**3. Real time tissue elastography**

The principle underlining RTE is shown in Figure 1A, which illustrates this as a spring mod‐ el [16]. When a spring is compressed, the displacement in each section of the spring depends on its stiffness: a soft spring compresses more than a hard spring. The strain distribution can be measured by differentiating the spatial displacement at each location. Although the tissue displacement usually is generated by manual compression and relaxation of the probe in practice, we were able to improve the acquisition of RTE images representing the distortion of liver tissue as a result of the beating of the heart or pulsing of the abdominal aorta.

RTE is carried out using a high quality ultrasound system (Hitachi AlokaMedical, Chiba, Ja‐ pan). The software uses a complex algorithm to process in a very short time all the data coming from the lesion as radiofrequency impulses and to minimize the artifacts due to lat‐ eral dislocations, allowing accurate measurement of the degree of tissue distortion. We used the Hitachi EUB-8500 and EUP-L52 Linear probe (3–7 MHz; Hitachi AlokaMedical) for RTE.

valuable in the breast cancer [15]. We show here the additional value of RTE, in comparsion

The two major categories of non-invasive hepatic elasticity imaging are dynamic elastogra‐ phy techniques, such as Fibroscan, and static elastography techniques, such as RTE. At present the dynamic elastography techniques have the advantage of allowing a quantitative imaging and better resolution than the static elastography techniques. These techniques re‐ quire more complex equipment for the generation mode and imaging modalities. Ultra‐ sound and magnetic resonance imaging are the major imaging modalities. The dynamic elastography techniques may be devided into two groups, based on the method of generat‐ ing the shear wave: remote generation using radiation force and mechanical vibration. Of the static elastography techniques, real time tissue elastography developed by Hitachi Medi‐ cal is most advanced ultrasound technique and can reveal tissue distortion using the hart beat and pulsing of the aorta. Several elastography techniques are summarized in Table 1.

Real-time Tissue Elastography (RTE) Tissue distortion Pulsing of the aorta Ultrasound

Supersonic Shear Imaging (SSI) Propagating shear wave Radiation force Ultrasound

The principle underlining RTE is shown in Figure 1A, which illustrates this as a spring mod‐ el [16]. When a spring is compressed, the displacement in each section of the spring depends on its stiffness: a soft spring compresses more than a hard spring. The strain distribution can be measured by differentiating the spatial displacement at each location. Although the tissue displacement usually is generated by manual compression and relaxation of the probe in practice, we were able to improve the acquisition of RTE images representing the distortion

of liver tissue as a result of the beating of the heart or pulsing of the abdominal aorta.

**Principle Mode of generation Imaging modality**

Propagating shear wave Mechanical vibration Magnetic resonance

imaging

Propagating shear wave Mechanical vibration Ultrasound

Propagating shear wave Radiation force Ultrasound

to Fibroscanin patients with chronic liver disease.

282 Liver Biopsy – Indications, Procedures, Results

**2. Principle of elastography imaging**

Vibration-Controlled Transient Elastography (VCTE, Fibroscan)

Acoustic Radiation Force Impulse

Magnetic Resonance Elastography

**Table 1.** Elastography techniques for measurement of liver stiffness.

**3. Real time tissue elastography**

(ARFI)

(MRE)

**Figure 1.** The principle and procedure of image analyses for real-time tissue elastography.(A) When a spring is com‐ pressed, displacement in each section of the spring depends on the stiffness of that part of the spring: a soft section compresses more than a hard section. The strain distribution can be measured by differentiating the spatial displace‐ ment at each location. (B) The ROI was fixed to a rectangle of approximately 20-30 mm length x 20 mm breadth with a 400–600 mm2 area located 5-10 mm below the surface of the liver.left; RTE image, right; B-mode image. (C-D) The color-coded images from the ROI of the RTE were analyzed by the software Elasto\_ver1.5.1. The colors ranged from blue to red indicating the relative gradients from hardness to softness. The Mean and Standard deviation were calcu‐ lated by a histogram, which was generated by 256 stepwise grading derived from the color image. The Area and Com‐ plexity were calculated from the binary image. Area was derived from the percentage of white regions (asterisks, i.e. hard area). Complexity was calculated asperiphery2/Area. Median value of the data were recorded as representative of RTE parameters.

This system is currently commercially available for the diagnosis of mammary neoplasm. Patients were examined in a supine position with the right arm elevated above the head, and were instructed to hold their breath. The examination was performed on the right lobe of the liver through the intercostal space, and liver biopsy and Fibroscan also were per‐ formed at the same site. The RTE equipment displays two images simultaneously; one shows the regions of interest (ROI) as a colored area and the other indicates the conventional B-mode image (Fig. 1B). We chose an area where the tissue was free from large vessels and near the biopsy point. The measurement was fixed to a rectangle 30 mm in length and 20 mm in breadth located 5-10 mm below the surface of the liver (Fig. 1B). The color in the ROI was graded from blue (representing hard areas) to red (representing soft areas, Fig. 1B). We stored the RTE images for 2- 3min as moving digital images (Fig. 1B) and ten static images were captured at random from the moving images by the observer using AVI2JPG v6.10 converter software (Novo, Tokyo, Japan) and analyzed on a personal computer using the novel software Elasto\_ver 1.5.1,which was developed and donated by Hitachi Medical. Nu‐ merical values of pixels were from 0 to 255 (256 stepwise grading) according to color map‐ ping from blue (0) to red (255), and a histogram of the distribution was generated (Fig. 1C). The scale ranged from red for components with the greatest strain (i.e., the softest compo‐ nents) to blue for those with no strain (i.e., the hardest components). Green indicated aver‐ age strain in the ROI, and therefore intact liver tissue was displayed as a diffuse homogeneous green pattern. An appearance of unevenness in the color pattern was consid‐ ered to reflect a change in the liver stiffness. For quantification, all pixel data in the colored image were transferred into a histogram and binary image (Fig. 1C, D).

AUROCs for the diagnosis of significant fibrosis and cirrhosis were 0.76 and 0.90, respectively. Table 2 shows concisely the diagnostic accuracy of Fibroscan. The limitations of this method al‐ so have been discussed; intraobserver agreement is influenced by variables, such as body mass index (particularly when<28 kg/m2), hepatic steatosis, and flares of transaminases [17.23].

(kPa)

7.1 12.5

8.6 14.6

5.2 12.9

**5. Acoustic Radiation Force Impulse (ARFI) and Magnetic Resonance**

The technology applied most recent is acoustic radiation force impulse (ARFI) imaging. AR‐ FI imaging permits evaluation of the elastic properties of a region of interest during realtime B-mode conventional hepatic US examination. Results are expressed in meters per second and the region of interest can be chosen using ultrasound guidance, there by avoid‐ ing large blood vessels and the ribs. Previous reports have indicated that the diagnostic power of ARFI imaging for the staging of liver fibrosis is the same as that of Fibroscan [28.

New technological advances have been made in the clinical application of MRI such as dif‐ fusion-weighted MRI and MRI elastography. The former measures the apparent diffusion coefficient of water and the parameter is dependent on the tissue structure [30]. The latter measures the propagation characteristic of the shear waves from an acoustic driver within the liver. Although MRI elastography has been shown to be superior to APRI and Fibroscan for determining the stage of fibrosis in patients with various under lying liver diseases [31], it cannot be performed on aniron-overloaded liver because of noise. In addition, MRI takes

longer and costs more than the ultrasound-base delastographic examinations.

Sen, Sensitivity; Spe, Specificity; PPV, Positive Predictive Value; NPV, Negative Predictive Value; AUC, Area Under the

67% 87%

Real-Time Tissue Elastography and Transient Elastography for Evaluation of Hepatic Fibrosis

56% 86%

90% 70% 89% 91%

91% 96%

34% 90%

Sen Spe PPV NPV AUC

95% 77%

88% 78%

64% 53% 48% 95%

http://dx.doi.org/10.5772/52695

56% 97%

72% 95% 0.83 0.95 285

0.79 0.97

0.84 0.94

0.76 0.79

Study Patients (n) Prognosis Cutoff

n=183, CHC ≥F2

n=251, CHC ≥F2

Receiver-Operator-Characteristic curve; CHC, chronic hepatitis C.

**Table 2.** Diagnostic accuracies of transient elastography

50 studies, liver disease

hepatitis

Cirrhosis

Cirrhosis

≥F2 Cirrhosis

≥F2 Cirrhosis

Catera et al. 2005

Zioi et al. 2005

2008

29].

Friedrich-Rust et al.

Degos et al. 2010 n=1307, viral

**Elastography (MRE)**
