frac{L\_x}{\mu} \frac{\partial I\_x}{\partial t} \\\\ \frac{\partial V\_z}{\partial y} = -\frac{L\_y}{\upsilon} \frac{\partial I\_y}{\partial t} \\\\ -u \frac{\partial I\_x}{\partial x} - v \frac{\partial I\_y}{\partial y} = C \frac{\partial V\_z}{\partial t} \end{cases} \tag{1}$$

where *xI* and *yI* are the current traveling in the lines in *x* and *y* directions respectively and *Vz* is the total voltage in the element. Recall that the governing equations for EMF and Sound wave problems in the 2-D configuration are the following.

$$\begin{cases} \frac{\partial E\_x}{\partial x} = \mu \frac{\partial H\_y}{\partial t} \\ \frac{\partial E\_z}{\partial y} = -\mu \frac{\partial H\_x}{\partial t} \\ \frac{\partial H\_y}{\partial x} - \frac{\partial Hx}{\partial y} = \varepsilon \frac{\partial E\_z}{\partial t} \end{cases} \tag{2}$$

$$\begin{cases} \frac{\partial P}{\partial x} = -\rho \frac{\partial \delta I\_x}{\partial t} \\ \frac{\partial P}{\partial y} = -\rho \frac{\partial \delta I\_y}{\partial t} \\ -\frac{\partial \delta I\_x}{\partial x} - \frac{\partial \delta I\_y}{\partial y} = \sigma \frac{\partial P}{\partial t} \end{cases} \tag{3}$$

Where *E* and *H* are the Electric and magnetic fields, μ and ε are the permeability and permittivity of the space. *P* is the pressure, *Ux* and *Uy* are the pressure velocity components in *x* and *y* directions, ρ is the density of the medium and σ is the compressibility of the medium.

The system of equations in (1) is transformed to equation (4)

$$\begin{cases} \frac{\partial \left(\frac{V\_z}{\nu \upsilon}\right)}{\partial x} = \frac{L\_x \upsilon}{\mu \upsilon} \frac{\partial \left(-\frac{I\_x}{\upsilon}\right)}{\partial t} \\ \frac{\partial \left(\frac{V\_z}{\upsilon}\right)}{\partial y} = -\frac{L\_y \mu}{\upsilon \upsilon} \frac{\partial \left(\frac{I\_y}{\mu}\right)}{\partial t} \\ \frac{\partial \left(-\frac{I\_x}{\upsilon}\right)}{\partial x} - \frac{\partial \left(\frac{I\_y}{\mu}\right)}{\partial y} = \frac{C \upsilon \upsilon}{\mu \upsilon} \frac{\partial \left(\frac{V\_z}{\upsilon}\right)}{\partial t} \end{cases} \tag{4}$$

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 167

1 1 2 2 3 3 4 4

*V V V V V V V V*

<sup>=</sup>

There are applications, such as arteries, when the medium geometry is complex (curved or circular shapes), where the use of the regular TLM method is not appropriate to solve numerically the sound wave equation. This restriction on the shape and size of the mesh affects the capability of the conventional regular TLM method. Moreover the employment of the conventional TLM where the shape is irregular necessitates the use of finer meshes to represent these irregularities accurately. This represents a burden in terms of memory use and run time for numerical computations. Hence a new TLM mesh and model will be

A two dimensional element of a medium having differing dimensions *u* and *v* , is represented by a node intersected by two transmission lines in *x* and *y* directions (Fig. 6).

*x*

 = σ = ρ = ρ 

*uv <sup>C</sup> w uw <sup>L</sup> v*

*vw <sup>L</sup> u*

Time synchronism is conserved in the TLM (Christos, 1995). In fact, the transmitted pulse from one node must reach its surrounding nodes at the same time regardless the lines lengths linking these nodes in all direction ( *x* and *y* directions in the 2-D case). This means that the velocity of propagation of the voltage is dependent on the lines lengths. Since the

inductance term is fixed and capacitance is calculated for each direction by taking into

*y*

velocity is function of the total inductance and capacitance of the line ( <sup>1</sup> *<sup>V</sup>*

account the relationship between inductance, capacitance and velocity.

*R I k k R I k k R I k k R I k k*

0.5

developed for the whole artery cross-section in the next section.

**2.2 Cylindrical TLM** 

Fig. 6. Irregularly spaced element

From Table 1, the following relationships are obtained


 1 1 - 1 1 1 1 1 -1

. (5)

. (6)

*LC* <sup>=</sup> ), the

Here *w* is an arbitrary distance inserted to retain the correct dimensionality when dividing *xI* and *yI* by *v* and *u* respectively (Al-Mukhtar & Sitch, 1981). Comparing equations (2), (3) and (4), the analogy between EMF, sound propagation and electric circuits is established in Table 1. From this analogy the electric and magnetic fields of the EMF problem could be solved through the TLM method by considering them as the transmission line voltage and currents respectively. The same thing applies for the sound wave problem (wave equation), where the amplitudes are calculated via the voltages traveling in the TLM model.


Table 1. Analogy between EMF, Sound wave and TL parameters

In a regular mesh, each node is characterized by equally spaced nodes related to each other by four lines (in the x and y directions) as illustrated in Fig. 4. This shunt node in a Cartesian regular mesh is presented by four transmission line segments each of characteristic impedance , 1,2,3,4 *Z i <sup>i</sup>* = . These four lines have the same length (i.e. same impedance). The scattering is calculated based on the incident( )*<sup>I</sup> k i V* and reflected ( ) *<sup>R</sup> k i V* pulses to the node and the relationship between them. This relationship between ( )*<sup>I</sup> k i V* and ( ) *<sup>R</sup> k i V* is derived using a general approach based on replacing each of the line segment by its Thevenin equivalent (U.A. Bakshi & V.U. Bakshi, 2009). For each segment, this consists of a voltage 2 *<sup>I</sup> k i V* in series with the impedance *Zi* (Fig. 5).

Fig. 5. Thevenin equivalent circuit for the 4 lines intersecting the shunt node of the mesh The scattering matrix for the shunt node

$$
\begin{bmatrix}
{}\_k V\_1^R \\ {}\_k V\_2^R \\ {}\_k V\_3^R \\ {}\_k V\_4^R \end{bmatrix} = 0.5 \begin{bmatrix}
\mathbf{-1} & \mathbf{1} & \mathbf{1} & \mathbf{1} \\ \mathbf{1} & \mathbf{-1} & \mathbf{1} & \mathbf{1} \\ \mathbf{1} & \mathbf{1} & \mathbf{-1} & \mathbf{1} \\ \mathbf{1} & \mathbf{1} & \mathbf{1} & \mathbf{-1} \\ \end{bmatrix} \begin{bmatrix}
{}\_k V\_1^I \\ {}\_k V\_3^I \\ {}\_k V\_4^I \\ {}\_k V\_4^I \end{bmatrix} . \tag{5}
$$

There are applications, such as arteries, when the medium geometry is complex (curved or circular shapes), where the use of the regular TLM method is not appropriate to solve numerically the sound wave equation. This restriction on the shape and size of the mesh affects the capability of the conventional regular TLM method. Moreover the employment of the conventional TLM where the shape is irregular necessitates the use of finer meshes to represent these irregularities accurately. This represents a burden in terms of memory use and run time for numerical computations. Hence a new TLM mesh and model will be developed for the whole artery cross-section in the next section.

#### **2.2 Cylindrical TLM**

166 Intravascular Ultrasound

Here *w* is an arbitrary distance inserted to retain the correct dimensionality when dividing *xI* and *yI* by *v* and *u* respectively (Al-Mukhtar & Sitch, 1981). Comparing equations (2), (3) and (4), the analogy between EMF, sound propagation and electric circuits is established in Table 1. From this analogy the electric and magnetic fields of the EMF problem could be solved through the TLM method by considering them as the transmission line voltage and currents respectively. The same thing applies for the sound wave problem (wave equation),

> Electric Circuit Parameters for the Transmission Line (TL)

> > *w*

*v*

*u*

*vw* or *L vx*

*k i*

*k V*

*V* and ( ) *<sup>R</sup> k i*

*k i*

*V* pulses to the node

*V* is derived

*uw*

where the amplitudes are calculated via the voltages traveling in the TLM model.

*Ez P Vz*

−*Hy Ux xI*

*Hx Uy yI*

ε σ *Cw uv*

In a regular mesh, each node is characterized by equally spaced nodes related to each other by four lines (in the x and y directions) as illustrated in Fig. 4. This shunt node in a Cartesian regular mesh is presented by four transmission line segments each of characteristic impedance , 1,2,3,4 *Z i <sup>i</sup>* = . These four lines have the same length (i.e. same impedance). The

using a general approach based on replacing each of the line segment by its Thevenin equivalent (U.A. Bakshi & V.U. Bakshi, 2009). For each segment, this consists of a voltage

*k i*

*Z*<sup>2</sup> *Z*<sup>3</sup>

Fig. 5. Thevenin equivalent circuit for the 4 lines intersecting the shunt node of the mesh

*Z*<sup>1</sup> *Z*<sup>4</sup>

*V* and reflected ( ) *<sup>R</sup>*

<sup>3</sup> 2 *<sup>I</sup> k V*

*V* <sup>4</sup> 2 *<sup>I</sup>*

μ ρ *L uy*

Table 1. Analogy between EMF, Sound wave and TL parameters

and the relationship between them. This relationship between ( )*<sup>I</sup>*

<sup>1</sup> 2 *<sup>I</sup> k*

*V* <sup>2</sup> 2 *<sup>I</sup> k*

scattering is calculated based on the incident( )*<sup>I</sup>*

*V* in series with the impedance *Zi* (Fig. 5).

*Vz*

The scattering matrix for the shunt node

Sound wave parameters

EMF parameters

2 *<sup>I</sup> k i*

A two dimensional element of a medium having differing dimensions *u* and *v* , is represented by a node intersected by two transmission lines in *x* and *y* directions (Fig. 6).

Fig. 6. Irregularly spaced element

From Table 1, the following relationships are obtained

$$\begin{cases} \mathbf{C} = \sigma \frac{\mu \upsilon}{\upsilon \upsilon} \\ L\_x = \mathfrak{p} \frac{\mu \upsilon \upsilon}{\upsilon} \\ L\_y = \mathfrak{p} \frac{\upsilon \upsilon \upsilon}{\upsilon \upsilon} \end{cases} \tag{6}$$

Time synchronism is conserved in the TLM (Christos, 1995). In fact, the transmitted pulse from one node must reach its surrounding nodes at the same time regardless the lines lengths linking these nodes in all direction ( *x* and *y* directions in the 2-D case). This means that the velocity of propagation of the voltage is dependent on the lines lengths. Since the velocity is function of the total inductance and capacitance of the line ( <sup>1</sup> *<sup>V</sup> LC* <sup>=</sup> ), the inductance term is fixed and capacitance is calculated for each direction by taking into account the relationship between inductance, capacitance and velocity.

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 169

Obviously the nodes in this case are not equally spaced. Therefore the TLM model corresponds exactly to the same formulation. Consequently a stub line must be added to compensate for the residual capacitance caused by the length difference of the radial and angular lines of each element in the mesh. The element is characterized by radial and

In Fig. 9, the radial line[2,4], the angular line [1,3] and the stub line are characterized respectively by *Zr* , *Z*<sup>θ</sup> and *Z*<sup>5</sup> .The radial, angular impedances and the stub admittance can

( )( ) ( ) ( ) ( )

*dr rd h dr rd*

2 2 2 2 0

0

is the ratio of a line inductance with respect to the smallest line inductance

is the characteristic impedance of the smallest line in the mesh grid of the

<sup>σ</sup> are the inductance and capacitance of the reference line (i.e.

*r*

, (10)

( )( )

σ θ ρ −σ + θ <sup>=</sup> θ σρ

*r*

*dr rd w*

For both Cartesian and cylindrical geometry, each TLM element is thus characterized by a

angular impedances and a stub admittance *Zr* , *Z*<sup>θ</sup> and *Z*<sup>5</sup> .

Fig. 9. Added stub line to a circular element

be derived by replacing *u* by *dr* and *v* by *rd*θ .

 

 

5

θ

*Z*

where

0

0

artery cross-section. ρ<sup>0</sup> and <sup>0</sup>

*r* <sup>ρ</sup> ρ = ρ

and <sup>0</sup>

*ref <sup>h</sup> <sup>Z</sup>* <sup>ρ</sup> <sup>=</sup> <sup>σ</sup>

smallest line).

2

*h*

circuit structure of five transmission lines (Fig. 10).

*<sup>r</sup> <sup>r</sup> ref*

*wdr Z Z rd*

 <sup>ρ</sup> <sup>=</sup> θ

> *wrd Z Z dr*

θρ <sup>=</sup>

*<sup>r</sup> ref*

Given the inductances in both directions, the capacitances per unit length in these lines are obtained.

$$\begin{cases} \mathbf{C}\_x = \frac{\sigma\_0 \upsilon}{\mu^2 \hbar \mathfrak{p}\_r w} \\ \mathbf{C}\_y = \frac{\sigma\_0 \mu}{\upsilon^2 \hbar \mathfrak{p}\_r w} \end{cases} \tag{7}$$

Due to the irregular mesh grid, the total capacitances found in *x* and *y* directions, *Cx* and *Cy* are sometimes less than the total capacitance of the element*C* . A residual capacitance *Cs* is defined and modeled by an open-circuit stub at each node of the mesh (Fig. 7).

$$C\_s = \sigma \frac{\mu v}{w} - \frac{\sigma\_0 \left(\mu^2 + v^2\right)}{\mu v h \mathfrak{p}\_r w} \tag{8}$$

Fig. 7. Stub represented by a new line at each node

The artery cross-section is presented by a disk. The coordinates system is characterized by the angle θ and the radial position *r* (polar coordinates). In the TLM method, the discretization process of the medium will lead to an irregular gridding (Fig. 8).

In general for an arbitrary node that has a radial position *r* the element is characterized by the following lines lengths

$$\begin{cases} \mu\_r = dr \\ \mu\_\Theta = r d\Theta \end{cases} \tag{9}$$

Obviously the nodes in this case are not equally spaced. Therefore the TLM model corresponds exactly to the same formulation. Consequently a stub line must be added to compensate for the residual capacitance caused by the length difference of the radial and angular lines of each element in the mesh. The element is characterized by radial and angular impedances and a stub admittance *Zr* , *Z*<sup>θ</sup> and *Z*<sup>5</sup> .

Fig. 9. Added stub line to a circular element

In Fig. 9, the radial line[2,4], the angular line [1,3] and the stub line are characterized respectively by *Zr* , *Z*<sup>θ</sup> and *Z*<sup>5</sup> .The radial, angular impedances and the stub admittance can be derived by replacing *u* by *dr* and *v* by *rd*θ .

$$\begin{cases} Z\_r = \frac{w dr \mathfrak{p}\_r}{r d\mathfrak{q}} Z\_{r rf} \\\\ Z\_0 = \frac{w r d\mathfrak{p}\_r}{dr} Z\_{r rf} \\\\ Z\_5 = \frac{2\left[\mathfrak{q} \left(dr\right)^2 \left(r d\mathfrak{q}\right)^2 h \mathfrak{p}\_r - \mathfrak{q}\_0 \left(\left(dr\right)^2 + \left(r d\mathfrak{q}\right)^2\right)\right]}{\left(dr\mathfrak{r}\right) \left(r d\mathfrak{q}\right) w \mathfrak{p}\_0 \mathfrak{p}\_r} \end{cases} \tag{10}$$

where 0 *r* <sup>ρ</sup> ρ = ρ is the ratio of a line inductance with respect to the smallest line inductance

and <sup>0</sup> 0 *ref <sup>h</sup> <sup>Z</sup>* <sup>ρ</sup> <sup>=</sup> <sup>σ</sup> is the characteristic impedance of the smallest line in the mesh grid of the

artery cross-section. ρ<sup>0</sup> and <sup>0</sup> *h* <sup>σ</sup> are the inductance and capacitance of the reference line (i.e.

smallest line).

168 Intravascular Ultrasound

Given the inductances in both directions, the capacitances per unit length in these lines are

*<sup>v</sup> <sup>C</sup> uh w*

<sup>σ</sup> <sup>=</sup>

*<sup>u</sup> <sup>C</sup> vh w*

Due to the irregular mesh grid, the total capacitances found in *x* and *y* directions, *Cx* and *Cy* are sometimes less than the total capacitance of the element*C* . A residual capacitance

0

The artery cross-section is presented by a disk. The coordinates system is characterized by the angle θ and the radial position *r* (polar coordinates). In the TLM method, the

In general for an arbitrary node that has a radial position *r* the element is characterized by

*u dr <sup>r</sup> u rd* <sup>θ</sup>

<sup>=</sup> = θ (9)

discretization process of the medium will lead to an irregular gridding (Fig. 8).

Fig. 8. Irregular structure of a circular element of the cylindrical TLM model

*u v uv <sup>C</sup> w uvh w* σ +

<sup>ρ</sup> <sup>σ</sup> <sup>=</sup> <sup>ρ</sup>

*x*

*y*

*Cs* is defined and modeled by an open-circuit stub at each node of the mesh (Fig. 7).

=σ −

*s*

Fig. 7. Stub represented by a new line at each node

the following lines lengths

0 2

0 2

*r*

. (7)

(8)

*r*

( ) 2 2

*r*

ρ

obtained.

For both Cartesian and cylindrical geometry, each TLM element is thus characterized by a circuit structure of five transmission lines (Fig. 10).

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 171

by considering a small portion of the artery cross-section that has a rectangular shape (Fig. 14). However the second TLM model (cylindrical) takes into account the whole artery crosssection geometry. These codes were developed in Matlab. In order to construct the TLM models many basic parameters should be provided. The size of the medium, the gridding rate, the boundary termination, the wave source location and the traveling process are the

The medium is automatically generated from the developed TLM codes once the dimensions are specified. Given the inner and outer radii of the artery cross-section, an automated mesh is generated. Since TLM model is based on the nodes and lines of the discretized medium, the number of nodes in both directions as well as the lines lengths are function of the indicated gridding rates. In the cylindrical TLM model, the choice of the gridding rate is essential for capturing the propagation of the ultrasound wave. The wave should reach the outer edge of the artery cross-section. In fact for an arbitrary mesh the propagation trend of the ultrasound wave is more pronounced in the angular direction of the circular medium. The choice of the mesh grid must be generated in a way that guarantees a conic wave propagation of the TLM method. This means that the propagation should occur in a conic way in the radial direction. The propagation as developed previously in the TLM model depends on the scattering matrix which is function of the lines impedances. These impedances are function of the gridding rates in both radial and angular directions. Thus a specific mesh grid should be developed to ensure this numerical stability. The propagation of the sound wave is expected to be like the one illustrated by Fig. 12. Investigations have shown that the angular deviation of the propagation occurs when the

<sup>=</sup> . Since ( )

( )

*<sup>r</sup> Z dr <sup>Z</sup>*<sup>θ</sup> *Rd* <sup>=</sup> <sup>θ</sup>

> *Rd* <

<sup>θ</sup> . By imposing this numerical condition on the mesh grid, the

2 2

, after this radial position,

<sup>θ</sup> . The mesh grid is designed

most important data to be known in the modeling process.

radial position is characterized by 0.633 *Zr*

such that 0.8 *dr Rd* ≥

*Z*θ

Fig. 12. Conic propagation of the sent wave through the circular medium

components do not influence the wave propagation inside the artery cross-section.

As the TLM is a numerical method, the medium should be of a finite size. This is known as **medium termination**. This is presented by a wall that is characterized by the same acoustic impedance of the terminated medium. For example if the external medium that comes after the artery is air, then the wall that models the termination of air is characterized by the acoustic impedance of the air. For all the developed simulations the surrounding media impedances will be taken in such a way the boundary reflection effect is attenuated so that these reflected

the ratio between the gridding rates has this condition 0.8 *dr*

propagation occurs in a conic fashion as illustrated in Fig. 12.

Fig. 10. Shunt node for irregular TLM

The equivalent Thevenin circuit is composed of five Thevenin sources in series with five equivalent impedances corresponding to the five lines (Fig. 11).

$$\nu\_{\boldsymbol{z}}\left[\bigotimes\_{\boldsymbol{z},\boldsymbol{z}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\bigotimes\_{\boldsymbol{z},\boldsymbol{\nu}\_{i}^{\boldsymbol{\nu}^{\boldsymbol{\nu}}}}\right]$$

Fig. 11. Thevenin equivalent circuit for the 5 lines intersecting an arbitrary node of the irregular mesh

The scattering matrix equation in this case is

$$
\begin{bmatrix}
{}\_{k}^{V}\boldsymbol{l}\_{1}^{R} \\
{}\_{k}^{V}\boldsymbol{l}\_{2}^{R} \\
{}\_{k}^{V}\boldsymbol{l}\_{3}^{R} \\
{}\_{k}^{V}\boldsymbol{l}\_{4}^{R} \\
{}\_{k}^{V}\boldsymbol{l}\_{5}^{R}
\end{bmatrix} = \frac{1}{D} \begin{bmatrix}
2\boldsymbol{Z}\_{1} - \boldsymbol{D} & 2\boldsymbol{Z}\_{2} & 2\boldsymbol{Z}\_{3} & 2\boldsymbol{Z}\_{4} & 2\boldsymbol{Z}\_{5} \\
2\boldsymbol{Z}\_{1} & 2\boldsymbol{Z}\_{2} - \boldsymbol{D} & 2\boldsymbol{Z}\_{3} & 2\boldsymbol{Z}\_{4} & 2\boldsymbol{Z}\_{5} \\
2\boldsymbol{Z}\_{1} & 2\boldsymbol{Z}\_{2} & 2\boldsymbol{Z}\_{3} - \boldsymbol{D} & 2\boldsymbol{Z}\_{4} & 2\boldsymbol{Z}\_{5} \\
2\boldsymbol{Z}\_{1} & 2\boldsymbol{Z}\_{2} & 2\boldsymbol{Z}\_{3} & 2\boldsymbol{Z}\_{4} - \boldsymbol{D} & 2\boldsymbol{Z}\_{5} \\
2\boldsymbol{Z}\_{1} & 2\boldsymbol{Z}\_{2} & 2\boldsymbol{Z}\_{3} & 2\boldsymbol{Z}\_{4} & 2\boldsymbol{Z}\_{5} - \boldsymbol{D}
\end{bmatrix} \begin{bmatrix}
\boldsymbol{k}^{I}\_{1}^{I} \\
\boldsymbol{k}^{I}\_{2}^{I} \\
\boldsymbol{k}^{I}\_{3}^{I} \\
\boldsymbol{k}^{I}\_{4}^{I} \\
\boldsymbol{k}^{I}\_{5}^{I}
\end{bmatrix}.
\tag{11}$$

*R k i V* and *<sup>I</sup> k i V* are the reflected and incident voltages to an arbitrary node of the line *i* at time *k* and 5 1 *i i D Z* = <sup>=</sup> is the sum of the impedances of the four lines and the stub admittance.

#### **3. TLM IVUS model**

Ultrasound waves have the same properties as sound waves. They obey the same wave propagation law. In this section a physics-based numerical model is developed using TLM method to mimic the ultrasound wave propagation inside the arterial wall. Both rectangular and cylindrical TLM models will be employed to model IVUS. The first TLM model is used

2 *Lx*

> 2 *Ly*

The equivalent Thevenin circuit is composed of five Thevenin sources in series with five

<sup>3</sup> 2 *<sup>I</sup> k V*

*V* <sup>4</sup> 2 *<sup>I</sup>*

*k V* <sup>5</sup> 2 *<sup>I</sup> k V*

5 *Z*

. (11)

*Z*<sup>2</sup> *Z*<sup>3</sup>

Fig. 11. Thevenin equivalent circuit for the 5 lines intersecting an arbitrary node of the

<sup>1</sup> <sup>1</sup> 1 2345 2 12 3 4 5 2 3 1 23 4 5 3 1 2 34 5 <sup>4</sup> <sup>4</sup> 1 2 3 45 5 5

*R I k k R I k k R I k k R I k k R I k k*

2 2 22 2 2 2 2 22

<sup>=</sup> is the sum of the impedances of the four lines and the stub admittance.

Ultrasound waves have the same properties as sound waves. They obey the same wave propagation law. In this section a physics-based numerical model is developed using TLM method to mimic the ultrasound wave propagation inside the arterial wall. Both rectangular and cylindrical TLM models will be employed to model IVUS. The first TLM model is used

*V* are the reflected and incident voltages to an arbitrary node of the line *i* at time

*V V Z Z Z ZD Z Z Z Z Z ZD V V*

<sup>−</sup> <sup>−</sup> <sup>=</sup> <sup>−</sup> <sup>−</sup> <sup>−</sup>

2 2222 22 2 2 2 <sup>1</sup> 2 22 2 2

*V V ZD Z Z Z Z V V Z ZD Z Z Z V V Z Z ZD Z Z*

*Z*<sup>1</sup> *Z*<sup>4</sup>

*5* 5 *V*

4 *V*

*Cz Vz*

Δ*y*

3 *I*

3 *V*

*<sup>4</sup>* <sup>4</sup> *<sup>I</sup>*

*3*

*x*

*z*

*x* Δ

*y*

1*I*

*1*

*2*

2 *V*

1 *V*

*Vz*

The scattering matrix equation in this case is

*D*

*z* Δ

Fig. 10. Shunt node for irregular TLM

irregular mesh

*R k i*

*k* and

*V* and *<sup>I</sup> k i*

5

1 *i i D Z* =

**3. TLM IVUS model** 

2 *I*

2 *Lx*

equivalent impedances corresponding to the five lines (Fig. 11).

<sup>1</sup> 2 *<sup>I</sup> k V* <sup>2</sup> 2 *<sup>I</sup> k*

2 *Ly* by considering a small portion of the artery cross-section that has a rectangular shape (Fig. 14). However the second TLM model (cylindrical) takes into account the whole artery crosssection geometry. These codes were developed in Matlab. In order to construct the TLM models many basic parameters should be provided. The size of the medium, the gridding rate, the boundary termination, the wave source location and the traveling process are the most important data to be known in the modeling process.

The medium is automatically generated from the developed TLM codes once the dimensions are specified. Given the inner and outer radii of the artery cross-section, an automated mesh is generated. Since TLM model is based on the nodes and lines of the discretized medium, the number of nodes in both directions as well as the lines lengths are function of the indicated gridding rates. In the cylindrical TLM model, the choice of the gridding rate is essential for capturing the propagation of the ultrasound wave. The wave should reach the outer edge of the artery cross-section. In fact for an arbitrary mesh the propagation trend of the ultrasound wave is more pronounced in the angular direction of the circular medium. The choice of the mesh grid must be generated in a way that guarantees a conic wave propagation of the TLM method. This means that the propagation should occur in a conic way in the radial direction. The propagation as developed previously in the TLM model depends on the scattering matrix which is function of the lines impedances. These impedances are function of the gridding rates in both radial and angular directions. Thus a specific mesh grid should be developed to ensure this numerical stability. The propagation of the sound wave is expected to be like the one illustrated by Fig. 12.

Investigations have shown that the angular deviation of the propagation occurs when the

radial position is characterized by 0.633 *Zr Z*θ <sup>=</sup> . Since ( ) ( ) 2 2 *<sup>r</sup> Z dr <sup>Z</sup>*<sup>θ</sup> *Rd* <sup>=</sup> <sup>θ</sup> , after this radial position,

the ratio between the gridding rates has this condition 0.8 *dr Rd* < <sup>θ</sup> . The mesh grid is designed

such that 0.8 *dr Rd* ≥ <sup>θ</sup> . By imposing this numerical condition on the mesh grid, the propagation occurs in a conic fashion as illustrated in Fig. 12.

Fig. 12. Conic propagation of the sent wave through the circular medium

As the TLM is a numerical method, the medium should be of a finite size. This is known as **medium termination**. This is presented by a wall that is characterized by the same acoustic impedance of the terminated medium. For example if the external medium that comes after the artery is air, then the wall that models the termination of air is characterized by the acoustic impedance of the air. For all the developed simulations the surrounding media impedances will be taken in such a way the boundary reflection effect is attenuated so that these reflected components do not influence the wave propagation inside the artery cross-section.

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 173

**The IVUS TLM models can represent both healthy and abnormal artery cross-sections**. In the healthy case the TLM model is described by a medium that has constant acoustic impedance (ܼ ൌ ߩܿ, ߩ is the medium density andܿ is the acoustic speed in the medium). However the abnormal artery is modeled by an inclusion that is inserted in the healthy medium. This inclusion is characterized ban acoustic impedance that is different from the one of the healthy medium. Illustrated in Fig. 14 is the case where artery contains a plaque

The TLM model will consider the plaque as a rectangular object that is inserted inside the artery portion presented by the rectangular medium. The plaque (inclusion) that is formed inside the artery is characterized by different acoustic properties. In fact the ultrasound speed and density are not the same as of the normal tissue (i.e. different acoustic impedances). This will produce a boundary between the healthy portion of the artery and the abnormality edge. This boundary characterizes a change in impedances. A reflection/transmission phenomenon takes place due to this change along the four edges of the plaque. Considering *Z c Plaque Plaque PLaque* = ρ and *Z c Artery artery Artery* = ρ to be the acoustic impedances of the plaque and artery, then the reflection and transmission coefficients are

> *Plaque Artery Plaque Artery*

> > *Z Z*

*Z Z*

The transmission and reflection that occur on both sides of the boundary are function of these coefficients. Depending on the acoustic characteristics of the plaque the propagation of the wave will show different behavior. As an example to illustrate the effect of the plaque, three different acoustic impedances are taken. A swept sine wave is designed to be the source signal at the node (1st horizontal, 45th vertical). The medium is composed of 751 by 76 nodes and the plaque is located between the 20th and 30th node in the horizontal direction

*Z Z*

*Z Z*

<sup>−</sup> = − <sup>+</sup>

<sup>−</sup> <sup>=</sup> <sup>+</sup>

*Plaque Artery Plaque Artery* . (14)

1

*R*

*T*

and the 25th and 65th node in the vertical direction (Fig. 15).

(Yellow colored region).

Fig. 14. Plaque in the artery

The design of **the wave source** has been widely studied for the IVUS. In the TLM model, flexibility is given in the code to design any kind of source waves. Since Matlab is the platform where the code was developed, SIMULINK toolbox is used for the source wave specifications. This toolbox offers a variety of signals some of them are illustrated in Fig. 13. In addition to the wide range of source waves, this model gives the possibility of specifying any location in the mesh to be the source point where the ultrasonic wave starts to propagate. For instance the source could be in one node of the edges of the medium, inside the medium or in different nodes at the same time.

Fig. 13. Examples of different source waves designed by Simulink

**The propagation process** is based in the Huygens principle where for a given node in the mesh, the reflected amplitudes going out at time ݇ will serve as the incident waves to the surrounding nodes at time ݇ͳ. For the rectangular and cylindrical TLM models, it is given by equations (12) and (13).

() ( ) () ( ) () ( ) () ( ) 1 0 0 13 0 0 2 0 0 14 0 0 3 0 0 11 0 0 4 0 0 12 0 0 , , , , , , , , *R I k k R I k k R I k k R I k k V xy Vxy y V x y V x xy V xy Vxy y V x y V x xy* + + + + <sup>=</sup> − Δ = −Δ = + Δ = +Δ (12) ( ) () ( ) () ( ) () ( ) () () () 11 0 0 3 0 0 12 0 0 4 0 0 13 0 0 1 0 0 14 0 0 2 0 0 15 0 0 5 0 0 , , , , , , , , , , *I R k k I R k k I R k k I R k k I R k k Vr d V r V r dr V r Vr d V r V r dr V r Vr V r* + + + + + θ+ θ= θ + θ= θ θ−θ= θ − θ= θ θ= θ . (13)

**The IVUS TLM models can represent both healthy and abnormal artery cross-sections**. In the healthy case the TLM model is described by a medium that has constant acoustic impedance (ܼ ൌ ߩܿ, ߩ is the medium density andܿ is the acoustic speed in the medium). However the abnormal artery is modeled by an inclusion that is inserted in the healthy medium. This inclusion is characterized ban acoustic impedance that is different from the one of the healthy medium. Illustrated in Fig. 14 is the case where artery contains a plaque (Yellow colored region).

#### Fig. 14. Plaque in the artery

172 Intravascular Ultrasound

The design of **the wave source** has been widely studied for the IVUS. In the TLM model, flexibility is given in the code to design any kind of source waves. Since Matlab is the platform where the code was developed, SIMULINK toolbox is used for the source wave specifications. This toolbox offers a variety of signals some of them are illustrated in Fig. 13. In addition to the wide range of source waves, this model gives the possibility of specifying any location in the mesh to be the source point where the ultrasonic wave starts to propagate. For instance the source could be in one node of the edges of the medium, inside

<sup>0</sup> <sup>50</sup> <sup>100</sup> <sup>150</sup> <sup>200</sup> <sup>250</sup> <sup>300</sup> -1

Pulse Signal

<sup>0</sup> <sup>50</sup> <sup>100</sup> <sup>150</sup> <sup>200</sup> <sup>250</sup> <sup>300</sup> <sup>0</sup>

x 104 Band Limited White Noise Signal

<sup>0</sup> <sup>50</sup> <sup>100</sup> <sup>150</sup> <sup>200</sup> <sup>250</sup> <sup>300</sup> -5

Uniform Random Number Signal

<sup>0</sup> <sup>50</sup> <sup>100</sup> <sup>150</sup> <sup>200</sup> <sup>250</sup> <sup>300</sup> -1

Random Number Signal

<sup>0</sup> <sup>50</sup> <sup>100</sup> <sup>150</sup> <sup>200</sup> <sup>250</sup> <sup>300</sup> -5

Swept Sine Wave

**The propagation process** is based in the Huygens principle where for a given node in the mesh, the reflected amplitudes going out at time ݇ will serve as the incident waves to the surrounding nodes at time ݇ͳ. For the rectangular and cylindrical TLM models, it is given

> () ( ) () ( ) () ( ) () ( )

, ,

(12)

. (13)

2 0 0 14 0 0

4 0 0 12 0 0

11 0 0 3 0 0

*I R k k*

*Vr d V r*

θ+ θ= θ

*I R k k*

+ θ= θ

*V r dr V r*

*I R k k*

*Vr d V r*

θ−θ= θ

*I R k k*

*V r dr V r*

− θ= θ

12 0 0 4 0 0

13 0 0 1 0 0

, ,

( ) ()

, ,

( ) ()

, ,

( ) ()

, ,

( ) ()

, ,

() ()

, ,

15 0 0 5 0 0

*I R k k*

*Vr V r*

θ= θ

14 0 0 2 0 0

1 0 0 13 0 0

 <sup>=</sup> − Δ = −Δ

*R I k k R I k k R I k k R I k k*

, ,

+ + + +

*V xy Vxy y V x y V x xy V xy Vxy y V x y V x xy*

3 0 0 11 0 0

= +Δ

= + Δ

, ,

the medium or in different nodes at the same time.

0 1

0.5 1

> 0 5

> 0 1

> 0 5

Fig. 13. Examples of different source waves designed by Simulink

+

 

 

  +

+

+

+

by equations (12) and (13).

The TLM model will consider the plaque as a rectangular object that is inserted inside the artery portion presented by the rectangular medium. The plaque (inclusion) that is formed inside the artery is characterized by different acoustic properties. In fact the ultrasound speed and density are not the same as of the normal tissue (i.e. different acoustic impedances). This will produce a boundary between the healthy portion of the artery and the abnormality edge. This boundary characterizes a change in impedances. A reflection/transmission phenomenon takes place due to this change along the four edges of the plaque. Considering *Z c Plaque Plaque PLaque* = ρ and *Z c Artery artery Artery* = ρ to be the acoustic impedances of the plaque and artery, then the reflection and transmission coefficients are

$$\begin{aligned} R &= \frac{\mathbf{Z}\_{\text{Plaquette}} - \mathbf{Z}\_{\text{Artery}}}{\mathbf{Z}\_{\text{Plaquette}} + \mathbf{Z}\_{\text{Artery}}}\\ T &= \mathbf{1} - \frac{\mathbf{Z}\_{\text{Plaquette}} - \mathbf{Z}\_{\text{Artery}}}{\mathbf{Z}\_{\text{Plaquette}} + \mathbf{Z}\_{\text{Artery}}} \end{aligned} \tag{14}$$

The transmission and reflection that occur on both sides of the boundary are function of these coefficients. Depending on the acoustic characteristics of the plaque the propagation of the wave will show different behavior. As an example to illustrate the effect of the plaque, three different acoustic impedances are taken. A swept sine wave is designed to be the source signal at the node (1st horizontal, 45th vertical). The medium is composed of 751 by 76 nodes and the plaque is located between the 20th and 30th node in the horizontal direction and the 25th and 65th node in the vertical direction (Fig. 15).

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 175

Fig. 17. Time signals record of the wave propagation at different locations having different

This section departs from the traditional approaches appearing in the literature by considering the inclusion within a medium to be a dynamic system. A system identification approach will be adopted to characterize the dynamics of the plaque (Soderstrom & Stoica, 2001). Thus, the TLM models developed in the previous sections are used as a mean of acquiring the time signals transmitted and reflected in a region of interest within the medium (plaque or inclusion location). These signals will be considered as inputs and outputs to the dynamic system where digital signal processing techniques are employed to

Any input signal used in the context of system identification must meet certain condition. In particular, the input signal should be **persistently exciting** (Ljung, 1999). The frequency

One classical frequency-rich signal is the swept sine signal which is also known as the "chirp signal". The chirp signal is a single sine wave with a frequency that is changing continuously as a function of time. The general mathematical presentation of the swept sine

*<sup>k</sup> uk A k <sup>B</sup>*

<sup>−</sup> <sup>−</sup> β= + where max <sup>2</sup> *sf f* <sup>≥</sup>

<sup>−</sup> = πβ ∗ + ϕ +

*s*

*f*

1

() () ( ) <sup>1</sup> sin 2

arg

2 *t et s*

*A signal u t*( ) *characterized by its spectrum* Φ ω *<sup>u</sup>* ( ) *is said to be persistently exciting if* 

*Thus the spectrum may be zero on a set of number of points (almost all definition).* 

inclusion ( healthy artery *ZHardinclsuion* = 7.4Z and healthy artery *ZSoftinclsuion* = 0.074Z )

**4. Plaque characterization** 

wave is

identify a parametric model for these plaques.

**4.1 Persistency of excitation of the input signal** 

domain condition enforcing a persistency of excitation is:

( ) 0 Φ ω> *u for almost all* ω

( ) ( ) max min min

*f f <sup>k</sup> k f t f*

Fig. 15. Plaque example generated by the developed 2-D rectangular TLM model

Fig. 16 is an illustration of the plaque influence on the determination of the wave shape using regular TLM model. This model could be extended to study numerous cases where all combinations of abnormalities can be constructed.

Fig. 16. Comparison of the time signals using the rectangular TLM model (Z������������� = 7.4Z������������� and Z������������� = 0.074Z�������������)

Also using the cylindrical TLM model, an inclusion was inserted in the circular medium between the 70th and 130th angular nodes and 20th and 30th radial nodes. A sine wave is injected from the inner radius (node (1st radial direction, 100th angular direction)) and the wave propagation is recorded. It can be shown from Fig. 17, the effect of the acoustic properties of the inclusions that form inside the artery. These models will be employed in the next section to analyze these recorded signals and build a lumped parameter model of the different tissues types based on their size and acoustic properties.

Fig. 17. Time signals record of the wave propagation at different locations having different inclusion ( healthy artery *ZHardinclsuion* = 7.4Z and healthy artery *ZSoftinclsuion* = 0.074Z )

#### **4. Plaque characterization**

174 Intravascular Ultrasound

Fig. 15. Plaque example generated by the developed 2-D rectangular TLM model

Fig. 16. Comparison of the time signals using the rectangular TLM model (Z������������� = 7.4Z������������� and Z������������� = 0.074Z�������������)

the different tissues types based on their size and acoustic properties.

Also using the cylindrical TLM model, an inclusion was inserted in the circular medium between the 70th and 130th angular nodes and 20th and 30th radial nodes. A sine wave is injected from the inner radius (node (1st radial direction, 100th angular direction)) and the wave propagation is recorded. It can be shown from Fig. 17, the effect of the acoustic properties of the inclusions that form inside the artery. These models will be employed in the next section to analyze these recorded signals and build a lumped parameter model of

combinations of abnormalities can be constructed.

0

0

0

0.5

0.2

1

Fig. 16 is an illustration of the plaque influence on the determination of the wave shape using regular TLM model. This model could be extended to study numerous cases where all

> Zplaque<<Zartery Zplaque=Zartery Zplaque>>Zartery

<sup>0</sup> <sup>100</sup> <sup>200</sup> <sup>300</sup> <sup>400</sup> <sup>500</sup> <sup>600</sup> -1

node (1,45)

<sup>0</sup> <sup>100</sup> <sup>200</sup> <sup>300</sup> <sup>400</sup> <sup>500</sup> <sup>600</sup> -0.2

<sup>0</sup> <sup>100</sup> <sup>200</sup> <sup>300</sup> <sup>400</sup> <sup>500</sup> <sup>600</sup> -0.5

node (31,45)

node (20,45)

This section departs from the traditional approaches appearing in the literature by considering the inclusion within a medium to be a dynamic system. A system identification approach will be adopted to characterize the dynamics of the plaque (Soderstrom & Stoica, 2001). Thus, the TLM models developed in the previous sections are used as a mean of acquiring the time signals transmitted and reflected in a region of interest within the medium (plaque or inclusion location). These signals will be considered as inputs and outputs to the dynamic system where digital signal processing techniques are employed to identify a parametric model for these plaques.

#### **4.1 Persistency of excitation of the input signal**

Any input signal used in the context of system identification must meet certain condition. In particular, the input signal should be **persistently exciting** (Ljung, 1999). The frequency domain condition enforcing a persistency of excitation is:

*A signal u t*( ) *characterized by its spectrum* Φ ω *<sup>u</sup>* ( ) *is said to be persistently exciting if* 

( ) 0 Φ ω> *u for almost all* ω

*Thus the spectrum may be zero on a set of number of points (almost all definition).* 

One classical frequency-rich signal is the swept sine signal which is also known as the "chirp signal". The chirp signal is a single sine wave with a frequency that is changing continuously as a function of time. The general mathematical presentation of the swept sine wave is

$$
\mu(k) = A \sin \left( 2 \pi \mathfrak{P}(k) \* \frac{\left(k - 1\right)}{f\_s} + \mathfrak{q} \right) + B
$$

$$\beta(k) = f\_{\min} + \frac{(f\_{\max} - f\_{\min})}{2t\_{\text{target}}} \left(\frac{k-1}{f\_s}\right) \quad \text{where} \ f\_s \ge 2f\_{\max}$$

form

vectors.

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 177

where *z k*( ) is the output, *pi* ( ) *k* are the monomials of the different inputs up to certain degree *M* , *<sup>i</sup>* θ are the unknown parameters of the model to be estimated, ξ( ) *k* is the modeling error and *N* is the data length. Equation ,(15) can be transformed to the matrix

Given this formulation, a linear least squares problem emerges. The proposed OLS method systematically searches the entire regressor space (monomials) as precised in equation (16) to find the best error reduction set, transforms these optimal regressors into orthogonal components, and then perform final regressor identification based on the new orthogonal system. These estimates will be mapped back to the original parameter estimates with their relative regressors given in equations ,(15) and .(16). This is called Parameter Estimation (PE). Structure Selection (SS) algorithm is then applied where it is anticipated that a linear model will emerge. This procedure takes the estimated parameters and statistically prioritizes these regressors into the most significant regressor, second most significant

The second stage is characterized by the estimation of the model coefficients. A second system identification technique called *recursive least squares* (RLS) is used (Ljung, 1999). This

where *M*×<sup>1</sup> Θ∈ℜ is the unknown parameters of the model to be determined, *<sup>N</sup>* <sup>1</sup> *Y* <sup>×</sup> ∈ℜ is the output vector *N M P* <sup>×</sup> ∈ℜ is the information matrix which is function of the input and output

The utility of this method is to calculate the inverse of the information matrix. Based on an algorithm that is composed of three equations, the inverse matrix is simply calculated by means of additions and multiplications. Finally once the inverse of the information matrix is

A set of inputs were designed. This set was composed of a swept sine, a Schroeder wave, a pulse and a band limited white noise. Swept sine and Schroeder wave signals were the more appropriate candidates since they are characterized by their frequency-rich content and their persistent excitation property. During the model structure identification all the considered inputs except the swept sine gave different model structure of the plaque while its properties were changed. That is why, the swept sine signal was considered to be the best input that captures the dynamics of the studied plaques. The OLS algorithm is applied to the input/output sets of data and a discrete parametric model is established for the plaque.

where *y* ( ) *k* is the model output of the plaque and *u k*( ) is the input to the plaque. In order to investigate the effect of plaque acoustic properties variation on the model, a first order

regressor and so on until accuracy of the model output is realized.

method departs from a system of linear equations in the matrix form

found, the model coefficient vector Θ can be calculated from equation (17).

**4.3 Tissue characterization using regular and cylindrical irregular TLM models** 

The following simple first order linear model is generated for the different plaques

continuous model is derived from the input/output data sets

*Z P* = Θ+Ξ . (16)

*Y P* = Θ , (17)

() ( ) () 1 0 *y k a* = −+ *y k bu k* 1 , (18)

Where *A* is the wave amplitude, *B* is the signal bias term, ϕ is the phase angle of the wave and β( ) *k* is the time varying frequency of the swept sine in Hertz. The frequency *sf* is the sampling frequency. The frequency β( ) *k* in this case is a linearly varying frequency over the interval[ *f f* min max , ] . The target time, denoted as *t et* arg *t* , is the time for which the upper bound of the frequency range is achieved. During the system identification process of the plaque and healthy tissue characterization, a swept sine will be designed as the source signal (the choice of the swept sign came from the fact that this wave was the only signal that was consistent in terms of constancy of the model structure). From literature, the frequency range used in the signal processing for the soft tissue is in the range of 5 7 10 ,10 *Hz* . The swept sine is therefore designed such that the frequency covers this range. This signal will be combined with a zero-element vector. As illustrated in Fig. 18, a swept sine is designed to be the source signal of the simulation part for the TLM models. The sampling time of this signal is equal to 10-9 sec.

Fig. 18. Constructed swept sine pulse

#### **4.2 System identification method**

This process is composed of two stages. In the first stage, the identification technique that is used for modeling purposes is the so-called *Orthogonal Least Squares* (OLS) method (Korenberg et al., 1988; Chen et al., 1989). This method is a discrete time domain based approach where the time signals are used for model determination. In fact, the transient time domain information generated from the TLM artery models and their delayed components will be used as possible input regressors. This method will determine the most significant regressors from a broad range of possible candidates to identify the best parametric model. The general model structure can be linear or nonlinear. However for this work, it is anticipated that only a linear model will be needed.

A discrete time model generally resembles a polynomial structure. Considering a general case, a discrete system model with unknown coefficients (model parameters to be estimate) can be transformed into the linear-in-the-parameters representation by means of the expansion

$$z(k) = \sum\_{i=1}^{M} p\_i(k)\boldsymbol{\Theta}\_i + \mathsf{f}\_i(k), \quad k = 1, \ldots, N \; \; \tag{15}$$

Where *A* is the wave amplitude, *B* is the signal bias term, ϕ is the phase angle of the wave and β( ) *k* is the time varying frequency of the swept sine in Hertz. The frequency *sf* is the sampling frequency. The frequency β( ) *k* in this case is a linearly varying frequency over the interval[ *f f* min max , ] . The target time, denoted as *t et* arg *t* , is the time for which the upper bound of the frequency range is achieved. During the system identification process of the plaque and healthy tissue characterization, a swept sine will be designed as the source signal (the choice of the swept sign came from the fact that this wave was the only signal that was consistent in terms of constancy of the model structure). From literature, the frequency range used in the signal processing for the soft tissue is in the range of 5 7 10 ,10 *Hz* . The swept sine is therefore designed such that the frequency covers this range. This signal will be combined with a zero-element vector. As illustrated in Fig. 18, a swept sine is designed to be the source signal of the simulation part for the TLM models.

This process is composed of two stages. In the first stage, the identification technique that is used for modeling purposes is the so-called *Orthogonal Least Squares* (OLS) method (Korenberg et al., 1988; Chen et al., 1989). This method is a discrete time domain based approach where the time signals are used for model determination. In fact, the transient time domain information generated from the TLM artery models and their delayed components will be used as possible input regressors. This method will determine the most significant regressors from a broad range of possible candidates to identify the best parametric model. The general model structure can be linear or nonlinear. However for this

A discrete time model generally resembles a polynomial structure. Considering a general case, a discrete system model with unknown coefficients (model parameters to be estimate) can be transformed into the linear-in-the-parameters representation by means of the expansion

*z k p k kk N*

, 1,...,

= θ +ξ = , (15)

() () () 1

*i i*

*M*

*i*

=

The sampling time of this signal is equal to 10-9 sec.

Fig. 18. Constructed swept sine pulse

**4.2 System identification method** 

work, it is anticipated that only a linear model will be needed.

where *z k*( ) is the output, *pi* ( ) *k* are the monomials of the different inputs up to certain degree *M* , *<sup>i</sup>* θ are the unknown parameters of the model to be estimated, ξ( ) *k* is the modeling error and *N* is the data length. Equation ,(15) can be transformed to the matrix form

$$Z = P\Theta + \Xi \text{ .} \tag{16}$$

Given this formulation, a linear least squares problem emerges. The proposed OLS method systematically searches the entire regressor space (monomials) as precised in equation (16) to find the best error reduction set, transforms these optimal regressors into orthogonal components, and then perform final regressor identification based on the new orthogonal system. These estimates will be mapped back to the original parameter estimates with their relative regressors given in equations ,(15) and .(16). This is called Parameter Estimation (PE). Structure Selection (SS) algorithm is then applied where it is anticipated that a linear model will emerge. This procedure takes the estimated parameters and statistically prioritizes these regressors into the most significant regressor, second most significant regressor and so on until accuracy of the model output is realized.

The second stage is characterized by the estimation of the model coefficients. A second system identification technique called *recursive least squares* (RLS) is used (Ljung, 1999). This method departs from a system of linear equations in the matrix form

*Y P* = Θ , (17)

where *M*×<sup>1</sup> Θ∈ℜ is the unknown parameters of the model to be determined, *<sup>N</sup>* <sup>1</sup> *Y* <sup>×</sup> ∈ℜ is the output vector *N M P* <sup>×</sup> ∈ℜ is the information matrix which is function of the input and output vectors.

The utility of this method is to calculate the inverse of the information matrix. Based on an algorithm that is composed of three equations, the inverse matrix is simply calculated by means of additions and multiplications. Finally once the inverse of the information matrix is found, the model coefficient vector Θ can be calculated from equation (17).

#### **4.3 Tissue characterization using regular and cylindrical irregular TLM models**

A set of inputs were designed. This set was composed of a swept sine, a Schroeder wave, a pulse and a band limited white noise. Swept sine and Schroeder wave signals were the more appropriate candidates since they are characterized by their frequency-rich content and their persistent excitation property. During the model structure identification all the considered inputs except the swept sine gave different model structure of the plaque while its properties were changed. That is why, the swept sine signal was considered to be the best input that captures the dynamics of the studied plaques. The OLS algorithm is applied to the input/output sets of data and a discrete parametric model is established for the plaque. The following simple first order linear model is generated for the different plaques

$$y(k) = a\_1 y(k-1) + b\_0 u(k) \, , \tag{18}$$

where *y* ( ) *k* is the model output of the plaque and *u k*( ) is the input to the plaque. In order to investigate the effect of plaque acoustic properties variation on the model, a first order continuous model is derived from the input/output data sets

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 179

Table 2 confirms that the DC gain is indeed decreasing when the acoustic impedance of the plaque in increased. Moreover, the time constant ߬ (indicator of the time response of the system) is decreasing likewise the DC gain when the acoustic impedance is increased. This is explained physically by the fact that the increase of the hardness of the tissue (the plaque) will affect the speed of the system response. The coefficients percentage variations are

> DC gain ݀

Z=1.2xZhealthyTissue 20 0.5171 -8.22 21.95 -0.90 Z=1.4xZhealthyTissue 40 0.4778 -15.19 21.81 -1.50 Z=1.6xZhealthyTissue 60 0.4442 -21.16 21.71 -1.99 Z=1.8xZhealthyTissue 80 0.4149 -26.36 21.64 -2.30 Z=2xZhealthyTissue 100 0.3893 -30.90 21.61 -2.44

Table 3. DC gain and Time constant variation in percentage (rectangular TLM model)

impedance of the plaque is increased and this is what is presented in Table 4.

Acoustic Impedance [ܭ݃݉ିଶݏିଵ] DC gain ݀ Time Constant ߬ ZhealthyTissue=1559216 0.5275 26.42 Z=1.2xZhealthyTissue 0.5224 25.04 Z=1.4xZhealthyTissue 0.5090 23.28 Z=1.6xZhealthyTissue 0.4910 21.34 Z=1.8xZhealthyTissue 0.4699 19.30 Z=2xZhealthyTissue 0.4472 17.28

Table 4. DC gain and Time constant variation as function of the acoustic impedance of the

plaque (cylindrical irregular TLM model)

Using the cylindrical irregular TLM model, the same plaque size and location as of the regular TLM model is considered. The plaque is located between the 10th and 30th radial nodes and 25th and 65th angular nodes. The same designed swept sine signal is injected at the 1st radial and 45th angular node. The 45th angular direction coincides with the middle line crossing the plaque. The input (10th radial position) and output (31st radial position) signals to the plaque are recorded. To study the plaque type effect on the model coefficients, the variation of the DC gain and pole location is studied as function of the plaque density variation. Therefore the speed is set constant and the density of the plaque is varying with respect the healthy tissue density. The same approximations are used to determine the coefficients of the continuous model. As in the case of the regular TLM model section, it is expected that both the DC gain and the time constant to decrease when the acoustic

DC gain change [%]

Time Constant ߬

Time Constant change [%]

Acoustic impedance change [%]

summarized in Table 3.

Acoustic Impedance [ଵିݏଶ݃݉ିܭ]

$$
\pi \dot{y}(t) + y(t) = d u(t) \,. \tag{19}
$$

*d* is the DC gain and τ the time constant.

The DC gain and the time constant are determined using different approximations of the first derivative of the output, *y* ( )*t* . These approximations calculations were performed to

test the robustness of the model coefficients when recovering continuous model from discrete model. Multiple first time derivate approximations were performed to recover the continuous model calculations (Centered first order derivative approximation, Forward second order derivative approximation, Backward second order derivative approximation and Centered fourth order derivative approximation). The model coefficients were calculated and compared using these approximations and the error variation was negligible. The characterization of the plaque will be linked to the model coefficients and mainly the DC gain. The DC gain is expected to decrease if the impedance is increasing. This is explained by the fact that if the acoustic impedance is going up then the density of the plaque is increasing, meaning that this portion of tissue is getting harder and denser mechanically. A denser material has a repulsive effect and the transmitted signal into it is minor. This means that the denser the material is the more resistive effect it shows. Therefore if the impedance goes up then the DC gain is expected to decrease.

In the TLM model, the plaque acoustic impedance is increased gradually and the input/output data sets to this plaque are recorded. The model coefficients (DC gain and pole location) are calculated.

Table 2 illustrates the results of the first order model of the plaque that is obtained from the rectangular TLM model. This model is characterized by a medium that is composed of 90 by 300 nodes in the horizontal and vertical directions respectively and a plaque that is located between the 10th and 30th horizontal nodes and 25th and 65th vertical nodes. The designed swept sine signal is composed of 600 data points with a sampling time that is equal to 10-9 sec and a frequency range of 4 7 10 ,10 *Hz* . This input was injected at the 1st horizontal and 45th vertical node. The 45th vertical direction coincides with the middle line crossing the plaque. The input (10th radial position) and output (31st radial position) signals to the plaque were recorded.


Table 2. Time constant and DC gain variation as function of the acoustic impedance of the plaque (rectangular TLM model)

The DC gain and the time constant are determined using different approximations of the first derivative of the output, *y* ( )*t* . These approximations calculations were performed to test the robustness of the model coefficients when recovering continuous model from discrete model. Multiple first time derivate approximations were performed to recover the continuous model calculations (Centered first order derivative approximation, Forward second order derivative approximation, Backward second order derivative approximation and Centered fourth order derivative approximation). The model coefficients were calculated and compared using these approximations and the error variation was negligible. The characterization of the plaque will be linked to the model coefficients and mainly the DC gain. The DC gain is expected to decrease if the impedance is increasing. This is explained by the fact that if the acoustic impedance is going up then the density of the plaque is increasing, meaning that this portion of tissue is getting harder and denser mechanically. A denser material has a repulsive effect and the transmitted signal into it is minor. This means that the denser the material is the more resistive effect it shows.

Therefore if the impedance goes up then the DC gain is expected to decrease.

In the TLM model, the plaque acoustic impedance is increased gradually and the input/output data sets to this plaque are recorded. The model coefficients (DC gain and

Table 2 illustrates the results of the first order model of the plaque that is obtained from the rectangular TLM model. This model is characterized by a medium that is composed of 90 by 300 nodes in the horizontal and vertical directions respectively and a plaque that is located between the 10th and 30th horizontal nodes and 25th and 65th vertical nodes. The designed swept sine signal is composed of 600 data points with a sampling time that is equal to 10-9 sec and a frequency range of 4 7 10 ,10 *Hz* . This input was injected at the 1st horizontal and 45th vertical node. The 45th vertical direction coincides with the middle line crossing the plaque. The input (10th radial position) and output (31st radial position) signals to the plaque

> Acoustic Impedance [ܭ݃݉ିଶݏିଵ] DC gain d Time constant τ ZhealthyTissue=1559216 0.5634 22.15 Z=1.2xZhealthyTissue 0.5171 21.95 Z=1.4xZhealthyTissue 0.4778 21.81 Z=1.6xZhealthyTissue 0.4442 21.71 Z=1.8xZhealthyTissue 0.4149 21.64 Z=2xZhealthyTissue 0.3893 21.61

Table 2. Time constant and DC gain variation as function of the acoustic impedance of the

*d* is the DC gain and τ the time constant.

pole location) are calculated.

plaque (rectangular TLM model)

were recorded.

τ+ = *y* () () () *t y t du t* . (19)

Table 2 confirms that the DC gain is indeed decreasing when the acoustic impedance of the plaque in increased. Moreover, the time constant ߬ (indicator of the time response of the system) is decreasing likewise the DC gain when the acoustic impedance is increased. This is explained physically by the fact that the increase of the hardness of the tissue (the plaque) will affect the speed of the system response. The coefficients percentage variations are summarized in Table 3.



Using the cylindrical irregular TLM model, the same plaque size and location as of the regular TLM model is considered. The plaque is located between the 10th and 30th radial nodes and 25th and 65th angular nodes. The same designed swept sine signal is injected at the 1st radial and 45th angular node. The 45th angular direction coincides with the middle line crossing the plaque. The input (10th radial position) and output (31st radial position) signals to the plaque are recorded. To study the plaque type effect on the model coefficients, the variation of the DC gain and pole location is studied as function of the plaque density variation. Therefore the speed is set constant and the density of the plaque is varying with respect the healthy tissue density. The same approximations are used to determine the coefficients of the continuous model. As in the case of the regular TLM model section, it is expected that both the DC gain and the time constant to decrease when the acoustic impedance of the plaque is increased and this is what is presented in Table 4.


Table 4. DC gain and Time constant variation as function of the acoustic impedance of the plaque (cylindrical irregular TLM model)

Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 181

simple regularly-shaped medium (rectangular geometry) where a transmission line matrix (TLM) model was employed to capture the ultrasound wave propagation. In a second step an irregular TLM model was constructed based on a circular-shaped medium (disk) to simulate IVUS. Both of these models were based on the discretization of the medium where the Huygens principle was applied in the propagation process from one node to another. Moreover the propagating ultrasound waves were recorded in a digitized format in any

Advanced system identification techniques were, then, introduced and applied to characterize tissues. This approach used specific simulated waves in terms of locations to serve as the input/output data sets for the dynamic identification of these regions of interest. This characterization was based upon the construction of parametric models in the form of transfer function where its coefficients are directly related to each plaque type. A first order structure was, thus, found for all plaque types with different DC gain and time

Finally, a quantitative study was performed to link the variation of these two parameters with respect to acoustic properties. It has been shown consequently that these plaque characteristics were identified quantitatively based on the ultrasound waves using the

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location at any time specified during the numerical simulation.

constant values depending on the properties of these inclusions.

al%20Cardiovascular%20Disease%20%20Tables.pdf>

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system identification approach.

**6. References** 


It can be seen from both models that a plaque could be characterized by a first order system. In fact the coefficients variation of this model is inversely proportional to the acoustic impedance variation. The coefficients variations are summarized in Table 5.

Table 5. DC gain and Time constant variation in percentage (cylindrical irregular TLM model)

Considering the model structure found during the tissue characterization, the plaque can be viewed as *a first order low pass filter*. This first order filter illustrated in Fig. 19 is characterized by a DC gain and a time constant that decrease when the resistance *R*<sup>1</sup> is increasing.

Fig. 19. RL low pass filter

The transfer function of this filter is the following

$$TF = \overbrace{\begin{pmatrix} \frac{R\_2}{R\_1 + R\_2} \\ 1 + \frac{L}{R\_1 + R\_2}s \end{pmatrix}}^{R\_2} \tag{16}$$

The resistance *R*<sup>1</sup> and *R*2 can be linked to the acoustic impedance of the medium. From the transfer function above, if *R*<sup>1</sup> and *R*2 increases the DC gain and the time constant decrease.

#### **5. Conclusions**

In this paper, ultrasound wave propagation through biological tissues and specifically through arterial wall was studied. This modeling work was twofold. First it departed from a simple regularly-shaped medium (rectangular geometry) where a transmission line matrix (TLM) model was employed to capture the ultrasound wave propagation. In a second step an irregular TLM model was constructed based on a circular-shaped medium (disk) to simulate IVUS. Both of these models were based on the discretization of the medium where the Huygens principle was applied in the propagation process from one node to another. Moreover the propagating ultrasound waves were recorded in a digitized format in any location at any time specified during the numerical simulation.

Advanced system identification techniques were, then, introduced and applied to characterize tissues. This approach used specific simulated waves in terms of locations to serve as the input/output data sets for the dynamic identification of these regions of interest. This characterization was based upon the construction of parametric models in the form of transfer function where its coefficients are directly related to each plaque type. A first order structure was, thus, found for all plaque types with different DC gain and time constant values depending on the properties of these inclusions.

Finally, a quantitative study was performed to link the variation of these two parameters with respect to acoustic properties. It has been shown consequently that these plaque characteristics were identified quantitatively based on the ultrasound waves using the system identification approach.

#### **6. References**

180 Intravascular Ultrasound

It can be seen from both models that a plaque could be characterized by a first order system. In fact the coefficients variation of this model is inversely proportional to the acoustic

> DC gain ݀

Z=1.2xZhealthyTissue 20 0.5224 -0.97 25.04 -5.22 Z=1.4xZhealthyTissue 40 0.5090 -3.51 23.28 -11.88 Z=1.6xZhealthyTissue 60 0.4910 -6.92 21.34 -19.23 Z=1.8xZhealthyTissue 80 0.4699 -10.92 19.30 -26.95 Z=2xZhealthyTissue 100 0.4472 -15.22 17.28 -34.60

Table 5. DC gain and Time constant variation in percentage (cylindrical irregular TLM

Considering the model structure found during the tissue characterization, the plaque can be viewed as *a first order low pass filter*. This first order filter illustrated in Fig. 19 is characterized by a DC gain and a time constant that decrease when the resistance *R*<sup>1</sup> is

> 2 1 2

The resistance *R*<sup>1</sup> and *R*2 can be linked to the acoustic impedance of the medium. From the transfer function above, if *R*<sup>1</sup> and *R*2 increases the DC gain and the time constant decrease.

In this paper, ultrasound wave propagation through biological tissues and specifically through arterial wall was studied. This modeling work was twofold. First it departed from a

*R R R*

*TF* <sup>+</sup>

1 2 1

*<sup>L</sup> <sup>s</sup> R R*

= . (16)

<sup>+</sup> <sup>+</sup>

DC gain change [%]

Time Constant ߬

Time Constant change [%]

impedance variation. The coefficients variations are summarized in Table 5.

Acoustic impedance change [%]

Acoustic Impedance [ଵିݏଶ݃݉ିܭ]

model)

increasing.

Fig. 19. RL low pass filter

**5. Conclusions** 

The transfer function of this filter is the following


Arterial Plaque Characterization Using IVUS Radio-Frequency Time Echoes 183

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**0**

**12**

*Bellaterra, Spain*

**The Benefits of IVUS Dynamics for Retrieving**

*Computer Science Dept. and Computer Vision Center, Universitat Autònoma de Barcelona*

Artery diseases are mainly caused by the accumulation of plaque (made up of a combination of blood, cholesterol, fat and cells) inside arterial walls (Fuster, 1994). Such plaque accumulation narrows the artery blood flow (stenosis) and makes arteries inflaming and being less flexible (atherosclerosis). Artery blood flow reduction is measured by the percentage of obstruction in vessel sections and is a usual measurement previous to decide which is the best treatment (either surgical or pharmacological) for an atherosclerotic lesion. Depending on the histological composition of the plaque, its (bio-mechanical) physical behavior will be different, making it more or less unstable (vulnerable plaques) and, thus, resulting in a different risk for the patient (Kakadiaris et al., 2006). Early detection of plaque composition is a main step for planning the most suitable treatment (angioplasty, stent apposition, ...) and might prevent further thrombosis potentially leading to a fatal heart attack. Tissue bio-mechanical properties play an important role in the diagnosis and treatment of cardiovascular diseases. The main mechanical properties currently under study are radial strain, which is related to plaque type and vulnerability (Céspedes et al., 2000), and shear stress, which influences the probability of plaque accumulation (Wentzel et al., 2001). Both measures can be computed by means of the

IntraVascular UltraSound (IVUS) is the best choice to study, both, vessel morphology and its bio-mechanical properties. On one hand, inspection of a single IVUS image gives information about the percentage of stenosis. Manual stenosis measurements require a manual tracing of vessel borders (the internal layer, intima, and the most external one, adventitia). This is a very time-consuming task and might suffer from inter-observer variations. On the other hand, inspection of longitudinal views provides information about artery bio-mechanical properties. The assessment of bio-mechanical properties requires exploring the evolution of vessel walls and structures along the sequence. Dynamics due to heart pumping (among others) introduces a misalignment of sequence frames, preventing any feasible volumetric measurement or 3D reconstruction. In particular heart dynamics produce two types of motion: longitudinal motion along the catheter pullback and in-plane motion of each single cross section. Longitudinal dynamics produces a sequence block with spatially shuffled frames, which hinders any analysis along the sequence. Heart pumping also introduces a periodic rotation and translation in IVUS cross-sections, which hinders proper evaluation of tissue bio-mechanical properties. Both 3D reconstructions and bio-mechanical properties

study of vessel tissue deformation along the cardiac cycle.

**1. Introduction**

**Stable Models of Arteries**

Aura Hernàndez-Sabaté and Debora Gil


## **The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries**

Aura Hernàndez-Sabaté and Debora Gil

*Computer Science Dept. and Computer Vision Center, Universitat Autònoma de Barcelona Bellaterra, Spain*

#### **1. Introduction**

184 Intravascular Ultrasound

Korenberg, M.; Billings, S.A.; Liu, Y.P. & McIlroy, P.J. (1988). Orthogonal parameter

*Control*, Vol. 48, No. 1, (January 1988), pp. (193-210), ISSN 0020-7179 Chen, S.; Billings, S.A. & Luo, W. (1989). Orthogonal least squares methods and their

50, No. 5, (November 1989), pp. (1873 - 1896), ISSN 0020-7179

estimation algorithm for non-linear stochastic systems. *International Journal of* 

application to non-linear system identification. *International Journal of Control*, Vol.

Artery diseases are mainly caused by the accumulation of plaque (made up of a combination of blood, cholesterol, fat and cells) inside arterial walls (Fuster, 1994). Such plaque accumulation narrows the artery blood flow (stenosis) and makes arteries inflaming and being less flexible (atherosclerosis). Artery blood flow reduction is measured by the percentage of obstruction in vessel sections and is a usual measurement previous to decide which is the best treatment (either surgical or pharmacological) for an atherosclerotic lesion. Depending on the histological composition of the plaque, its (bio-mechanical) physical behavior will be different, making it more or less unstable (vulnerable plaques) and, thus, resulting in a different risk for the patient (Kakadiaris et al., 2006). Early detection of plaque composition is a main step for planning the most suitable treatment (angioplasty, stent apposition, ...) and might prevent further thrombosis potentially leading to a fatal heart attack. Tissue bio-mechanical properties play an important role in the diagnosis and treatment of cardiovascular diseases. The main mechanical properties currently under study are radial strain, which is related to plaque type and vulnerability (Céspedes et al., 2000), and shear stress, which influences the probability of plaque accumulation (Wentzel et al., 2001). Both measures can be computed by means of the study of vessel tissue deformation along the cardiac cycle.

IntraVascular UltraSound (IVUS) is the best choice to study, both, vessel morphology and its bio-mechanical properties. On one hand, inspection of a single IVUS image gives information about the percentage of stenosis. Manual stenosis measurements require a manual tracing of vessel borders (the internal layer, intima, and the most external one, adventitia). This is a very time-consuming task and might suffer from inter-observer variations. On the other hand, inspection of longitudinal views provides information about artery bio-mechanical properties. The assessment of bio-mechanical properties requires exploring the evolution of vessel walls and structures along the sequence. Dynamics due to heart pumping (among others) introduces a misalignment of sequence frames, preventing any feasible volumetric measurement or 3D reconstruction. In particular heart dynamics produce two types of motion: longitudinal motion along the catheter pullback and in-plane motion of each single cross section. Longitudinal dynamics produces a sequence block with spatially shuffled frames, which hinders any analysis along the sequence. Heart pumping also introduces a periodic rotation and translation in IVUS cross-sections, which hinders proper evaluation of tissue bio-mechanical properties. Both 3D reconstructions and bio-mechanical properties

Fig. 2. Pipeline for Image-based Cardiac Phase Retrieval

highlighted in orange.

Fig. 3. Pipeline for the Integrative Framework

**2. Rigid in-plane motion estimation**

methods will be given in the last section of the chapter.

component of in-plane motion as the signal reflecting cardiac motion.

using a band-pass filter in the second step and the extrema of filtered signals for sampling at end-systole and diastole. The main differences among existing algorithms and thus, the clue for an accurate cardiac phase retrieval, lie in the signal computed from the sequence. Given that in-plane and out-of-plane cardiac motion are coupled, we propose using the periodic

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 187

In this chapter we propose an integrative framework for retrieving vessel morphology and cardiac phase from IVUS rigid dynamics. Vessel structures extracted from IVUS sequences and stabilized by correcting cardiac dynamics produce stable models of arteries containing deformation along all cardiac cycle and, thus, useful for exploring biomechanics. The collection of vessel structures at frames synchronized at the same fraction of the cardiac cycle provide static models for computing 3D measurements. The pipeline of our integrative framework is sketched in figure 3 where the three clinical tools presented in the chapter are

The remainder of the chapter is structured as follows. In section 2 we sketch the method used to compute rigid in-plane motion (Hernàndez-Sabaté et al., 2009). Section 3 is devoted to detail the three steps which constitute the integrative framework we propose. In section 4 we explain the validation protocol while results are given in section 5. Finally, discussions about the advantages and limitations of using rigid in-plane dynamics compared to appearance

Different factors such as heart pumping, blood pressure or artery geometric properties mainly contribute to the dynamics of coronary arteries (Holzapfel et al., 2002; Mazumdar, 1992; Nadkarni et al., 2003). The first order approximation to vessel in-plane dynamics is given by a linear transformation combining translation, rotation and scaling (Waks et al., 1996). Dilation is inherent to the elasticity of the vessel itself and it does not preserve the metric. The rigid part of this approximation can be modeled as a rigid body motion and is given by a rotation

assessment require a compensation of artery dynamics, either by sampling the sequence synchronized with a cardiac phase or by in-plane sequence stabilization.

Since the early years of IVUS imaging, many algorithms for a reliable intima detection (Bouma et al., 1997; Brathwaite et al., 1996; Brathwaite & McPherson, 1998; Brusseau et al., 2004; Dijkstra et al., 2001; Gil et al., 2000; Hansen et al., 2002; Luo et al., 2003; Mendizabal-Ruiz et al., 2008; Sonka et al., 1996; von Birgelen et al., 1996; 1997) and plaque characterization (de Korte et al., 2000; Escalera et al., 2008; Granada et al., 2007; Nair et al., 2002; Okubo et al., 2008) have been proposed. Most of them are based on the appearance of structures in images. Adventitia modeling has been a delicate issue hardly addressed e.g. (Dijkstra et al., 1999; Gil et al., 2006; Haas et al., 2000; Klingensmith et al., 2000; Olszewski et al., 2004; Plissiti et al., 2004; Pujol & Radeva, 2005; Sonka et al., 1995; Takagi et al., 2000), though it is crucial for stenosis measurement. This is due to its weak appearance in IVUS images, which makes appearance-based techniques fail to produce optimal results and forces ad-hoc elaborated strategies. Also, image-based cardiac phase retrieval strategies are based on image appearance and extract cardiac phase by exploring its temporal changes across the sequence (Barajas et al., 2007; Matsumoto et al., 2008; Nadkarni et al., 2005; Sean M. O'Malley, 2006; Zhu et al., 2003). Speckle, texture and morphology introduce non-cardiac irregular variations in appearance patterns that must be carefully filtered.

So far, dynamics has only been considered as an artifact which is, at most, corrected (Hernàndez-Sabaté et al., 2009; Rosales et al., 2004). We claim that rigid motion estimation is a useful tool for exploring, both, vessel structures and cardiac dynamics. The main concern of this chapter is to show the benefits of cardiac dynamics for adventitia segmentation and image-based cardiac phase retrieval.

The general scheme for adventitia segmentation can be split in three main steps sketched in figure 1.

$$\begin{array}{c} \mathsf{F} \mathsf{VOL5} \quad \Big|\longrightarrow \begin{array}{c} \mathsf{F} \mathsf{R} \mathsf{E}\text{-} \mathsf{P} \mathsf{R} \mathsf{O} \mathsf{C} \mathsf{S} \mathsf{S} \mathsf{N} \mathsf{N} \mathsf{G} \end{array} \longrightarrow \begin{array}{c} \mathsf{F} \mathsf{E} \mathsf{A} \mathsf{T} \mathsf{U} \mathsf{R} \mathsf{E} \\ \mathsf{E} \mathsf{X} \mathsf{T} \mathsf{R} \mathsf{A} \mathsf{T} \mathsf{I} \mathsf{O} \mathsf{N} \end{array} \longrightarrow \begin{array}{c} \mathsf{A} \mathsf{D} \mathsf{V} \mathsf{E} \mathsf{N} \mathsf{T} \mathsf{T} \mathsf{I} \mathsf{A} \\ \mathsf{S} \mathsf{E} \mathsf{G} \mathsf{M} \mathsf{E} \mathsf{N} \mathsf{T} \mathsf{A} \mathsf{T} \mathsf{O} \mathsf{N} \end{array}$$

Fig. 1. Pipeline for Adventitia Segmentation

The poor image quality as well as large variety of IVUS artifacts (calcium, side-branches, shadows, catheter guide and blood back scatter) force an elaborated pre-processing step for enhancing adventitia appearance. In order to ensure a good compromise between preservation of the adventitia weak appearance and speckle smoothing, a filtering carefully driven for each image is compulsory (Gil et al., 2006; Unal et al., 2006). This makes the pre-processing stage to be one of the most computationally expensive tasks of the whole scheme. We claim that IVUS (in-plane) rigid motion can significantly improve the smoothing step, since vessel structures follow a periodic motion (induced by heart beat) clearly different from the chaotic random behavior of textured and blood areas. We propose using the mean of stabilized sequence blocks in order to enhance vessel structures while blurring texture and speckle.

Concerning image-based ECG-gating, existing strategies (Barajas et al., 2007; Matsumoto et al., 2008; Nadkarni et al., 2005; Sean M. O'Malley, 2006; Zhu et al., 2003) follow the scheme sketched in figure 2.

First, a signal reflecting cardiac motion is computed from IVUS sequences. Second, the signal is filtered (in the frequency domain) in order to remove non-cardiac phenomena and artifacts. Finally, a suitable sampling of the filtered signal retrieve cardiac phase. All authors agree in


Fig. 2. Pipeline for Image-based Cardiac Phase Retrieval

2 Will-be-set-by-IN-TECH

assessment require a compensation of artery dynamics, either by sampling the sequence

Since the early years of IVUS imaging, many algorithms for a reliable intima detection (Bouma et al., 1997; Brathwaite et al., 1996; Brathwaite & McPherson, 1998; Brusseau et al., 2004; Dijkstra et al., 2001; Gil et al., 2000; Hansen et al., 2002; Luo et al., 2003; Mendizabal-Ruiz et al., 2008; Sonka et al., 1996; von Birgelen et al., 1996; 1997) and plaque characterization (de Korte et al., 2000; Escalera et al., 2008; Granada et al., 2007; Nair et al., 2002; Okubo et al., 2008) have been proposed. Most of them are based on the appearance of structures in images. Adventitia modeling has been a delicate issue hardly addressed e.g. (Dijkstra et al., 1999; Gil et al., 2006; Haas et al., 2000; Klingensmith et al., 2000; Olszewski et al., 2004; Plissiti et al., 2004; Pujol & Radeva, 2005; Sonka et al., 1995; Takagi et al., 2000), though it is crucial for stenosis measurement. This is due to its weak appearance in IVUS images, which makes appearance-based techniques fail to produce optimal results and forces ad-hoc elaborated strategies. Also, image-based cardiac phase retrieval strategies are based on image appearance and extract cardiac phase by exploring its temporal changes across the sequence (Barajas et al., 2007; Matsumoto et al., 2008; Nadkarni et al., 2005; Sean M. O'Malley, 2006; Zhu et al., 2003). Speckle, texture and morphology introduce non-cardiac irregular variations in appearance

So far, dynamics has only been considered as an artifact which is, at most, corrected (Hernàndez-Sabaté et al., 2009; Rosales et al., 2004). We claim that rigid motion estimation is a useful tool for exploring, both, vessel structures and cardiac dynamics. The main concern of this chapter is to show the benefits of cardiac dynamics for adventitia segmentation and

The general scheme for adventitia segmentation can be split in three main steps sketched in

The poor image quality as well as large variety of IVUS artifacts (calcium, side-branches, shadows, catheter guide and blood back scatter) force an elaborated pre-processing step for enhancing adventitia appearance. In order to ensure a good compromise between preservation of the adventitia weak appearance and speckle smoothing, a filtering carefully driven for each image is compulsory (Gil et al., 2006; Unal et al., 2006). This makes the pre-processing stage to be one of the most computationally expensive tasks of the whole scheme. We claim that IVUS (in-plane) rigid motion can significantly improve the smoothing step, since vessel structures follow a periodic motion (induced by heart beat) clearly different from the chaotic random behavior of textured and blood areas. We propose using the mean of stabilized sequence blocks in order to enhance vessel structures while blurring texture and

Concerning image-based ECG-gating, existing strategies (Barajas et al., 2007; Matsumoto et al., 2008; Nadkarni et al., 2005; Sean M. O'Malley, 2006; Zhu et al., 2003) follow the scheme

First, a signal reflecting cardiac motion is computed from IVUS sequences. Second, the signal is filtered (in the frequency domain) in order to remove non-cardiac phenomena and artifacts. Finally, a suitable sampling of the filtered signal retrieve cardiac phase. All authors agree in

synchronized with a cardiac phase or by in-plane sequence stabilization.

patterns that must be carefully filtered.

image-based cardiac phase retrieval.

Fig. 1. Pipeline for Adventitia Segmentation

figure 1.

speckle.

sketched in figure 2.

using a band-pass filter in the second step and the extrema of filtered signals for sampling at end-systole and diastole. The main differences among existing algorithms and thus, the clue for an accurate cardiac phase retrieval, lie in the signal computed from the sequence. Given that in-plane and out-of-plane cardiac motion are coupled, we propose using the periodic component of in-plane motion as the signal reflecting cardiac motion.

In this chapter we propose an integrative framework for retrieving vessel morphology and cardiac phase from IVUS rigid dynamics. Vessel structures extracted from IVUS sequences and stabilized by correcting cardiac dynamics produce stable models of arteries containing deformation along all cardiac cycle and, thus, useful for exploring biomechanics. The collection of vessel structures at frames synchronized at the same fraction of the cardiac cycle provide static models for computing 3D measurements. The pipeline of our integrative framework is sketched in figure 3 where the three clinical tools presented in the chapter are highlighted in orange.

Fig. 3. Pipeline for the Integrative Framework

The remainder of the chapter is structured as follows. In section 2 we sketch the method used to compute rigid in-plane motion (Hernàndez-Sabaté et al., 2009). Section 3 is devoted to detail the three steps which constitute the integrative framework we propose. In section 4 we explain the validation protocol while results are given in section 5. Finally, discussions about the advantages and limitations of using rigid in-plane dynamics compared to appearance methods will be given in the last section of the chapter.

#### **2. Rigid in-plane motion estimation**

Different factors such as heart pumping, blood pressure or artery geometric properties mainly contribute to the dynamics of coronary arteries (Holzapfel et al., 2002; Mazumdar, 1992; Nadkarni et al., 2003). The first order approximation to vessel in-plane dynamics is given by a linear transformation combining translation, rotation and scaling (Waks et al., 1996). Dilation is inherent to the elasticity of the vessel itself and it does not preserve the metric. The rigid part of this approximation can be modeled as a rigid body motion and is given by a rotation

Finally, the following formula weights both centers of mass, taking into account the deviation

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 189

where *DR* is the vessel-catheter deviation rate (i.e. the deviation of the vessel from the center of the image). If we consider the maximum, *Rmax*, and minimum, *Rmin*, distances of the set

We note that in case the artery is centered at the catheter, *DR* measures its eccentricity. Figure 5 shows the computation of the Vessel Center of Mass from computation of the Image and

Once vessel translation has been compensated, two global motions still remain: rotation and radial scaling. In the polar domain with origin *VCM*, they convert into a horizontal translation (corresponding to rotation) and a vertical scaling (corresponding to radial scaling). In the case of human coronary arteries, scaling is very close to 1 (Ramírez, 2005), so *λ* = 1 + *ε* becomes a perturbation of identity given by *ε* (Hernàndez-Sabaté, 2009). The horizontal translation is estimated by means of the computation of the phase of the ratio of Fourier transforms of every

*I*2(*i*, *j*) = *I*1(*i* − *t*1, *j* − *t*2)

 *x*2 *<sup>k</sup>* <sup>+</sup> *<sup>y</sup>*<sup>2</sup> *k* )

*VCM* = *DR* · *ICM* + (1 − *DR*) · *GCM* (1)

<sup>=</sup> *Rmin Rmax*

of the vessel from the center of the image (Hernàndez-Sabaté et al., 2009):

*DR* <sup>=</sup> *mink*(

*maxk*( *x*2 *<sup>k</sup>* <sup>+</sup> *<sup>y</sup>*<sup>2</sup> *k* )

(*xk*, *yk*)*<sup>k</sup>* to the image center, *DR* is defined as:

Fig. 5. Computation of the Vessel Center of Mass

Geometric Centers of Mass given by formula (1).

two consecutive frames (Hernàndez-Sabaté et al., 2009).

That is, if *I*1, *I*<sup>2</sup> are two functions (images) that differ in a pure translation:

**2.2 Rotation**

followed by a translation. Figure 4 shows the physics-based model of the rigid motion of an artery. The computation of the translation and rotation angle is as follows (Hernàndez-Sabaté et al., 2009).

Fig. 4. Physics-based model: rigid solid motion

#### **2.1 Translation**

In body dynamics, the point describing the object response to external forces and torques is determined by means of its center of gravity or mass (Goldstein et al., 2002). The difference between its position and the origin of coordinates is identified to the object translation. We note it as *VCM* which is computed from IVUS frames as follows.

Since grey level reflects tissue mass density due to IVUS images reconstruction, the center of mass given by the image intensity, namely *ICM*, corresponds to the physical center of gravity of the vessel. However, some acquisition devices allow interactive tuning of the image brightness in order to enhance tissue and vessel structures appearance (Mintz & Nissen, 2001). Given that such intensity gain is radial (Caballero et al., 2006), tissue close to the catheter might look brighter and, for vessels not centered at the catheter, intensity gainings might deviate the position of *ICM* from the true center of mass. Vessel geometric center, namely *GCM*, coincides with the vessel center of gravity only in the case of uniform tissue density. However, it serves to compensate the deviation of *ICM* for non centered vessels. We define the center of mass of the vessel, *VCM*, by a combination of *ICM* and *GCM* achieving a good compromise between vessels whose intensity gain has been tuned and vessels with uniform tissue density. The center of mass of the image intensities is given by:

$$ICM = \left(\frac{\sum\_{i=1}^{n} i \sum\_{j=1}^{m} I(i, j)}{\sum\_{i=1}^{n} \sum\_{j=1}^{m} I(i, j)}, \frac{\sum\_{j=1}^{m} j \sum\_{i=1}^{n} I(i, j)}{\sum\_{i=1}^{n} \sum\_{j=1}^{m} I(i, j)}\right)$$

The geometric center of mass of a set of N points roughly lying on the adventitia (the most stable structure along the sequence) (*xk*, *yk*) is computed as follows:

$$GCM = \frac{1}{N} \left( \sum\_{k=1}^{N} \mathbf{x}\_{k'} \sum\_{k=1}^{N} y\_k \right)^2$$

Finally, the following formula weights both centers of mass, taking into account the deviation of the vessel from the center of the image (Hernàndez-Sabaté et al., 2009):

$$VCM = DR \cdot ICH + (1 - DR) \cdot COM \tag{1}$$

where *DR* is the vessel-catheter deviation rate (i.e. the deviation of the vessel from the center of the image). If we consider the maximum, *Rmax*, and minimum, *Rmin*, distances of the set (*xk*, *yk*)*<sup>k</sup>* to the image center, *DR* is defined as:

$$\begin{array}{ccccc} \text{lCM} & \text{GCM} & \text{DR} \\\\ \text{N} & \text{GCM} & \text{CS} \\\\ \text{N} & \text{GCM} & \text{CS} \\\\ \text{N} & \text{GCM} & \\\\ \text{N} & \text{GCM} & \\\\ \end{array}$$

*DR* <sup>=</sup> *mink*( *x*2 *<sup>k</sup>* <sup>+</sup> *<sup>y</sup>*<sup>2</sup> *k* ) *maxk*( *x*2 *<sup>k</sup>* <sup>+</sup> *<sup>y</sup>*<sup>2</sup> *k* ) <sup>=</sup> *Rmin Rmax*

Fig. 5. Computation of the Vessel Center of Mass

We note that in case the artery is centered at the catheter, *DR* measures its eccentricity. Figure 5 shows the computation of the Vessel Center of Mass from computation of the Image and Geometric Centers of Mass given by formula (1).

#### **2.2 Rotation**

4 Will-be-set-by-IN-TECH

followed by a translation. Figure 4 shows the physics-based model of the rigid motion of an artery. The computation of the translation and rotation angle is as follows (Hernàndez-Sabaté

In body dynamics, the point describing the object response to external forces and torques is determined by means of its center of gravity or mass (Goldstein et al., 2002). The difference between its position and the origin of coordinates is identified to the object translation. We

Since grey level reflects tissue mass density due to IVUS images reconstruction, the center of mass given by the image intensity, namely *ICM*, corresponds to the physical center of gravity of the vessel. However, some acquisition devices allow interactive tuning of the image brightness in order to enhance tissue and vessel structures appearance (Mintz & Nissen, 2001). Given that such intensity gain is radial (Caballero et al., 2006), tissue close to the catheter might look brighter and, for vessels not centered at the catheter, intensity gainings might deviate the position of *ICM* from the true center of mass. Vessel geometric center, namely *GCM*, coincides with the vessel center of gravity only in the case of uniform tissue density. However, it serves to compensate the deviation of *ICM* for non centered vessels. We define the center of mass of the vessel, *VCM*, by a combination of *ICM* and *GCM* achieving a good compromise between

vessels whose intensity gain has been tuned and vessels with uniform tissue density.

*<sup>j</sup>*=<sup>1</sup> *I*(*i*, *j*)

∑*<sup>m</sup> <sup>j</sup>*=<sup>1</sup> *<sup>j</sup>* <sup>∑</sup>*<sup>n</sup>*

∑*n <sup>i</sup>*=<sup>1</sup> <sup>∑</sup>*<sup>m</sup>*

*<sup>i</sup>*=<sup>1</sup> *I*(*i*, *j*)

*<sup>j</sup>*=<sup>1</sup> *I*(*i*, *j*)

*<sup>j</sup>*=<sup>1</sup> *<sup>I</sup>*(*i*, *<sup>j</sup>*) ,

The geometric center of mass of a set of N points roughly lying on the adventitia (the most

 *N* ∑ *k*=1 *xk*, *N* ∑ *k*=1 *yk* 

*<sup>i</sup>*=<sup>1</sup> *<sup>i</sup>* <sup>∑</sup>*<sup>m</sup>*

*GCM* <sup>=</sup> <sup>1</sup>

*N*

et al., 2009).

**2.1 Translation**

Fig. 4. Physics-based model: rigid solid motion

note it as *VCM* which is computed from IVUS frames as follows.

The center of mass of the image intensities is given by:

∑*<sup>n</sup>*

∑*n <sup>i</sup>*=<sup>1</sup> <sup>∑</sup>*<sup>m</sup>*

stable structure along the sequence) (*xk*, *yk*) is computed as follows:

*ICM* =

Once vessel translation has been compensated, two global motions still remain: rotation and radial scaling. In the polar domain with origin *VCM*, they convert into a horizontal translation (corresponding to rotation) and a vertical scaling (corresponding to radial scaling). In the case of human coronary arteries, scaling is very close to 1 (Ramírez, 2005), so *λ* = 1 + *ε* becomes a perturbation of identity given by *ε* (Hernàndez-Sabaté, 2009). The horizontal translation is estimated by means of the computation of the phase of the ratio of Fourier transforms of every two consecutive frames (Hernàndez-Sabaté et al., 2009).

That is, if *I*1, *I*<sup>2</sup> are two functions (images) that differ in a pure translation:

$$I\_2(i,j) = I\_1(i - t\_1, j - t\_2)$$

sequences hinders a properly 3D reconstruction and vessel measurements. Furthermore, vessel plaque assessment by analysis of IntraVascular UltraSound sequences is a useful tool for cardiac disease diagnosis and intervention. Manual detection of luminal (inner) and medial-adventitial (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts, and blurred signal response due to ultrasound physical properties

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 191

Fig. 7. Images extracted from an IVUS pullback. The left image is a block of 16 IVUS

consecutive frames from a constant pullback. The right top image is a single cross-section of the vessel. The right bottom image is a longitudinal view obtained by intersecting 401 frames

Figure 7 shows a block of IVUS images obtained from a pullback (on the left) and the two kind of images derived from them (on the right). Each sequence frame (on the top right) shows a cross-section of the vessel under study with a complete detail of its morphology. The frames on the left can be intersected by a longitudinal plane including the catheter trajectory (grey plane on fig.7, left graphic), defined by a fixed angle on cross sections. The image obtained in this way is called longitudinal cut of the artery (bottom-right image). The image misalignment can be appreciated in the echo-shadowing calcified plaque of the upper profile

A framework integrating the solution for the three limitations of IVUS (image misalignment, longitudinal motion and adventitia segmentation) should be of utmost importance for clinical practice. In the above section, we have presented a method for assessing IVUS rigid in-plane motion. This estimation allows us to compute the following three steps for achieving an integrative framework of stable models of arteries useful for clinical practice. On one hand, translation and rotation estimation serves to stabilize the sequence by removing cardiac dynamics. On the other side, we present the potential of rigid motion estimation for approaching cardiac phase retrieval from coronary IVUS sequences without ECG signal for

trouble automated adventitia segmentation.

with the grey plane at the same angle.

of the longitudinal cut.

the first order approximation to *I*<sup>2</sup> can be computed by applying the Fourier transform (Oppenheim & Willsky, 1997) and using phase correlation (Kuglin & Hines, 1975). Let *I*1, *I*<sup>2</sup> be the Fourier transforms of *I*<sup>1</sup> and *I*2, respectively, then they are related via:

$$
\widehat{I}\_2(\omega) = \widehat{I}\_1(\omega)e^{-i\langle \omega, t\rangle t}
$$

for *<sup>ω</sup>* = (*ω*1, *<sup>ω</sup>*2) the Fourier frequency, *<sup>t</sup>* = (*t*1, *<sup>t</sup>*2) and �*<sup>ω</sup>* ,*<sup>t</sup>*� <sup>=</sup> *<sup>ω</sup>*1*t*<sup>1</sup> <sup>+</sup> *<sup>ω</sup>*2*t*<sup>2</sup> the Euclidean scalar product.

If we consider the phase, *ρ*(*ω*), of the ratio between the two Fourier transforms (Alliney, 1993), then we have that:

$$\rho(\omega) = \rho\left(\frac{\hat{I}\_2(\omega)}{\hat{I}\_1(\omega)}\right) = \rho\left(e^{-i\langle\omega,t\rangle}\right) = \langle\omega,t\rangle \, = \omega\_1 t\_1 + \omega\_2 t\_2$$

so that the points (*ω*1, *ω*2, *ρ*(*ω*)) lie on a plane, Π, with the slopes given by the translation components:

$$\Pi: \rho(\omega) = t\_1\omega\_1 + t\_2\omega\_2$$

In practice, noise and texture introduce a scatter in the set (*ω*1, *ω*2, *ρ*(*ω*)), especially for

Fig. 6. Regression plane approximating Fourier phase correlation between two shifted images.

those frequencies with smaller amplitudes. We reduce noise-scatter by only considering those frequencies common to both images with an associated amplitude larger than a given percentile. Such frequencies with the phase *ρ* yield a point cloud, like the one shown in figure 6, which regression plane provides a least-square estimator of the plane Π. The first slope of that regression plane, *t*1, estimates the angle of rotation between two consecutive frames.

#### **3. Stable models of arteries**

Tissue bio-mechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation along the cardiac cycle. On one hand, image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. On the other hand, longitudinal motion artifacts in IVUS 6 Will-be-set-by-IN-TECH

the first order approximation to *I*<sup>2</sup> can be computed by applying the Fourier transform (Oppenheim & Willsky, 1997) and using phase correlation (Kuglin & Hines, 1975). Let *I*1,

for *<sup>ω</sup>* = (*ω*1, *<sup>ω</sup>*2) the Fourier frequency, *<sup>t</sup>* = (*t*1, *<sup>t</sup>*2) and �*<sup>ω</sup>* ,*<sup>t</sup>*� <sup>=</sup> *<sup>ω</sup>*1*t*<sup>1</sup> <sup>+</sup> *<sup>ω</sup>*2*t*<sup>2</sup> the Euclidean

If we consider the phase, *ρ*(*ω*), of the ratio between the two Fourier transforms (Alliney, 1993),

so that the points (*ω*1, *ω*2, *ρ*(*ω*)) lie on a plane, Π, with the slopes given by the translation

Π : *ρ*(*ω*) = *t*1*ω*<sup>1</sup> + *t*2*ω*<sup>2</sup> In practice, noise and texture introduce a scatter in the set (*ω*1, *ω*2, *ρ*(*ω*)), especially for

Fig. 6. Regression plane approximating Fourier phase correlation between two shifted

those frequencies with smaller amplitudes. We reduce noise-scatter by only considering those frequencies common to both images with an associated amplitude larger than a given percentile. Such frequencies with the phase *ρ* yield a point cloud, like the one shown in figure 6, which regression plane provides a least-square estimator of the plane Π. The first slope of that regression plane, *t*1, estimates the angle of rotation between two consecutive frames.

Tissue bio-mechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation along the cardiac cycle. On one hand, image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. On the other hand, longitudinal motion artifacts in IVUS

−*i*�*ω*,*t*�

= �*ω*, *t*� = *ω*1*t*<sup>1</sup> + *ω*2*t*<sup>2</sup>

*I*<sup>2</sup> be the Fourier transforms of *I*<sup>1</sup> and *I*2, respectively, then they are related via:

scalar product.

components:

images.

**3. Stable models of arteries**

then we have that:

*ρ*(*ω*) = *ρ*

 *<sup>I</sup>*2(*ω*) *I*1(*ω*)  = *ρ e* −*i*�*ω*,*t*� 

*I*2(*ω*) = *I*1(*ω*)*e*

sequences hinders a properly 3D reconstruction and vessel measurements. Furthermore, vessel plaque assessment by analysis of IntraVascular UltraSound sequences is a useful tool for cardiac disease diagnosis and intervention. Manual detection of luminal (inner) and medial-adventitial (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts, and blurred signal response due to ultrasound physical properties trouble automated adventitia segmentation.

Fig. 7. Images extracted from an IVUS pullback. The left image is a block of 16 IVUS consecutive frames from a constant pullback. The right top image is a single cross-section of the vessel. The right bottom image is a longitudinal view obtained by intersecting 401 frames with the grey plane at the same angle.

Figure 7 shows a block of IVUS images obtained from a pullback (on the left) and the two kind of images derived from them (on the right). Each sequence frame (on the top right) shows a cross-section of the vessel under study with a complete detail of its morphology. The frames on the left can be intersected by a longitudinal plane including the catheter trajectory (grey plane on fig.7, left graphic), defined by a fixed angle on cross sections. The image obtained in this way is called longitudinal cut of the artery (bottom-right image). The image misalignment can be appreciated in the echo-shadowing calcified plaque of the upper profile of the longitudinal cut.

A framework integrating the solution for the three limitations of IVUS (image misalignment, longitudinal motion and adventitia segmentation) should be of utmost importance for clinical practice. In the above section, we have presented a method for assessing IVUS rigid in-plane motion. This estimation allows us to compute the following three steps for achieving an integrative framework of stable models of arteries useful for clinical practice. On one hand, translation and rotation estimation serves to stabilize the sequence by removing cardiac dynamics. On the other side, we present the potential of rigid motion estimation for approaching cardiac phase retrieval from coronary IVUS sequences without ECG signal for

Since, even in healthy cases, the heart rate varies along the pullback, the peaks in the Fourier series are spread around the theoretic harmonic frequencies. The more irregularities in periodicity are, the more spread around the theoretic harmonic the Fourier development is. The harmonics less corrupted by noise are obtained by optical filtering (Klug & D.J.DeRosier, 1966). Optical filtering is a technique widely used in electron crystallography in order to discard harmonics corrupted with noise. Optical filtering selects only those harmonics presenting a prominent peak. The peakedness of an harmonic is given by the normalized difference between the amplitude achieved at the harmonic and an average of amplitudes in

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 193

*<sup>S</sup>* <sup>−</sup> <sup>1</sup>

where F stands for either t or *<sup>θ</sup>*, *<sup>S</sup>* = <sup>∑</sup>*x*∈*Ik<sup>ω</sup><sup>c</sup>* |*F*(*x*)| and *<sup>N</sup>* is the number of harmonics in *Ik<sup>ω</sup><sup>c</sup>* .

Harmonics selected by optical filtering are the only contributions to the sums in (3).

Fig. 8. Motion Decomposition. Rotation angle and its Fourier decomposition on the left;

Figure 8 shows the Fourier terms decoupling for the rotation angle in the top left plot. Vertical lines in the Fourier spectrum of the signal (bottom left plot) indicate the ranges defined for the 3 phenomena. Dots mark the 10 cardiac harmonics and squares the ones selected after optical

Finally, the linear application mapping the artery at a given time to the artery at time zero is

*<sup>x</sup>* <sup>−</sup> *VCM<sup>x</sup>*

*<sup>y</sup>* <sup>−</sup> *VCM<sup>y</sup> c* 

*c*

(4)

 cos(*θc*) <sup>−</sup> sin(*θc*) sin(*θc*) cos(*θc*)

geometric, breathing and cardiac terms on the right.

 *x*˜ *y*˜ =

given by:

filtering. The 3 components of the angle are shown in right plots.

*<sup>N</sup>* <sup>×</sup> *<sup>S</sup>* <sup>∑</sup> *<sup>x</sup>*∈*Ik<sup>ω</sup><sup>c</sup>* \*kω<sup>c</sup>*


a neighborhood *Ik<sup>ω</sup><sup>c</sup>* centered at the harmonic:

*OF*(*kωc*) = <sup>|</sup>*F*(*kωc*)<sup>|</sup>

correction of longitudinal motion artifacts. Finally, we show the benefits of using stabilized sequences for improving the computational time of automatic adventitia segmentation algorithms.

#### **3.1 Sequence stabilization**

The rigid motion that cardiac vessels undergo is a complex dynamical process which results from the combination of several contributions. In general, it presents a geometric component related to the artery 3D shape and a dynamic one induced by breathing and cardiac movements (Rosales et al., 2004). Depending on the particular problem to approach, each of the terms should have a specific treatment. Exploring artery geometry might be derived by analyzing the geometric component (Rotger et al., 2006), whereas extraction of cardiac dynamics concerns the cardiac dynamical contribution (Zhu et al., 2003). In the case of vessel biomechanics analysis, the goal is to produce a static model allowing a better tissue tracking along the segment. Firstly, the reader should note that, without further analysis, the geometric component does not reach a reliable 3D representation of the vessel geometry, which might lead to wrong static models. Secondly, even if one could infer the true 3D geometry from it, by compensating vessel tortuosity there is no guarantee of a better alignment of vessel plaque. This suggests only correcting the dynamical terms of the translation and rotation for stabilizing the sequence.

For that, the signal obtained is decoupled in the Fourier domain into geometric, breathing and cardiac component and the last component serves to stabilize the images along the sequence (Hernàndez-Sabaté, 2009). The translation and rotation parameters are functions of the time *s*. If the geometric term of a motion parameter is denoted by the subindex *<sup>g</sup>*, the cardiac term, induced by heart beating, is denoted by the subindex *<sup>c</sup>* and breathing contributions are denoted by the subindex *<sup>b</sup>*, the angle and translation decompose into:

$$\begin{aligned} t(s) &= t\_{\mathcal{S}}(s) + t\_b(s) + t\_c(s) \\ \theta(s) &= \theta\_{\mathcal{S}}(s) + \theta\_b(s) + \theta\_c(s) \end{aligned} \tag{2}$$

Focusing on the Fourier series of these components, breathing and cardiac terms are periodic and, thus, have a discrete Fourier spectrum, whereas geometry has a broad-band (non-discrete) spectrum (Oppenheim & Willsky, 1997). As usual, Fourier transforms are indicated by a hat ( ˆ ) over functions. Principal harmonics have been learned by supervised classification of the spectrum of a training set of 30 patients without apparent lesions used in a study for assessment of myocardial perfusion in contrast angiography (Gil et al., 2008). Confidence intervals of the 95% yield the expected ranges for the principal frequency of each of the periodic components. For breathing it is (10, 45) repetitions per minute (rpm), while for cardiac motion it is (45, 200) rpm. Thus, cardiac motion principal harmonic, *ωc*, is defined as the first local maximum in *Iω<sup>c</sup>* = (45, 200) rpm and the term is approximated by the first 10 harmonics, (*kωc*)*k*<sup>=</sup>1:10. For the sake of an efficient algorithm, *ω<sup>c</sup>* is approximated by the global maximum of Fourier transform amplitude for frequencies in the range *Iωc*. It follows that the cardiac motion term of a sequence lasting *NSec* seconds is given by:

$$t\_{\mathcal{C}}(\mathbf{s}) = \frac{1}{T} \sum\_{k=1}^{k=10} \widehat{t}(k\omega\_{\mathcal{C}}) e^{ik\omega\_{\mathcal{C}}s} \quad \theta\_{\mathcal{C}}(\mathbf{s}) = \frac{1}{T} \sum\_{k=1}^{k=10} \widehat{\theta}(k\omega\_{\mathcal{C}}) e^{ik\omega\_{\mathcal{C}}s}$$

where the period *T* = *NSec*/60 is the sequence length (in minutes) and defines the domain of integration.

8 Will-be-set-by-IN-TECH

correction of longitudinal motion artifacts. Finally, we show the benefits of using stabilized sequences for improving the computational time of automatic adventitia segmentation

The rigid motion that cardiac vessels undergo is a complex dynamical process which results from the combination of several contributions. In general, it presents a geometric component related to the artery 3D shape and a dynamic one induced by breathing and cardiac movements (Rosales et al., 2004). Depending on the particular problem to approach, each of the terms should have a specific treatment. Exploring artery geometry might be derived by analyzing the geometric component (Rotger et al., 2006), whereas extraction of cardiac dynamics concerns the cardiac dynamical contribution (Zhu et al., 2003). In the case of vessel biomechanics analysis, the goal is to produce a static model allowing a better tissue tracking along the segment. Firstly, the reader should note that, without further analysis, the geometric component does not reach a reliable 3D representation of the vessel geometry, which might lead to wrong static models. Secondly, even if one could infer the true 3D geometry from it, by compensating vessel tortuosity there is no guarantee of a better alignment of vessel plaque. This suggests only correcting the dynamical terms of the translation and rotation for

For that, the signal obtained is decoupled in the Fourier domain into geometric, breathing and cardiac component and the last component serves to stabilize the images along the sequence (Hernàndez-Sabaté, 2009). The translation and rotation parameters are functions of the time *s*. If the geometric term of a motion parameter is denoted by the subindex *<sup>g</sup>*, the cardiac term, induced by heart beating, is denoted by the subindex *<sup>c</sup>* and breathing contributions are

*θ*(*s*) = *θg*(*s*) + *θb*(*s*) + *θc*(*s*)

Focusing on the Fourier series of these components, breathing and cardiac terms are periodic and, thus, have a discrete Fourier spectrum, whereas geometry has a broad-band (non-discrete) spectrum (Oppenheim & Willsky, 1997). As usual, Fourier transforms are indicated by a hat ( ˆ ) over functions. Principal harmonics have been learned by supervised classification of the spectrum of a training set of 30 patients without apparent lesions used in a study for assessment of myocardial perfusion in contrast angiography (Gil et al., 2008). Confidence intervals of the 95% yield the expected ranges for the principal frequency of each of the periodic components. For breathing it is (10, 45) repetitions per minute (rpm), while for cardiac motion it is (45, 200) rpm. Thus, cardiac motion principal harmonic, *ωc*, is defined as the first local maximum in *Iω<sup>c</sup>* = (45, 200) rpm and the term is approximated by the first 10 harmonics, (*kωc*)*k*<sup>=</sup>1:10. For the sake of an efficient algorithm, *ω<sup>c</sup>* is approximated by the global maximum of Fourier transform amplitude for frequencies in the range *Iωc*. It follows

*ikω<sup>c</sup> <sup>s</sup> <sup>θ</sup>c*(*s*) = <sup>1</sup>

where the period *T* = *NSec*/60 is the sequence length (in minutes) and defines the domain of

*T*

*k*=10 ∑ *k*=1 *θ* (*kωc*)*e*

*ikω<sup>c</sup> s*

*t*(*s*) = *tg*(*s*) + *tb*(*s*) + *tc*(*s*) (2)

denoted by the subindex *<sup>b</sup>*, the angle and translation decompose into:

that the cardiac motion term of a sequence lasting *NSec* seconds is given by:

*t*(*kωc*)*e*

*tc*(*s*) = <sup>1</sup>

integration.

*T*

*k*=10 ∑ *k*=1

algorithms.

**3.1 Sequence stabilization**

stabilizing the sequence.

Since, even in healthy cases, the heart rate varies along the pullback, the peaks in the Fourier series are spread around the theoretic harmonic frequencies. The more irregularities in periodicity are, the more spread around the theoretic harmonic the Fourier development is. The harmonics less corrupted by noise are obtained by optical filtering (Klug & D.J.DeRosier, 1966). Optical filtering is a technique widely used in electron crystallography in order to discard harmonics corrupted with noise. Optical filtering selects only those harmonics presenting a prominent peak. The peakedness of an harmonic is given by the normalized difference between the amplitude achieved at the harmonic and an average of amplitudes in a neighborhood *Ik<sup>ω</sup><sup>c</sup>* centered at the harmonic:

$$OF(k\omega\_c) = \frac{|F(k\omega\_c)|}{S} - \frac{1}{N \times S} \sum\_{\mathbf{x} \in I\_{k\omega\_c}} |F(\mathbf{x})| \tag{3}$$

where F stands for either t or *<sup>θ</sup>*, *<sup>S</sup>* = <sup>∑</sup>*x*∈*Ik<sup>ω</sup><sup>c</sup>* |*F*(*x*)| and *<sup>N</sup>* is the number of harmonics in *Ik<sup>ω</sup><sup>c</sup>* . Harmonics selected by optical filtering are the only contributions to the sums in (3).

Fig. 8. Motion Decomposition. Rotation angle and its Fourier decomposition on the left; geometric, breathing and cardiac terms on the right.

Figure 8 shows the Fourier terms decoupling for the rotation angle in the top left plot. Vertical lines in the Fourier spectrum of the signal (bottom left plot) indicate the ranges defined for the 3 phenomena. Dots mark the 10 cardiac harmonics and squares the ones selected after optical filtering. The 3 components of the angle are shown in right plots.

Finally, the linear application mapping the artery at a given time to the artery at time zero is given by:

$$
\begin{pmatrix} \tilde{\mathfrak{x}} \\ \tilde{\mathfrak{y}} \end{pmatrix} = \begin{pmatrix} \cos(\theta\_{\mathcal{C}}) - \sin(\theta\_{\mathcal{C}}) \\ \sin(\theta\_{\mathcal{C}}) & \cos(\theta\_{\mathcal{C}}) \end{pmatrix} \begin{pmatrix} \mathfrak{x} - V\mathbf{C}M\_{\mathcal{C}}^{\mathbf{x}} \\ \mathfrak{y} - V\mathbf{C}M\_{\mathcal{C}}^{\mathbf{y}} \end{pmatrix} \tag{4}
$$

Fig. 10. Signal filtering with a Butterworth filter with parameters *n* = 2; *δ* = 0.1

Fig. 11. Original rotation motion profile and the corresponding filtered one.

for speeding up the process, since ˆ

Extrema positions are computed in the Fourier domain using the equation:

*f*

3. **Cardiac Phase Retrieval:** Maximums and minimums of the filtered signal give a sampling at end-systole and end-diastole and, thus, retrieve cardiac phase for each selected pixel.

<sup>=</sup> <sup>2</sup>*πi<sup>ω</sup>* <sup>ˆ</sup>

*f*

*f* has already been computed.

the cardiac phase.

Figure 11 plots the rotation motion profile on a longitudinal cut (on the left) and the profile filtered on the same cut (on the right). Note that the most prominent minimums and maximums of the cardiac profile, on the left, correspond to the minimums and maximums of the filtered signal on the right, though it is necessary to filter the signal in order to extract

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 195

for *VCMc* = (*VCM<sup>x</sup> <sup>c</sup>* , *VCM<sup>y</sup> <sup>c</sup>* ) the cardiac component of the position of the vessel center of mass and *θ<sup>c</sup>* the cardiac component of the angle of rotation in degrees.

#### **3.2 Cardiac phase retrieval**

The first step for modeling longitudinal motion in IVUS sequences is retrieving information about the cardiac phase. Following the general scheme shown in figure 9, our image-based algorithm to approach ECG sampling (Hernàndez-Sabaté et al., 2011) splits in the following three steps.

Fig. 9. Pipeline for Image-based Cardiac Phase Retrieval

#### 1. **Extraction of Signal Reflecting Cardiac Motion:**

By the physical coupling (Nadkarni et al., 2003), luminal area evolution is synchronized to other vessel cardiac phenomena, such as tissue motion or rigid motion. It follows that, since rigid in-plane motion comes from artery motion due to heart pumping, the angle of rotation is also synchronized to cardiac phase. In particular the periodic component, *θc*, given in Section 2 is a signal reflecting (pure) cardiac motion.

2. **Signal Filtering for Cardiac Profile Extraction:** Even in healthy subjects, cardiac frequency does not remain constant along the sequence. This artifact introduces (among other phenomena) irregularities in the Fourier transform of the cardiac motion profile. The irregularities distort the cardiac signal and corrupt the location of local extrema in the signal reflecting cardiac motion. Following the literature, we filter the cardiac profile with two families of band-pass filters centered at the cardiac frequency *ωc*: Butterworth (*B*) (Zhu et al., 2003) and Gaussian-based (*g*) (Matsumoto et al., 2008).

The Butterworth filter is defined as:

$$B(\omega) = \frac{1}{\sqrt{1 + \left(\frac{|\omega| - \omega\_\varepsilon}{0.6\Delta\omega\_\varepsilon}\right)^{2n}}}$$

where *n* is related to the filter decay and Δ*ω* = *δω<sup>c</sup>* to its support. Meanwhile, the Gaussian filter is defined as:

$$\mathcal{g}(\omega, \sigma) = \frac{1}{\sigma \sqrt{2\pi}} e^{-(|\omega| - \omega\_c)^2 / (2\sigma^2)}$$

In this case, the decay cannot be handled (it is always exponential) and only its support might be tuned by its deviation *σ*.

Figure 10 shows a signal reflecting cardiac motion filtered by a Butterworth filter with parameters *n* = 2, *δ* = 0.1. In the top left image, we present the original filter. The Fourier transform is computed and shown in the bottom left image. The result of the product between its Fourier transform and the filter is shown in the bottom right image. The final result is shown in the top right image.

The real part of the inverse Fourier transform of the filtered cardiac profile is a smooth signal suitable for cardiac phase retrieval. Regardless of the filter used we will denote it by *Filt*.

10 Will-be-set-by-IN-TECH

The first step for modeling longitudinal motion in IVUS sequences is retrieving information about the cardiac phase. Following the general scheme shown in figure 9, our image-based algorithm to approach ECG sampling (Hernàndez-Sabaté et al., 2011) splits in the following

By the physical coupling (Nadkarni et al., 2003), luminal area evolution is synchronized to other vessel cardiac phenomena, such as tissue motion or rigid motion. It follows that, since rigid in-plane motion comes from artery motion due to heart pumping, the angle of rotation is also synchronized to cardiac phase. In particular the periodic component, *θc*,

2. **Signal Filtering for Cardiac Profile Extraction:** Even in healthy subjects, cardiac frequency does not remain constant along the sequence. This artifact introduces (among other phenomena) irregularities in the Fourier transform of the cardiac motion profile. The irregularities distort the cardiac signal and corrupt the location of local extrema in the signal reflecting cardiac motion. Following the literature, we filter the cardiac profile with two families of band-pass filters centered at the cardiac frequency *ωc*: Butterworth (*B*)

> *<sup>B</sup>*(*ω*) = <sup>1</sup> 1 +

where *n* is related to the filter decay and Δ*ω* = *δω<sup>c</sup>* to its support. Meanwhile, the Gaussian

In this case, the decay cannot be handled (it is always exponential) and only its support

Figure 10 shows a signal reflecting cardiac motion filtered by a Butterworth filter with parameters *n* = 2, *δ* = 0.1. In the top left image, we present the original filter. The Fourier transform is computed and shown in the bottom left image. The result of the product between its Fourier transform and the filter is shown in the bottom right image. The final

The real part of the inverse Fourier transform of the filtered cardiac profile is a smooth signal suitable for cardiac phase retrieval. Regardless of the filter used we will denote it by

 <sup>|</sup>*ω*|−*ω<sup>c</sup>* 0.6Δ*ω<sup>c</sup>*

<sup>2</sup>*<sup>n</sup>*

<sup>−</sup>(|*ω*|−*ω<sup>c</sup>* )2/(2*σ*<sup>2</sup>)

*<sup>c</sup>* ) the cardiac component of the position of the vessel center of

for *VCMc* = (*VCM<sup>x</sup>*

three steps.

**3.2 Cardiac phase retrieval**

*<sup>c</sup>* , *VCM<sup>y</sup>*

Fig. 9. Pipeline for Image-based Cardiac Phase Retrieval

given in Section 2 is a signal reflecting (pure) cardiac motion.

(Zhu et al., 2003) and Gaussian-based (*g*) (Matsumoto et al., 2008).

*<sup>g</sup>*(*ω*, *<sup>σ</sup>*) = <sup>1</sup>

*σ* <sup>√</sup>2*<sup>π</sup> e*

1. **Extraction of Signal Reflecting Cardiac Motion:**

The Butterworth filter is defined as:

might be tuned by its deviation *σ*.

result is shown in the top right image.

filter is defined as:

*Filt*.

mass and *θ<sup>c</sup>* the cardiac component of the angle of rotation in degrees.

Fig. 10. Signal filtering with a Butterworth filter with parameters *n* = 2; *δ* = 0.1

Figure 11 plots the rotation motion profile on a longitudinal cut (on the left) and the profile filtered on the same cut (on the right). Note that the most prominent minimums and maximums of the cardiac profile, on the left, correspond to the minimums and maximums of the filtered signal on the right, though it is necessary to filter the signal in order to extract the cardiac phase.

Fig. 11. Original rotation motion profile and the corresponding filtered one.

3. **Cardiac Phase Retrieval:** Maximums and minimums of the filtered signal give a sampling at end-systole and end-diastole and, thus, retrieve cardiac phase for each selected pixel. Extrema positions are computed in the Fourier domain using the equation:

$$
\hat{f'} = 2\pi i \omega \hat{f}
$$

for speeding up the process, since ˆ *f* has already been computed.

Fig. 13. Enhancement of vessel structures by using a diffusion filter (center images) and the

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 197

in (Hernàndez-Sabaté et al., 2009), we prefer only to visually illustrate the quality of stabilizations. Cardiac motion introduces a misalignment in IVUS images, as well as, irregular profiles in longitudinal cuts. Therefore, the quality of stabilizations will be visually checked by longitudinal cuts obtained from original sequences and after sequence stabilization.

For the assessment of cardiac phase retrieval, we have compared the automatic phase retrieval to a manual sampling of the sequence. Automatic samplings were compared to the frames achieving extrema lumen areas. These extrema were manually detected by exploring longitudinal cuts by selecting minimums and maximums of intima/lumen and media-adventitia transition profiles. The distances between each manual detected frame and

the sequence for a manual and automatic sampling respectively, we define their distance as

The distances of all frames provide a distance map for each patient. As for in-plane dynamics, we retrieve a single quantity for each sequence (seq) by averaging *E<sup>k</sup>* over all sampled frames

Statistical ranges (given by the mean ± the variance, *μ* ± *σ*) of errors for all patients indicate

In order to detect if there are any significant differences among smoothing filters (that is, a best/worst performer), we have used the multiple comparison methodology (Nemenyi test) proposed in (Demsar, 2006). For each sequence (trial) the M filters (there are 12 in our case and might be considered as classifiers) are ranked according to their errors. The ranking assigns 1 to the best performer and M for the worst one. The average ranks are statistically compared to find out if there are any significant differences. The significance level for computing and

Finally, we have checked the benefits of using dynamic quantities by comparing results to the ones obtained using gray-intensity cardiac signals (Hernàndez-Sabaté et al., 2011).

*<sup>k</sup>* <sup>−</sup> *<sup>s</sup>*˜ *k*|

> *N* ∑ *k*=1 *Ek*

*<sup>E</sup><sup>k</sup>* <sup>=</sup> <sup>|</sup>*<sup>s</sup>*

*E*1 *seq* <sup>=</sup> <sup>1</sup> *N* *<sup>k</sup>* are frame positions in

the automatic one most close to it were computed. That is, if *s<sup>k</sup>* and *s*˜

mean of stabilized sequences (left images).

the absolute differences between their positions:

the accuracy of each of the method.

comparing ranks in the Nemenyi test is 0.1.

**4.2 Cardiac phase retrieval**

(N):

#### **3.3 Vessel structures detection**

The strategy for media-adventitia (simply adventitia from now on) segmentation we suggest follows the general scheme presented in (Gil et al., 2006) summarized in figure 12. First, a pre-processing step simplifies the appearance of adventitia, as well as, enhances significant structures while removing noise and textured tissue. Second, the feature extraction task computes two different masks and, by combining them, we obtain those points that most probably correspond to the adventitia layer. Finally, a closing stage delineates the adventitia layer.

Fig. 12. Adventitia Detection Flow (Gil et al., 2006)

In the pre-processing step, in order to enhance significant structures while removing noise and textured tissue, some kind of filtering is necessary. The most extended way of preserving adventitia thin structure (Gil et al., 2006; Takagi et al., 2000) is by using anisotropic filtering, like the Structure Preserving Diffusion (SPD) introduced in (Gil et al., 2010). Given that such diffusions are computed by means of iterative schemes, the filtering step is, generally, the most time consuming task of the algorithm. For instance, the SPD filtering used in (Gil et al., 2006) takes about the half of the total time and it can consume up to 1.54 seconds per frame. We observe that, after rigid motion compensation, image pixel intensity, which is related to tissue density of mass, remains more uniform along frames. It follows that the mean of stabilized sequence blocks enhances vessel structures, while blurring texture and speckle. We propose replacing the SPD by the mean of stabilized sequences, namely MSS. The remaining steps of the process are the same reported in (Gil et al., 2006). Figure 13 shows the same image given in the general scheme of fig. 12 filtered using SPD diffusion and MSS. For a better comparison across filters, we show images in cartesian (top) and polar (bottom) domains.

#### **4. Validation protocol**

#### **4.1 Sequence stabilization**

The quality of sequence stabilization exclusively relies on the accuracy of the estimated parameters of rigid in-plane motion. Given that their accuracy has been assessed

Fig. 13. Enhancement of vessel structures by using a diffusion filter (center images) and the mean of stabilized sequences (left images).

in (Hernàndez-Sabaté et al., 2009), we prefer only to visually illustrate the quality of stabilizations. Cardiac motion introduces a misalignment in IVUS images, as well as, irregular profiles in longitudinal cuts. Therefore, the quality of stabilizations will be visually checked by longitudinal cuts obtained from original sequences and after sequence stabilization.

#### **4.2 Cardiac phase retrieval**

12 Will-be-set-by-IN-TECH

The strategy for media-adventitia (simply adventitia from now on) segmentation we suggest follows the general scheme presented in (Gil et al., 2006) summarized in figure 12. First, a pre-processing step simplifies the appearance of adventitia, as well as, enhances significant structures while removing noise and textured tissue. Second, the feature extraction task computes two different masks and, by combining them, we obtain those points that most probably correspond to the adventitia layer. Finally, a closing stage delineates the adventitia

In the pre-processing step, in order to enhance significant structures while removing noise and textured tissue, some kind of filtering is necessary. The most extended way of preserving adventitia thin structure (Gil et al., 2006; Takagi et al., 2000) is by using anisotropic filtering, like the Structure Preserving Diffusion (SPD) introduced in (Gil et al., 2010). Given that such diffusions are computed by means of iterative schemes, the filtering step is, generally, the most time consuming task of the algorithm. For instance, the SPD filtering used in (Gil et al., 2006) takes about the half of the total time and it can consume up to 1.54 seconds per frame. We observe that, after rigid motion compensation, image pixel intensity, which is related to tissue density of mass, remains more uniform along frames. It follows that the mean of stabilized sequence blocks enhances vessel structures, while blurring texture and speckle. We propose replacing the SPD by the mean of stabilized sequences, namely MSS. The remaining steps of the process are the same reported in (Gil et al., 2006). Figure 13 shows the same image given in the general scheme of fig. 12 filtered using SPD diffusion and MSS. For a better comparison across filters, we show images in cartesian (top) and polar (bottom) domains.

The quality of sequence stabilization exclusively relies on the accuracy of the estimated parameters of rigid in-plane motion. Given that their accuracy has been assessed

**3.3 Vessel structures detection**

Fig. 12. Adventitia Detection Flow (Gil et al., 2006)

**4. Validation protocol**

**4.1 Sequence stabilization**

layer.

For the assessment of cardiac phase retrieval, we have compared the automatic phase retrieval to a manual sampling of the sequence. Automatic samplings were compared to the frames achieving extrema lumen areas. These extrema were manually detected by exploring longitudinal cuts by selecting minimums and maximums of intima/lumen and media-adventitia transition profiles. The distances between each manual detected frame and the automatic one most close to it were computed. That is, if *s<sup>k</sup>* and *s*˜ *<sup>k</sup>* are frame positions in the sequence for a manual and automatic sampling respectively, we define their distance as the absolute differences between their positions:

$$E^k = |s^k - \mathfrak{s}^k|.$$

The distances of all frames provide a distance map for each patient. As for in-plane dynamics, we retrieve a single quantity for each sequence (seq) by averaging *E<sup>k</sup>* over all sampled frames (N):

$$E\_{seq}^1 = \frac{1}{N} \sum\_{k=1}^N E^k$$

Statistical ranges (given by the mean ± the variance, *μ* ± *σ*) of errors for all patients indicate the accuracy of each of the method.

In order to detect if there are any significant differences among smoothing filters (that is, a best/worst performer), we have used the multiple comparison methodology (Nemenyi test) proposed in (Demsar, 2006). For each sequence (trial) the M filters (there are 12 in our case and might be considered as classifiers) are ranked according to their errors. The ranking assigns 1 to the best performer and M for the worst one. The average ranks are statistically compared to find out if there are any significant differences. The significance level for computing and comparing ranks in the Nemenyi test is 0.1.

Finally, we have checked the benefits of using dynamic quantities by comparing results to the ones obtained using gray-intensity cardiac signals (Hernàndez-Sabaté et al., 2011).

the ratio between both segmentation techniques (SPD/MSS) and the ratio taking into account

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 199

Since we want to compare MSS filtering to the anisotropic filtering used in (Gil et al., 2006), the experimental setting is the same reported in (Gil et al., 2006). A total number of 5400 images extracted from 22 vessel segments of a length ranging from 4 to 6 mm (200-300 frames). Sequences were recorded with a Boston Scientific Clear View Ultra scanner at 40 MHz with

Figure 14 shows two longitudinal cuts taken at the white lines on the IVUS left image and the same cut after sequence alignment. Each IVUS image cuts present the two main artifacts induced by vessel dynamics in *in vivo* pullbacks. The upper longitudinal cuts show the saw-tooth-shape pattern of the vessel intima wall (dark line) introduced by relative vessel-catheter translation. The profile of bottom cuts presents a structure misalignment due to the relative vessel-catheter rotation for an echo-shadowing calcified plaque. After sequence stabilization, the vessel wall profiles of upper cuts are straight and continuous, whereas

As in (Hernàndez-Sabaté et al., 2011), the set of filters scanned, *Gi* for gaussian filters and *Bi*

*G*<sup>1</sup> : {*σ* = 0.001}; *G*<sup>2</sup> : {*σ* = 1.5}; *G*<sup>3</sup> : {*σ* = 10}

*B*<sup>1</sup> : {*n* = 1, *δ* = 0.5}; *B*<sup>2</sup> : {*n* = 1, *δ* = 0.05}; *B*<sup>3</sup> : {*n* = 1, *δ* = 0.005}; *B*<sup>4</sup> : {*n* = 2, *δ* = 0.5}; *B*<sup>5</sup> : {*n* = 2, *δ* = 0.05}; *B*<sup>6</sup> : {*n* = 2, *δ* = 0.005}; *B*<sup>7</sup> : {*n* = 4, *δ* = 0.5}; *B*<sup>8</sup> : {*n* = 4, *δ* = 0.05}; *B*<sup>9</sup> : {*n* = 4, *δ* = 0.005}

As well, we have added the results of the angle output without filtering. Two Nemenyi tests have been performed, one (labeled *TN*1) to detect differences across filters and another one (labeled *TN*2) to compare the impact of the filtering with the angle itself. The first one only includes errors for *Bi* and *Gi*, while the second one incorporates the errors obtained by the angle *θc*. Tables 1 and 2, report the average ranks (the smaller, the better) reflecting each filter performance (table 1) and its comparison to the sampling obtained without filtering (table 2). Filter Param. *G*<sup>1</sup> *G*<sup>2</sup> *G*<sup>3</sup> *B*<sup>1</sup> *B*<sup>2</sup> *B*<sup>3</sup> *B*<sup>4</sup> *B*<sup>5</sup> *B*<sup>6</sup> *B*<sup>7</sup> *B*<sup>8</sup> *B*<sup>9</sup> Rank 8.12 5.53 6.15 5.71 5.24 7.47 6.06 5.44 7.94 5.56 6.68 8.12

Filter Param. *G*<sup>1</sup> *G*<sup>2</sup> *G*<sup>3</sup> *B*<sup>1</sup> *B*<sup>2</sup> *B*<sup>3</sup> *B*<sup>4</sup> *B*<sup>5</sup> *B*<sup>6</sup> *B*<sup>7</sup> *B*<sup>8</sup> *B*<sup>9</sup> *θ* Rank 8.29 5.65 6.27 5.82 5.35 7.59 6.18 5.56 8.06 5.68 6.79 8.29 11.47

Table 2. *TN*2: Comparison of performance between the filters set and the sampling without

the time computation for Rigid In-plane Motion Estimation (SPD/(MSS+RME)).

constant pull-back at 0.5 mm/s and a digitalization rate of 25 frames/s.

**5. Results**

filtering

**5.1 Sequence stabilization**

**5.2 Cardiac phase retrieval**

calcium shows a uniform appearance.

for Butterworth ones is the following.

Table 1. *TN*1: Average rank of the filters set performance

Therefore for the sake of a faithful comparison, the experimental set is the same used in (Hernàndez-Sabaté et al., 2011): 22 vessel segments 420-690 frames long (7-11.5 mm approximately) recorded with a Galaxy-BostonSci device at 40 MHz, with a rotating single transducer and constant pullback speed of 0.5 mm./s. The digitalization rate was 30 fps.

#### **4.3 Vessel structures detection**

The goal of this experiment is checking wether the rotation angle can produce accurate enough adventitia segmentations, while significantly reducing computational time. Therefore, we have compared segmentations obtained using MSS filtering to SPD diffusion (Gil et al., 2006) in terms of quality of the segmentations and computational cost.

In this case, ground truth is given by manual identification of the adventitia in IVUS images. Since discrepancies among experts provide a non-unique ground truth, we follow the same protocol described in (Gil et al., 2006), based on comparisons of inter-observer variability to manual segmentations. The accuracy has been assessed by means of absolute (in millimeters) and relative (in percent) distances. If *p* = (*xp*, *yp*) denotes the points corresponding to an automatic contour, its absolute distance to the manual contour is defined as:

$$D(p) = \min\_{q \in \gamma} \sqrt{(\mathbf{x}\_p - \mathbf{x}\_q)^2 + (y\_p - y\_q)^2} \tag{5}$$

and relative distances correspond to the ratio:

$$RelD(p) = 100 \cdot \frac{D(p)}{d(q\_\prime O)}$$

for the origin *O* the center of mass of the manual contour and *q* the point achieving the minimum in (5). Absolute distances are given in mm and relative ones in percentages. For each distance error, we compute its maximum and mean values on the automated contour to measure accuracy in positions.

• Maximum distance errors:

$$\begin{aligned} \text{MaxD} &= \max\_{p} (D(p) \cdot \text{PixSze})) \\ \text{RelMaxD} &= \max\_{p} (\text{RelD}(p)) \end{aligned}$$

• Mean distance errors:

$$\begin{aligned} \textit{Mean}D &= \textit{mean}\_p(D(p) \cdot \textit{PixSize}))\\ \textit{RelMean}D &= \textit{mean}\_p(\textit{RelD}(p)) \end{aligned}$$

for PixSze denoting the image spatial resolution and *p* is any point on the automatically traced adventitia. The interval given by the mean ± standard deviation computed over the 4 experts contours indicate the statistical range of values for each of the automated errors (MaxD, RelMaxD, MeanD, RelMeanD). Inter-observer variability is obtained by computing the error measures for the models made every two independent observers and it, thus, quantifies discrepancy among experts.

Concerning computational time, we have considered maximums and ranges for the following tasks: Rigid In-plane Motion Estimation (RME), adventitia segmentation by means of Mean of Stabilized Sequences (MSS), adventitia segmentation by means of Structures Preserving Diffusion (SPD). For a better quantification of time improvement, we have also considered the ratio between both segmentation techniques (SPD/MSS) and the ratio taking into account the time computation for Rigid In-plane Motion Estimation (SPD/(MSS+RME)).

Since we want to compare MSS filtering to the anisotropic filtering used in (Gil et al., 2006), the experimental setting is the same reported in (Gil et al., 2006). A total number of 5400 images extracted from 22 vessel segments of a length ranging from 4 to 6 mm (200-300 frames). Sequences were recorded with a Boston Scientific Clear View Ultra scanner at 40 MHz with constant pull-back at 0.5 mm/s and a digitalization rate of 25 frames/s.

#### **5. Results**

14 Will-be-set-by-IN-TECH

Therefore for the sake of a faithful comparison, the experimental set is the same used in (Hernàndez-Sabaté et al., 2011): 22 vessel segments 420-690 frames long (7-11.5 mm approximately) recorded with a Galaxy-BostonSci device at 40 MHz, with a rotating single transducer and constant pullback speed of 0.5 mm./s. The digitalization rate was 30 fps.

The goal of this experiment is checking wether the rotation angle can produce accurate enough adventitia segmentations, while significantly reducing computational time. Therefore, we have compared segmentations obtained using MSS filtering to SPD diffusion (Gil et al., 2006)

In this case, ground truth is given by manual identification of the adventitia in IVUS images. Since discrepancies among experts provide a non-unique ground truth, we follow the same protocol described in (Gil et al., 2006), based on comparisons of inter-observer variability to manual segmentations. The accuracy has been assessed by means of absolute (in millimeters) and relative (in percent) distances. If *p* = (*xp*, *yp*) denotes the points corresponding to an

(*xp* − *xq*)<sup>2</sup> + (*yp* − *yq*)<sup>2</sup> (5)

in terms of quality of the segmentations and computational cost.

automatic contour, its absolute distance to the manual contour is defined as:

*RelD*(*p*) = <sup>100</sup> · *<sup>D</sup>*(*p*)

for the origin *O* the center of mass of the manual contour and *q* the point achieving the minimum in (5). Absolute distances are given in mm and relative ones in percentages. For each distance error, we compute its maximum and mean values on the automated contour

*MaxD* = *maxp*(*D*(*p*) · *PixSze*))

*MeanD* = *meanp*(*D*(*p*) · *PixSze*))

*RelMaxD* = *maxp*(*RelD*(*p*))

*RelMeanD* = *meanp*(*RelD*(*p*))

for PixSze denoting the image spatial resolution and *p* is any point on the automatically traced adventitia. The interval given by the mean ± standard deviation computed over the 4 experts contours indicate the statistical range of values for each of the automated errors (MaxD, RelMaxD, MeanD, RelMeanD). Inter-observer variability is obtained by computing the error measures for the models made every two independent observers and it, thus, quantifies

Concerning computational time, we have considered maximums and ranges for the following tasks: Rigid In-plane Motion Estimation (RME), adventitia segmentation by means of Mean of Stabilized Sequences (MSS), adventitia segmentation by means of Structures Preserving Diffusion (SPD). For a better quantification of time improvement, we have also considered

*d*(*q*,*O*)

*D*(*p*) = *minq*∈*<sup>γ</sup>*

and relative distances correspond to the ratio:

to measure accuracy in positions. • Maximum distance errors:

• Mean distance errors:

discrepancy among experts.

**4.3 Vessel structures detection**

#### **5.1 Sequence stabilization**

Figure 14 shows two longitudinal cuts taken at the white lines on the IVUS left image and the same cut after sequence alignment. Each IVUS image cuts present the two main artifacts induced by vessel dynamics in *in vivo* pullbacks. The upper longitudinal cuts show the saw-tooth-shape pattern of the vessel intima wall (dark line) introduced by relative vessel-catheter translation. The profile of bottom cuts presents a structure misalignment due to the relative vessel-catheter rotation for an echo-shadowing calcified plaque. After sequence stabilization, the vessel wall profiles of upper cuts are straight and continuous, whereas calcium shows a uniform appearance.

#### **5.2 Cardiac phase retrieval**

As in (Hernàndez-Sabaté et al., 2011), the set of filters scanned, *Gi* for gaussian filters and *Bi* for Butterworth ones is the following.

$$\mathcal{G}\_1 \colon \{ \sigma = 0.001 \} \colon \mathcal{G}\_2 \colon \{ \sigma = 1.5 \} \colon \mathcal{G}\_3 \colon \{ \sigma = 10 \}$$

$$B\_1: \{n=1, \delta=0.5\}; B\_2: \{n=1, \delta=0.05\}; B\_3: \{n=1, \delta=0.005\}; B\_4: \{n=2, \delta=0.5\}; B\_5: \{n=2, \delta=0.005\}; B\_7: \{n=2, \delta=0.005\}; B\_7: \{n=4, \delta=0.05\}; B\_8: \{n=4, \delta=0.005\}$$

As well, we have added the results of the angle output without filtering. Two Nemenyi tests have been performed, one (labeled *TN*1) to detect differences across filters and another one (labeled *TN*2) to compare the impact of the filtering with the angle itself. The first one only includes errors for *Bi* and *Gi*, while the second one incorporates the errors obtained by the angle *θc*. Tables 1 and 2, report the average ranks (the smaller, the better) reflecting each filter performance (table 1) and its comparison to the sampling obtained without filtering (table 2).




Table 2. *TN*2: Comparison of performance between the filters set and the sampling without filtering

Fig. 16. Visually comparison of different filters to the sampling without filtering using *NT*2.

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 201

there is no significative difference between them. The Butterworth filter with *n* = 1 and *δ* = 0.05 achieves the best results with an error within 3.55 ± 1.80 frames, which corresponds

> Method Frames Seconds Millimeters *G*<sup>2</sup> 3.5601 ± 1.9804 0.1187 ± 0.0660 0.0593 ± 0.0330 *G*<sup>3</sup> 3.6974 ± 1.8520 0.1232 ± 0.0617 0.0616 ± 0.0309 *B*<sup>1</sup> 3.6416 ± 1.8747 0.1214 ± 0.0625 0.0607 ± 0.0312 *B*<sup>2</sup> 3.5498 ± 1.7998 0.1183 ± 0.0600 0.0592 ± 0.0300 *B*<sup>4</sup> 3.6824 ± 1.8478 0.1227 ± 0.0616 0.0614 ± 0.0308 *B*<sup>5</sup> 3.7468 ± 1.5738 0.1249 ± 0.0525 0.0624 ± 0.0262 *B*<sup>7</sup> 3.6660 ± 1.8423 0.1222 ± 0.0614 0.0611 ± 0.0307 *B*<sup>8</sup> 4.0192 ± 1.6035 0.1340 ± 0.0534 0.0670 ± 0.0267

In order to compare the ranges of the approach proposed in this chapter to the ones presented in (Hernàndez-Sabaté et al., 2011) table 4 reports the ranges of the filters presented in table 3 in frames (1st column), seconds (2nd column) and millimeters (3rd column). We can observe

> Method Frames Seconds Millimeters *G*<sup>1</sup> 3.8644 ± 1.7497 0.1288 ± 0.0583 0.0644 ± 0.0292 *G*<sup>2</sup> 3.8929 ± 1.6648 0.1298 ± 0.0555 0.0649 ± 0.0277 *B*<sup>1</sup> 4.0240 ± 1.6105 0.1341 ± 0.0537 0.0671 ± 0.0268 *B*<sup>2</sup> **3**.**8972** ± **1**.**8001** 0.1299 ± 0.0600 0.0650 ± 0.0300 *B*<sup>3</sup> 4.4488 ± 1.9458 0.1483 ± 0.0649 0.0741 ± 0.0324 *B*<sup>4</sup> 3.8570 ± 1.7338 0.1286 ± 0.0578 0.0643 ± 0.0289 *B*<sup>5</sup> 4.1506 ± 1.8597 0.1384 ± 0.0620 0.0692 ± 0.0310 *B*<sup>7</sup> 3.8680 ± 1.7279 0.1289 ± 0.0576 0.0645 ± 0.0288 *B*<sup>8</sup> 4.2071 ± 1.8385 0.1402 ± 0.0613 0.0701 ± 0.0306

Table 4. Average Errors of the best set of filters for the image-grey level evolution approach Figure 17 shows the performance of our method for the Butterworth filtering in 4 large longitudinal cuts. The original cuts are in the left, while the cuts sampled at end diastole rate are in the right. For the first segment, we can notice the continuous profile for the lumen contour, while in the second and third segments, we can follow up the calcium plaques present in the vessel. In the four segment we can appreciate the continuous profile of two bifurcations

Table 5 reports the inter-observer variability (INT-OBS) to ranges of automatic errors for SPD and MSS computed for all segments. The results for the MSS algorithm are slightly worse

to 0.06 ± 0.03 mm.

Table 3. Average Errors of the best set of filters

at the upper side of the cut.

**5.3 Vessel structures detection**

that there is no significative difference as a Nemenyi test proves.

Fig. 14. Longitudinal cuts for sequences of two patients. The first column corresponds to a representative original frame, for each patient, with the angle of the longitudinal cuts. In the second column, the original longitudinal cut and the corrected one in the third column.

The Nemenyi critical difference (CD) for *TN*<sup>1</sup> is 3.75, while for *TN*<sup>2</sup> is 4.11. The test detects that the sampling without filtering is significatively worst than the filtered ones. However, the Nemenyi test also reports that there is not enough evidence of a significantly different performance among the filtered methods.

Figures 15 and 16 show the rank of samplings from left to right (the best is on the left) together with the critical difference in order to visually compare them. In figure 15 we can note that there is no significative difference among the filters. However, in figure 16, we can appreciate that the sampling without filtering is clearly separated from the rest.

Fig. 15. Visually comparison of different filters using *NT*1.

Table 3 reports the ranges, by the mean ± the variance (*μ* ± *σ*) of the 8 filters of the set with better ranks. Values in the first column are in frames, the ones of the second column are in seconds and the last column correspond to the values in millimeters. As figure 15 shows, 16 Will-be-set-by-IN-TECH

Fig. 14. Longitudinal cuts for sequences of two patients. The first column corresponds to a representative original frame, for each patient, with the angle of the longitudinal cuts. In the second column, the original longitudinal cut and the corrected one in the third column.

The Nemenyi critical difference (CD) for *TN*<sup>1</sup> is 3.75, while for *TN*<sup>2</sup> is 4.11. The test detects that the sampling without filtering is significatively worst than the filtered ones. However, the Nemenyi test also reports that there is not enough evidence of a significantly different

Figures 15 and 16 show the rank of samplings from left to right (the best is on the left) together with the critical difference in order to visually compare them. In figure 15 we can note that there is no significative difference among the filters. However, in figure 16, we can appreciate

Table 3 reports the ranges, by the mean ± the variance (*μ* ± *σ*) of the 8 filters of the set with better ranks. Values in the first column are in frames, the ones of the second column are in seconds and the last column correspond to the values in millimeters. As figure 15 shows,

that the sampling without filtering is clearly separated from the rest.

Fig. 15. Visually comparison of different filters using *NT*1.

performance among the filtered methods.

Fig. 16. Visually comparison of different filters to the sampling without filtering using *NT*2.

there is no significative difference between them. The Butterworth filter with *n* = 1 and *δ* = 0.05 achieves the best results with an error within 3.55 ± 1.80 frames, which corresponds to 0.06 ± 0.03 mm.


Table 3. Average Errors of the best set of filters

In order to compare the ranges of the approach proposed in this chapter to the ones presented in (Hernàndez-Sabaté et al., 2011) table 4 reports the ranges of the filters presented in table 3 in frames (1st column), seconds (2nd column) and millimeters (3rd column). We can observe that there is no significative difference as a Nemenyi test proves.


Table 4. Average Errors of the best set of filters for the image-grey level evolution approach

Figure 17 shows the performance of our method for the Butterworth filtering in 4 large longitudinal cuts. The original cuts are in the left, while the cuts sampled at end diastole rate are in the right. For the first segment, we can notice the continuous profile for the lumen contour, while in the second and third segments, we can follow up the calcium plaques present in the vessel. In the four segment we can appreciate the continuous profile of two bifurcations at the upper side of the cut.

#### **5.3 Vessel structures detection**

Table 5 reports the inter-observer variability (INT-OBS) to ranges of automatic errors for SPD and MSS computed for all segments. The results for the MSS algorithm are slightly worse

diffusion approach. Although rigid in-plane motion estimation is useful for the whole integrative framework, we could take into account the time needed for computing it. Still,

The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries 203

In this chapter we proposed an integrative framework for exploring vessel dynamics and structures, so that to obtain stable models of arteries. We showed the potential of vessel in-plane rigid dynamics to analyze and correct vessel in-plane rigid dynamics, retrieve cardiac

In (Hernàndez-Sabaté et al., 2009) we already proved that rigid in-plane dynamics estimation contributes in a proper image misalignment correction. In this chapter we also showed the usefulness of this estimation for retrieving cardiac phase and we compared the method proposed to other vessel appearance-based models. There are two main advantages in using a dynamic quantity instead of the usual signals computed from image grey-level evolution (Barajas et al., 2007; Hernàndez-Sabaté et al., 2011; Matsumoto et al., 2008; Nadkarni et al., 2005). Firstly, since *θ<sup>c</sup>* does not include non-cardiac phenomena (such as breathing) it requires less specific tuning of the band-pass filtering. Secondly, it is computationally faster. Although errors ranges seem to be worse for the new approach, a Nemenyi test reports that there is no significative differences. Concerning the usefulness of rigid dynamics for the contribution to the adventitia segmentation, the main improvement is the computational time. Nevertheless,

For that reasons, we can conclude that rigid in-plane dynamics estimation has a high potential for developing useful techniques for clinical practice, and reducing drastically the time

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the new approach is 5 times faster (in average).

computation, since they can be parallelizable.

**7. References**

*IEEE EMBS*.

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phase and aid the automatic segmentation of adventitia layer.

the accuracy errors still keep within the range of inter-observer variability.

**6. Discussions and conclusions**

Fig. 17. Results of Image-based ECG sampling for two different longitudinal cuts.

than the ones from the SPD approach. However, note that they are still in the range of inter-observer variability.


Table 5. Performance Evaluation of the Adventitia Segmentation Strategies

Table 6 reports the computational times required for each task: Rigid In-plane Motion Estimation (RME), adventitia segmentation by means of Mean of Stabilized Sequences (MSS), adventitia segmentation by means of Structures Preserving Diffusion (SPD), the ratio between both segmentation techniques (SPD/MSS) and the ratio taking into account the time computation for Rigid In-plane Motion Estimation (SPD/(MSS+RME)). We can observe that the new approach proposed is almost 27 times faster (in average) than the vessel appearance


Table 6. Times comparison of Adventitia Segmentation Strategies for each frame (in sec.)

diffusion approach. Although rigid in-plane motion estimation is useful for the whole integrative framework, we could take into account the time needed for computing it. Still, the new approach is 5 times faster (in average).

#### **6. Discussions and conclusions**

18 Will-be-set-by-IN-TECH

Fig. 17. Results of Image-based ECG sampling for two different longitudinal cuts.

Table 5. Performance Evaluation of the Adventitia Segmentation Strategies

inter-observer variability.

than the ones from the SPD approach. However, note that they are still in the range of

MaxD (mm) 0.5386 ± 0.3075 0.5715 ± 0.2296 0.5988 ± 0.2047 RelMaxD (%) 0.4697 ± 0.2664 0.5122 ± 0.2344 0.5369 ± 0.1953 MeanD (mm) 0.2206 ± 0.1126 0.2265 ± 0.0688 0.2604 ± 0.0879 RelMeanD (%) 0.1888 ± 0.0945 0.1972 ± 0.0662 0.2387 ± 0.0808

Table 6 reports the computational times required for each task: Rigid In-plane Motion Estimation (RME), adventitia segmentation by means of Mean of Stabilized Sequences (MSS), adventitia segmentation by means of Structures Preserving Diffusion (SPD), the ratio between both segmentation techniques (SPD/MSS) and the ratio taking into account the time computation for Rigid In-plane Motion Estimation (SPD/(MSS+RME)). We can observe that the new approach proposed is almost 27 times faster (in average) than the vessel appearance

Max 0.5412 0.0909 2.4379 32.2131 5.5228 Mean 0.3575 ± 0.0673 0.0797 ± 0.0057 2.1282 ± 0.1279 26.8792 ± 2.9042 4.9484 ±0.6193

Table 6. Times comparison of Adventitia Segmentation Strategies for each frame (in sec.)

INT-OBS SPD MSS

RME MSS SPD SPD/MSS SPD/(MSS+RME)

In this chapter we proposed an integrative framework for exploring vessel dynamics and structures, so that to obtain stable models of arteries. We showed the potential of vessel in-plane rigid dynamics to analyze and correct vessel in-plane rigid dynamics, retrieve cardiac phase and aid the automatic segmentation of adventitia layer.

In (Hernàndez-Sabaté et al., 2009) we already proved that rigid in-plane dynamics estimation contributes in a proper image misalignment correction. In this chapter we also showed the usefulness of this estimation for retrieving cardiac phase and we compared the method proposed to other vessel appearance-based models. There are two main advantages in using a dynamic quantity instead of the usual signals computed from image grey-level evolution (Barajas et al., 2007; Hernàndez-Sabaté et al., 2011; Matsumoto et al., 2008; Nadkarni et al., 2005). Firstly, since *θ<sup>c</sup>* does not include non-cardiac phenomena (such as breathing) it requires less specific tuning of the band-pass filtering. Secondly, it is computationally faster. Although errors ranges seem to be worse for the new approach, a Nemenyi test reports that there is no significative differences. Concerning the usefulness of rigid dynamics for the contribution to the adventitia segmentation, the main improvement is the computational time. Nevertheless, the accuracy errors still keep within the range of inter-observer variability.

For that reasons, we can conclude that rigid in-plane dynamics estimation has a high potential for developing useful techniques for clinical practice, and reducing drastically the time computation, since they can be parallelizable.

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### *Edited by Yasuhiro Honda*

Intravascular ultrasound (IVUS) is a cardiovascular imaging technology using a specially designed catheter with a miniaturized ultrasound probe for the assessment of vascular anatomy with detailed visualization of arterial layers. Over the past two decades, this technology has developed into an indispensable tool for research and clinical practice in cardiovascular medicine, offering the opportunity to gather diagnostic information about the process of atherosclerosis in vivo, and to directly observe the effects of various interventions on the plaque and arterial wall. This book aims to give a comprehensive overview of this rapidly evolving technique from basic principles and instrumentation to research and clinical applications with future perspectives.

Intravascular Ultrasound

Intravascular Ultrasound

*Edited by Yasuhiro Honda*

Photo by Ugreen / iStock