Preface

As a unique platform, this book provides a perspective on the current status of bioimaging technology, furthering the evolution of nano-bioimaging. The chapters in this book are pro‐ vided by experts who reviewed the recent developments in the nano-bioimaging technology and its application.

The book starts with a general introduction, presenting basic information on the nano-bioi‐ maging technology. The following chapters discuss the technological aspects of nano-bioi‐ maging and its applications, as well as the recent progress in employment of nanomaterials. Also covered is the recent development in the application of bioimaging for multidisciplina‐ ry research and among various professions, including computed tomography, cancer detec‐ tion, and clinical medicine.

The first chapter in the book is an Introductory Chapter. In the second chapter, diverse re‐ search on nanomaterial-based optical imaging for effective cancer therapy is introduced. In the third chapter, we look at the unique properties of carbon quantum dots, their synthesis, material as well as optical characterizations, origin of fluorescence nature, and applications of carbon quantum dots in bioimaging. In the fourth chapter, the recently developed electro‐ magnetic tomography (EMT) is reviewed. As a promising diagnostic tool for lung cancer and biosensing techniques for early-stage lung cancer detection, the electromagnetic tomog‐ raphy technique has been proposed. In addition, developing label-free and cost-effective bi‐ osensors for target tumor marker detection has attracted attentions worldwide. The research status of low-dose technology from the following aspects low-dose scan implementation, re‐ construction methods, and image processing methods is introduced in the fifth chapter. Fur‐ thermore, other technologies related to the development tendency of computed tomography (CT), such as automatic tube current modulation technology, rapid peak kilovoltage (kVp) switching technology, and dual source CT technology, are also summarized. Finally, the fu‐ ture research prospects are discussed and analyzed. In the final chapter, the advantages of magic-sized quantum dots (MSQDs) as luminescent markers and probes to bioimage appli‐ cations are demonstrated. In addition, the visualization of magic-sized quantum dots (MSQDs) bioconjugated with biological probes in cells was performed.

> **Morteza Sasani Ghamsari** Photonics and Quantum Technologies Research School NSTRI, Tehran, Iran

**Chapter 1**

**Provisional chapter**

**Introductory Chapter: Nano-bioimaging—Past, Present,**

From the 1960s to the present, the image processing technology was dramatically improved, and an enormous growth rate in the use of image processing technology can be seen today in almost every field. It is a computer vision technology with the ability to replace the human vision by an artificial vision for observation of objects and processes. Historically, the potential of image processing for biological applications has been understood by researchers in later years of the 1980s and in the early 1990s, and many attempts have been made to focus on conducting research for the employment of this technique in biological imaging [1]. For instance, the milestones of optical imaging in autophagy research are shown in **Figure 1**. As it has been reported by Wang et al. [2], these events involve specific fluorescence probing methods that localize the selected autophagic components and optical imaging platforms. They confirmed that most of the new investigative methods and advanced imaging equipment were developed during the past decade, during which some super-resolution optical

Biological imaging or bioimaging is a precision technique for the recording of information relevant to biological materials using a variety of imaging equipments and processings. Usually, it is defined as a visualization method in which a biological process can be recognized noninvasively or to record the information from the biological specimen. Bioimaging aims to interfere as little as possible with life processes. Moreover, it is often used to gain information on the 3D structure of the observed specimen from the outside, i.e., without physical interference. In addition, the subcellular structures and the entire cells over tissues up to the entire multicellular organisms can be observed using bioimaging. Also, in cell biology, the cellular process or the ion or metabolite levels can be evaluated by bioimaging. Over three decades various biological imaging techniques such as X-ray, thermal imaging, X-ray computed

**Introductory Chapter: Nano-bioimaging—Past,** 

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: 10.5772/intechopen.74959

**and Future**

**1. Introduction**

Morteza Sasani Ghamsari

**Present, and Future**

http://dx.doi.org/10.5772/intechopen.74959

imaging technologies have emerged.

Additional information is available at the end of the chapter

Morteza Sasani GhamsariAdditional information is available at the end of the chapter

#### **Introductory Chapter: Nano-bioimaging—Past, Present, and Future Introductory Chapter: Nano-bioimaging—Past, Present, and Future**

DOI: 10.5772/intechopen.74959

### Morteza Sasani Ghamsari

Additional information is available at the end of the chapter Morteza Sasani GhamsariAdditional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.74959

#### **1. Introduction**

From the 1960s to the present, the image processing technology was dramatically improved, and an enormous growth rate in the use of image processing technology can be seen today in almost every field. It is a computer vision technology with the ability to replace the human vision by an artificial vision for observation of objects and processes. Historically, the potential of image processing for biological applications has been understood by researchers in later years of the 1980s and in the early 1990s, and many attempts have been made to focus on conducting research for the employment of this technique in biological imaging [1]. For instance, the milestones of optical imaging in autophagy research are shown in **Figure 1**. As it has been reported by Wang et al. [2], these events involve specific fluorescence probing methods that localize the selected autophagic components and optical imaging platforms. They confirmed that most of the new investigative methods and advanced imaging equipment were developed during the past decade, during which some super-resolution optical imaging technologies have emerged.

Biological imaging or bioimaging is a precision technique for the recording of information relevant to biological materials using a variety of imaging equipments and processings. Usually, it is defined as a visualization method in which a biological process can be recognized noninvasively or to record the information from the biological specimen. Bioimaging aims to interfere as little as possible with life processes. Moreover, it is often used to gain information on the 3D structure of the observed specimen from the outside, i.e., without physical interference. In addition, the subcellular structures and the entire cells over tissues up to the entire multicellular organisms can be observed using bioimaging. Also, in cell biology, the cellular process or the ion or metabolite levels can be evaluated by bioimaging. Over three decades various biological imaging techniques such as X-ray, thermal imaging, X-ray computed

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### 2 State of the Art in Nano-bioimaging

**Figure 1.** Milestones of optical imaging in autophagy research. All abbreviations are as follows: CLEM, correlated light and electron microscopy; dSTORM, direct stochastic optical reconstruction microscopy; LC3, light chain 3; LSCM, laser scanning confocal microscopy; SIM, structured illumination microscope; STED, stimulated emission depletion microscopy; TIRFM, total internal reflection fluorescence microscopy [2].

in the images is followed by the image processing. Over three decades, many developments have been achieved in equipments and image processing steps. As can be seen in **Figure 2**, recent progresses in bioimaging include super-resolution, two-photon fluorescence excitation microscopy, fluorescence recovery/redistribution after photobleaching (FRAP), and fluores-

Introductory Chapter: Nano-bioimaging—Past, Present, and Future

http://dx.doi.org/10.5772/intechopen.74959

3

As it is mentioned above, considerable advancements have been achieved in bioimaging. Nevertheless, the limitation of image resolution is a barrier that needs to circumvent for the next generation of bioimaging technology. Recently, the super-resolution microscopy was purposed for image resolution betterment [4]. It is found that the super-resolution microscopy can address some of the difficulties inherent in earlier microscopy techniques, provide new advances in biomedicine, and in those fields deal with the study of biological systems [4, 5]. However, it is suffering from the special equipment requirement which makes it as complex as it needs to be and hard to operate [6]. On the other hand, biologists believe that only a single type of technique cannot be used to obtain all information about a biological system [7]. Hauser et al. [8] found that the integration of two or more microscopy techniques performed on the same sample has been highly successful in overcoming the aforementioned limits of each method. They demonstrate how a correlative approach adds new dimensions of information and provides new opportunities in the fast-growing field of super-resolution microscopy. Additionally, other super-resolution microscopy methods such as structured

cence resonance energy transfer (FRET).

**Figure 2.** Recently developed techniques for bioimaging.

**2. Nano-bioimaging**

tomography (CT), hyperspectral imaging, optical, and magnetic resonance imaging (MRI) have been developed that are different in principles and equipment [3]. Due to their wide application potential in various fields, these techniques have continuously seen the rapid growths and the tremendous improvements. To carry out bioimaging, a setup of equipment is needed. Each kind of imaging requires different equipments, but the basic components in any imaging system are essentially the same. Usually, the following basic components such as a camera, illumination, frame grabber, and image processing hardware and software are used in a biological imaging system [1]. In bioimaging process, the image of the biological object is primary captured by a camera, and its external characteristics, such as color, shape, size, and surface texture, are evaluated using a sensor including a charge-coupled device (CCD) camera, X-ray, X-ray CT, ultrasound, and MRI. CCD camera is the most commonly used sensor for this purpose. After that, the conversion process named as digitization is used to convert the analog video signal from the camera into a digital signal. The conversion of pictorial images into digital form is performed by the frame grabber (or digitizer). Following that, digital image must be processed by the image processing hardware and software to analyze the captured images and obtain the necessary output. There are several steps including image acquisition, image preprocessing, enhancement, segmentation, representation, and description that need to be performed for image processing [1]. In each step, a process is performed. For example, the process of acquiring the raw binary data from the image of the area of interest is achieved by image acquisition, and the reduction of the unwanted features Introductory Chapter: Nano-bioimaging—Past, Present, and Future http://dx.doi.org/10.5772/intechopen.74959 3

**Figure 2.** Recently developed techniques for bioimaging.

in the images is followed by the image processing. Over three decades, many developments have been achieved in equipments and image processing steps. As can be seen in **Figure 2**, recent progresses in bioimaging include super-resolution, two-photon fluorescence excitation microscopy, fluorescence recovery/redistribution after photobleaching (FRAP), and fluorescence resonance energy transfer (FRET).

#### **2. Nano-bioimaging**

tomography (CT), hyperspectral imaging, optical, and magnetic resonance imaging (MRI) have been developed that are different in principles and equipment [3]. Due to their wide application potential in various fields, these techniques have continuously seen the rapid growths and the tremendous improvements. To carry out bioimaging, a setup of equipment is needed. Each kind of imaging requires different equipments, but the basic components in any imaging system are essentially the same. Usually, the following basic components such as a camera, illumination, frame grabber, and image processing hardware and software are used in a biological imaging system [1]. In bioimaging process, the image of the biological object is primary captured by a camera, and its external characteristics, such as color, shape, size, and surface texture, are evaluated using a sensor including a charge-coupled device (CCD) camera, X-ray, X-ray CT, ultrasound, and MRI. CCD camera is the most commonly used sensor for this purpose. After that, the conversion process named as digitization is used to convert the analog video signal from the camera into a digital signal. The conversion of pictorial images into digital form is performed by the frame grabber (or digitizer). Following that, digital image must be processed by the image processing hardware and software to analyze the captured images and obtain the necessary output. There are several steps including image acquisition, image preprocessing, enhancement, segmentation, representation, and description that need to be performed for image processing [1]. In each step, a process is performed. For example, the process of acquiring the raw binary data from the image of the area of interest is achieved by image acquisition, and the reduction of the unwanted features

**Figure 1.** Milestones of optical imaging in autophagy research. All abbreviations are as follows: CLEM, correlated light and electron microscopy; dSTORM, direct stochastic optical reconstruction microscopy; LC3, light chain 3; LSCM, laser scanning confocal microscopy; SIM, structured illumination microscope; STED, stimulated emission depletion

microscopy; TIRFM, total internal reflection fluorescence microscopy [2].

2 State of the Art in Nano-bioimaging

As it is mentioned above, considerable advancements have been achieved in bioimaging. Nevertheless, the limitation of image resolution is a barrier that needs to circumvent for the next generation of bioimaging technology. Recently, the super-resolution microscopy was purposed for image resolution betterment [4]. It is found that the super-resolution microscopy can address some of the difficulties inherent in earlier microscopy techniques, provide new advances in biomedicine, and in those fields deal with the study of biological systems [4, 5]. However, it is suffering from the special equipment requirement which makes it as complex as it needs to be and hard to operate [6]. On the other hand, biologists believe that only a single type of technique cannot be used to obtain all information about a biological system [7]. Hauser et al. [8] found that the integration of two or more microscopy techniques performed on the same sample has been highly successful in overcoming the aforementioned limits of each method. They demonstrate how a correlative approach adds new dimensions of information and provides new opportunities in the fast-growing field of super-resolution microscopy. Additionally, other super-resolution microscopy methods such as structured illumination microscopy (SIM) were developed for resolution enhancement. Despite their great success, all of these techniques are intrinsically involving with their limitations and challenges. For example, an expensive hardware and an expensive software are needed to overcome the spatial resolution improvement of SIM providing excellent super-resolution in 2D or 3D [9]. Ponsetto et al. explained that all of these methods have trade-offs between several factors such as resolution, speed, field of view, biocompatibility, sensitivity, and experimental complexity [10]. So et al. [11] compared the advancements of the widely used fluorescence microscopic techniques, stochastic optical reconstruction microscopy (STORM) or photoactivated localization microscopy (PALM), stimulated emission depletion (STED), and SIM. They explained that the label-free optical microscopic techniques whose functions are originated from nanoscale structures such as micro-curvilinear lens, super-oscillatory, and metamaterials can provide the conventional microscopy procedure with the ability for the new generation of nanoscopy. These approaches can break the barrier of diffraction limit, which is literally not a limit any more [11].

nano-bioimaging. Nanotechnology can also be used in other imaging techniques. For instance, Goel et al. reported that the hybridization of the dynamic synergism of positron emission tomography (PET) and nanotechnology can enhance the sensitivity and quantitative nature of PET which can help overcome certain key challenges in the field [18]. Fluorescence bioimaging in the second near-infrared spectral region (NIR-II, 1000–1700 nm) can be considered as attractive nanoparticles in nano-bioimaging. It can provide advantages of high spatial resolution and large penetration depth, due to low light scattering [18]. Their finding illustrates that NIR-II quantum dots (QDs) can be used in biomedical and clinical applications due to their excellent biocompatibility, photostability and brightness which require deep tissue imaging [19].

Lanthanide-doped upconversion nanoparticles (UCNPs) are the interesting nanomaterials with a great potential for nano-bioimaging applications [20, 21]. Their exceptional optical and physicochemical properties made them to be considered for design of the novel UCNP-based nanoplatform for luminescent and whole-body imaging [22]. Generalova et al. [22] demonstrated applications of UCNPs as a new nanoplatform for optical and multimodal cancer imaging in vitro and in vivo and extend discussions to delivery of UCNP-based therapeutic agents for photodynamic and photothermal cancer treatments. Similar to other semicon-

upconversion nanoparticles can be used for magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET)/single photon emission computed tomography (SPECT) [23–25]. **Figure 3** shows the schematic applications of semiconductor nanocrystals in bioimaging. As it is mentioned by Chen et al. [26, 27], semiconductor polymer dots (SPDs) can also be utilized in biological imaging because of their outstanding photophysical properties, such as high brightness, extraordinary photostability, and favorable biocompatibility, in comparison with those of quantum dots (QDs), organic dyes, and

, and CdSe/ZnS core shells, lanthanide-doped

Introductory Chapter: Nano-bioimaging—Past, Present, and Future

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5

ductor nanocrystals such as CdS, ZnO, TiO<sup>2</sup>

reversibly switchable fluorescent proteins (RSFPs).

**Figure 3.** Schematic illustration of semiconductor nanocrystal applications in bioimaging.

It is expected that the barrier of high-resolution image construction can be solved by nanotechnology. It seems that nanotechnology is able to advance medical imaging to the next level by increasing the resolution of current techniques [12]. This approach enhances the specificity of targeted imaging using the unique designed nanoconstructs. The increasing role of nanomaterials in biological and medical imaging research can reflect the impact of nanotechnology in bioimaging. As it has been mentioned, the contrast improvement of image is the most important reason for nanoparticle combination with imaging [13]. Usually, to utilize the enhancement of image contrast, contrast agents are needed. Traditionally, small-molecule contrast agents are used and biocompatible nanocrystals with the ability to provide a strong imaging signal. Also, plasmonic nanostructures can exhibit the field confinement effect which is locally amplified within subdiffraction-limited volume and is useful in many biomedical sensing and imaging applications [14]. Willets et al. reviewed the vital role of plasmonic nanoparticles in improvement of super-resolution imaging and described the growing partnership between super-resolution imaging and plasmonics, by describing the various ways in which the two topics mutually benefit one another to enhance our understanding of the nanoscale world [15]. They demonstrated that the plasmonic nanoparticles are explored as image contrast agents for super-localization and super-resolution imaging, offering benefits such as high photostability, large signal-to-noise ratio, and distance-dependent spectral features but presenting challenges for localizing individual nanoparticles within a diffraction-limited spot. In addition, they found that the subdiffraction-limited spatial resolution can be achieved by using the plasmon-tailored excitation fields [15]. Their study confirms that the localized surface plasmons and the surface plasmon polaritons can be used to create confined excitation volumes or image magnification to enhance spatial resolution. As powerful analytical tools, luminescent bioprobes are another example of the nanomaterial employment for optical imaging [16]. Shewring et al. described an Ir(III)-based small-molecule, multimodal probe for use in both light and electron microscopies [17]. Their finding confirmed the use of Ir(III) complexes as probes that provide excellent image contrast and quality for both luminescence and electron microscopy imagings. All of these correlative techniques are categorized in nano-bioimaging. Nanotechnology can also be used in other imaging techniques. For instance, Goel et al. reported that the hybridization of the dynamic synergism of positron emission tomography (PET) and nanotechnology can enhance the sensitivity and quantitative nature of PET which can help overcome certain key challenges in the field [18]. Fluorescence bioimaging in the second near-infrared spectral region (NIR-II, 1000–1700 nm) can be considered as attractive nanoparticles in nano-bioimaging. It can provide advantages of high spatial resolution and large penetration depth, due to low light scattering [18]. Their finding illustrates that NIR-II quantum dots (QDs) can be used in biomedical and clinical applications due to their excellent biocompatibility, photostability and brightness which require deep tissue imaging [19].

illumination microscopy (SIM) were developed for resolution enhancement. Despite their great success, all of these techniques are intrinsically involving with their limitations and challenges. For example, an expensive hardware and an expensive software are needed to overcome the spatial resolution improvement of SIM providing excellent super-resolution in 2D or 3D [9]. Ponsetto et al. explained that all of these methods have trade-offs between several factors such as resolution, speed, field of view, biocompatibility, sensitivity, and experimental complexity [10]. So et al. [11] compared the advancements of the widely used fluorescence microscopic techniques, stochastic optical reconstruction microscopy (STORM) or photoactivated localization microscopy (PALM), stimulated emission depletion (STED), and SIM. They explained that the label-free optical microscopic techniques whose functions are originated from nanoscale structures such as micro-curvilinear lens, super-oscillatory, and metamaterials can provide the conventional microscopy procedure with the ability for the new generation of nanoscopy. These approaches can break the barrier of diffraction limit,

It is expected that the barrier of high-resolution image construction can be solved by nanotechnology. It seems that nanotechnology is able to advance medical imaging to the next level by increasing the resolution of current techniques [12]. This approach enhances the specificity of targeted imaging using the unique designed nanoconstructs. The increasing role of nanomaterials in biological and medical imaging research can reflect the impact of nanotechnology in bioimaging. As it has been mentioned, the contrast improvement of image is the most important reason for nanoparticle combination with imaging [13]. Usually, to utilize the enhancement of image contrast, contrast agents are needed. Traditionally, small-molecule contrast agents are used and biocompatible nanocrystals with the ability to provide a strong imaging signal. Also, plasmonic nanostructures can exhibit the field confinement effect which is locally amplified within subdiffraction-limited volume and is useful in many biomedical sensing and imaging applications [14]. Willets et al. reviewed the vital role of plasmonic nanoparticles in improvement of super-resolution imaging and described the growing partnership between super-resolution imaging and plasmonics, by describing the various ways in which the two topics mutually benefit one another to enhance our understanding of the nanoscale world [15]. They demonstrated that the plasmonic nanoparticles are explored as image contrast agents for super-localization and super-resolution imaging, offering benefits such as high photostability, large signal-to-noise ratio, and distance-dependent spectral features but presenting challenges for localizing individual nanoparticles within a diffraction-limited spot. In addition, they found that the subdiffraction-limited spatial resolution can be achieved by using the plasmon-tailored excitation fields [15]. Their study confirms that the localized surface plasmons and the surface plasmon polaritons can be used to create confined excitation volumes or image magnification to enhance spatial resolution. As powerful analytical tools, luminescent bioprobes are another example of the nanomaterial employment for optical imaging [16]. Shewring et al. described an Ir(III)-based small-molecule, multimodal probe for use in both light and electron microscopies [17]. Their finding confirmed the use of Ir(III) complexes as probes that provide excellent image contrast and quality for both luminescence and electron microscopy imagings. All of these correlative techniques are categorized in

which is literally not a limit any more [11].

4 State of the Art in Nano-bioimaging

Lanthanide-doped upconversion nanoparticles (UCNPs) are the interesting nanomaterials with a great potential for nano-bioimaging applications [20, 21]. Their exceptional optical and physicochemical properties made them to be considered for design of the novel UCNP-based nanoplatform for luminescent and whole-body imaging [22]. Generalova et al. [22] demonstrated applications of UCNPs as a new nanoplatform for optical and multimodal cancer imaging in vitro and in vivo and extend discussions to delivery of UCNP-based therapeutic agents for photodynamic and photothermal cancer treatments. Similar to other semiconductor nanocrystals such as CdS, ZnO, TiO<sup>2</sup> , and CdSe/ZnS core shells, lanthanide-doped upconversion nanoparticles can be used for magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET)/single photon emission computed tomography (SPECT) [23–25]. **Figure 3** shows the schematic applications of semiconductor nanocrystals in bioimaging. As it is mentioned by Chen et al. [26, 27], semiconductor polymer dots (SPDs) can also be utilized in biological imaging because of their outstanding photophysical properties, such as high brightness, extraordinary photostability, and favorable biocompatibility, in comparison with those of quantum dots (QDs), organic dyes, and reversibly switchable fluorescent proteins (RSFPs).

**Figure 3.** Schematic illustration of semiconductor nanocrystal applications in bioimaging.

#### **3. Graphene-based materials for nano-bioimaging**

Among all nanomaterials that are considered as potential candidates for nano-bioimaging applications, graphene has attracted great attentions. As it has been expressed by Lin et al. [28], the biomedical applications of graphene and its derivatives are extensively investigated for diagnostics, drug delivery, near-infrared (NIR) light-induced photothermal therapy, and bioimaging. Due to the versatile surface functionalization and ultrahigh surface area of graphene and its derivatives, they can be easily functionalized by small-molecule dyes, polymers, nanoparticles, drugs, or biomolecules to obtain graphene-based nanomaterials for different bioimaging applications [28]. Lin et al. [28], focused on applying graphene-based nanomaterials for different molecular imaging modalities, and their review confirmed that the graphene-based materials can be employed for optical imaging (FL, two-photon FL, and Raman imaging), PET/SPECT (positron emission tomography/single photon emission computed tomography), MRI (magnetic resonance imaging), PAI (photoacoustic imaging), CT (computed tomography), and multimodal imaging (**Figure 4**). Graphene quantum dots (GQDs) are one of the graphene-based materials that have a considerable potential for bioimaging applications. Due to the photoluminescence (PL) and high structural stability, low cytotoxicity, and good biocompatibility, fluorescent graphene quantum dots (GQDs) have recently attracted an increasing interest in cancer bioimaging [29, 30]. Chen et al. [31] evaluated the recent advances and future challenges of biomedical applications of graphene quantum dots. They expressed that the wide applications of graphene quantum dots in biological imaging can be attributed to the relatively high quantum yields with high molar extinction coefficients, broad absorption with narrow emission spectra and high photostability, the strong quantum confinement, and edge effects stir of GQDs. In addition, in comparison with a traditional imaging modality, the highly stable and bright fluorescence characters of GQDderived nanomaterials lead to generate the optical signal with the small number of GQDs [31]. On the other hand, the ability of GQDs for near-infrared reflectance emission makes them as promising candidates for the imaging of deeper tissue samples. Based on the above reasons, applying GQDs as contrast agents for in vivo imaging has been the area of high expectations and recurring attention. The near-infrared emitting window shows great advantages for biomedical imaging because of the low tissue absorption and reduced light scattering in more than 650 nm wavelengths' region [31]. Functionalized graphene oxide (GO; 2D)-based nanocomposites are one of the graphene-based nanomaterials that have a great potential for biomedical applications. In recent years, because of their unique and highly enriched physical and chemical properties, such as excellent biocompatibility, ready cellular uptake, flexible chemical modifications, unique optical properties, and thermal and electrical conductivity, they have been used in biological fields, such as biomedicine, biosensors, drug delivery, and bioimaging [32]. Qiu et al. [33] developed the graphene oxide (GO)-wrapped gold nanorods (GO@GNRs) that can be used as a smart and robust nanoplatform for ultrafast NIR SERS bioimaging. Their finding demonstrated that the fabricated GO@GNRs could efficiently load various NIR probes, and the in vitro evaluation indicated that the nanoplatform could exhibit

Introductory Chapter: Nano-bioimaging—Past, Present, and Future

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7

a higher NIR SERS activity in comparison with traditional gold nanostructures.

Photonics and Quantum Technologies Research School, NSTRI, Tehran, Iran

[1] Vadivambal R, Jayas Digvir S, editors. Bio-Imaging Principles, Techniques and Applications.

[2] Wang Y, Li Y, Wei F, Duan Y. Optical imaging paves the way for autophagy research.

[3] Bronzino JD, Peterson DR, editors. Biomedical Signals, Imaging, and Informatics. Boca

[4] Diaspro A, van Zandvoort MAMJ, editors. Super-resolution Imaging in Biomedicine.

Address all correspondence to: msghamsari@yahoo.com

Boca Raton: CRC Press, Taylor & Francis Group; 2016

Trends in Biotechnology. 2017;**35**(12):1181-1193

Raton: CRC Press, Taylor & Francis Group; 2015

Boca Raton: CRC Press, Taylor & Francis Group; 2017

**Author details**

**References**

Morteza Sasani Ghamsari

**Figure 4.** The biomedical applications of graphene. Adapted from Ref. [28].

recently attracted an increasing interest in cancer bioimaging [29, 30]. Chen et al. [31] evaluated the recent advances and future challenges of biomedical applications of graphene quantum dots. They expressed that the wide applications of graphene quantum dots in biological imaging can be attributed to the relatively high quantum yields with high molar extinction coefficients, broad absorption with narrow emission spectra and high photostability, the strong quantum confinement, and edge effects stir of GQDs. In addition, in comparison with a traditional imaging modality, the highly stable and bright fluorescence characters of GQDderived nanomaterials lead to generate the optical signal with the small number of GQDs [31]. On the other hand, the ability of GQDs for near-infrared reflectance emission makes them as promising candidates for the imaging of deeper tissue samples. Based on the above reasons, applying GQDs as contrast agents for in vivo imaging has been the area of high expectations and recurring attention. The near-infrared emitting window shows great advantages for biomedical imaging because of the low tissue absorption and reduced light scattering in more than 650 nm wavelengths' region [31]. Functionalized graphene oxide (GO; 2D)-based nanocomposites are one of the graphene-based nanomaterials that have a great potential for biomedical applications. In recent years, because of their unique and highly enriched physical and chemical properties, such as excellent biocompatibility, ready cellular uptake, flexible chemical modifications, unique optical properties, and thermal and electrical conductivity, they have been used in biological fields, such as biomedicine, biosensors, drug delivery, and bioimaging [32]. Qiu et al. [33] developed the graphene oxide (GO)-wrapped gold nanorods (GO@GNRs) that can be used as a smart and robust nanoplatform for ultrafast NIR SERS bioimaging. Their finding demonstrated that the fabricated GO@GNRs could efficiently load various NIR probes, and the in vitro evaluation indicated that the nanoplatform could exhibit a higher NIR SERS activity in comparison with traditional gold nanostructures.

#### **Author details**

**3. Graphene-based materials for nano-bioimaging**

6 State of the Art in Nano-bioimaging

**Figure 4.** The biomedical applications of graphene. Adapted from Ref. [28].

Among all nanomaterials that are considered as potential candidates for nano-bioimaging applications, graphene has attracted great attentions. As it has been expressed by Lin et al. [28], the biomedical applications of graphene and its derivatives are extensively investigated for diagnostics, drug delivery, near-infrared (NIR) light-induced photothermal therapy, and bioimaging. Due to the versatile surface functionalization and ultrahigh surface area of graphene and its derivatives, they can be easily functionalized by small-molecule dyes, polymers, nanoparticles, drugs, or biomolecules to obtain graphene-based nanomaterials for different bioimaging applications [28]. Lin et al. [28], focused on applying graphene-based nanomaterials for different molecular imaging modalities, and their review confirmed that the graphene-based materials can be employed for optical imaging (FL, two-photon FL, and Raman imaging), PET/SPECT (positron emission tomography/single photon emission computed tomography), MRI (magnetic resonance imaging), PAI (photoacoustic imaging), CT (computed tomography), and multimodal imaging (**Figure 4**). Graphene quantum dots (GQDs) are one of the graphene-based materials that have a considerable potential for bioimaging applications. Due to the photoluminescence (PL) and high structural stability, low cytotoxicity, and good biocompatibility, fluorescent graphene quantum dots (GQDs) have

Morteza Sasani Ghamsari

Address all correspondence to: msghamsari@yahoo.com

Photonics and Quantum Technologies Research School, NSTRI, Tehran, Iran

#### **References**


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**Chapter 2**

**Provisional chapter**

**Recent Advances in Bioimaging for Cancer Research**

Molecular imaging techniques as well as nanoparticle applicable to molecular imaging are being explored to improve the cancer detection accuracy, which help to manage efficiently at the early stage. Among the various imaging technologies, optical imaging is a highly sensitive detection technique that allows direct observation of specific molecular events, biological pathways, and disease processes in real time through imaging probes that emit light in a range of wavelengths. Recently, nanoparticles have provided significant progresses that can be simultaneously used for cancer diagnosis and therapy (cancer theranostics). Theranostics aims to provide "image-guided cancer therapy," by integrating therapeutic and imaging agents in a single platform. In addition, molecular imaging techniques facilitate "image-guided surgery" enabling maximization of tumor excision and minimization of side effects. The optical signals generated by fluorescence nanoparticles offer the possibility to distinguish tumor sites and normal tissues during surgery by real-time guidance, thereby increasing the long-term patient survival. These techniques will considerably contribute to reducing cancer recurrence and developing more effective cures. In this chapter, we will introduce diverse research on nanomaterials-based optical

**Keywords:** molecular imaging, optical imaging, nanoprobe, cancer diagnosis,

**Recent Advances in Bioimaging for Cancer Research**

DOI: 10.5772/intechopen.72725

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

Cancer is one of the leading causes of death. So many researchers have made great efforts to improve cancer management [1]. An early cancer diagnosis provides the most efficient and effective management of cancer treatment with the use of surgical methods or chemotherapeutic agents. Therefore, techniques for detecting cancer at early stages have been developed to improve the detection accuracy. Molecular imaging techniques have undergone explosive growth over the past several decades and are important tools for cancer diagnosis and prognosis

Jae-Woo Lim, Seong Uk Son and Eun-Kyung Lim

Jae-Woo Lim, Seong Uk Son and Eun-Kyung Lim

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.72725

imaging for effective cancer therapy.

imaging-guided therapy, imaging-guided surgery

**Abstract**

**1. Introduction**

**Provisional chapter**

## **Recent Advances in Bioimaging for Cancer Research**

**Recent Advances in Bioimaging for Cancer Research**

DOI: 10.5772/intechopen.72725

Jae-Woo Lim, Seong Uk Son and Eun-Kyung Lim Jae-Woo Lim, Seong Uk Son and Eun-Kyung Lim Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.72725

#### **Abstract**

Molecular imaging techniques as well as nanoparticle applicable to molecular imaging are being explored to improve the cancer detection accuracy, which help to manage efficiently at the early stage. Among the various imaging technologies, optical imaging is a highly sensitive detection technique that allows direct observation of specific molecular events, biological pathways, and disease processes in real time through imaging probes that emit light in a range of wavelengths. Recently, nanoparticles have provided significant progresses that can be simultaneously used for cancer diagnosis and therapy (cancer theranostics). Theranostics aims to provide "image-guided cancer therapy," by integrating therapeutic and imaging agents in a single platform. In addition, molecular imaging techniques facilitate "image-guided surgery" enabling maximization of tumor excision and minimization of side effects. The optical signals generated by fluorescence nanoparticles offer the possibility to distinguish tumor sites and normal tissues during surgery by real-time guidance, thereby increasing the long-term patient survival. These techniques will considerably contribute to reducing cancer recurrence and developing more effective cures. In this chapter, we will introduce diverse research on nanomaterials-based optical imaging for effective cancer therapy.

**Keywords:** molecular imaging, optical imaging, nanoprobe, cancer diagnosis, imaging-guided therapy, imaging-guided surgery

#### **1. Introduction**

Cancer is one of the leading causes of death. So many researchers have made great efforts to improve cancer management [1]. An early cancer diagnosis provides the most efficient and effective management of cancer treatment with the use of surgical methods or chemotherapeutic agents. Therefore, techniques for detecting cancer at early stages have been developed to improve the detection accuracy. Molecular imaging techniques have undergone explosive growth over the past several decades and are important tools for cancer diagnosis and prognosis

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

in the clinic; they include positron emission tomography (PET), computed tomography (CT), magnetic resonance (MR) imaging, and optical imaging [2–4]. Molecular imaging techniques can identify the cancer mass on the basis of its physical properties, which may have major benefits for personalized diagnosis and for the prediction and monitoring of the response to therapy. Many researchers have made efforts to develop diverse imaging probes or contrast agents, thereby enabling the visualization of cellular function and the characterization and measurement of molecular processes in living organisms at the cellular and molecular levels without perturbing them. Such tools can help obtain more accurate information about early-stage cancer using molecular imaging [4]. Among the molecular imaging tools, optical imaging, which includes fluorescence and bioluminescent imaging, can provide particularly highly sensitive detection by using the various wavelengths emitted by fluorescent nanoparticles. In the UV and visible regions, light does not deeply penetrate into tissues, because it is easily absorbed and scattered by endogenous biomolecules (e.g., water and hemoglobin), and tissues generate strong auto-fluorescence [4]. However, light in the near-infrared (NIR) region (~650–900 nm) is minimally absorbed in living tissues and can penetrate more deeply, to a depth of several centimeters, with high signal-to-noise ratios (SNRs) [2]. The development of specific, sensitive, and targeted imaging probes is required for the success of optical imaging techniques in cancer diagnosis. Recently, nanomaterial-based optical imaging probes have been used extensively to non-invasively monitor the target biomolecules or biological pathways for cancer diagnosis and therapy compared with single molecule-based imaging agents. Fluorescent proteins and organic dyes are conventionally used to label cells and subcellular targets due to their small size, good biocompatibility, and water dispersibility. However, fluorescent nanomaterials such as quantum dots (QDs), gold nanoparticles, up-conversion nanocrystals, and silicon nanoparticles have shown several distinct advantages compared to fluorescent proteins and organic dyes [5–9]. These advantages include high resistance to photobleaching (photostability) and high quantum yields (QY), thus enabling the acquisition of optimal information of biological interest with high sensitivity in both *in vitro* and *in vivo* models [9]. In addition, nanomaterials (or nanoparticles) have the advantage that they can be easily modified with different molecules and delivered to the tumor along blood vessels with immune systems [10–13]. In this chapter, we explain the benefits of optical imaging and the importance of nanomaterial-based imaging agents for effective cancer therapy. We will focus on research on using nanomaterials as optical imaging agents and their diverse applications

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 13

Various nanoparticle systems are being explored for their potential use in bioimaging for cancer diagnosis or treatment because of their unique properties, including their large surface-to-volume ratio, high biocompatibility, facile surface modification, and overall structural robustness. In addition, they have unique optical, magnetic, and electron properties, which make them ideal candidates for signal generation and transduction in the development of sensing systems [5–8, 12, 14–20]. Moreover, some nano-sized materials exhibit unique physical properties, such as a proper size, surface charge, stability, shape, and hydrophilicity, which can aid their effective delivery to the desired site. The delivery of nano-sized agents is affected by the enhanced permeability and retention (EPR) effect, which is a unique property of solid tumors that is related to their anatomical and pathological differences from normal tissues. Unlike normal tissues, when tumor tissue produces neovascularization, it contains a discontinuous or absent basement membrane, making it "leaky." Therefore, the pore sizes of the blood vessels in most peripheral human tumors are hundreds of nanometers in diameter. This EPR effect leads to the passive accumulation of large molecules and small particles in tumor tissues due to the cut-off size of the leaky vasculature and retention with long circulation times, which is called passive targeting [21–26]. For successful bioimaging via passive targeting, both a size ranging from 100 to 200 nm in diameter and a prolonged circulation half-life in the blood with biocompatibility are required. Hydrophilic materials such as poly(ethylene glycol) (PEG) have been extensively investigated as effective ways to provide hydrophilic "stealth" properties, resulting in both the inhibition of plasma protein (opsonin) absorption and decreased recognition by the mononuclear phagocytic system (MPS) in the reticuloendothelial system (RES), such as the liver and spleen, thus producing longer circulation times

In addition, positively charged (cationic) nanoparticles can easily enhance endocytosis or phagocytosis for cell labeling via electrostatic interactions with the negatively charged cellular membrane. Among bio-imaging techniques, well-tailored superparamagnetic nanocrystals are of great interest for cancer detection via magnetic resonance (MR) imaging due to their high sensitivity and specificity due to the nanoeffect. Lim et al. [30–32] reported the successful fabrication of various types of water-soluble PEGylated magnetic complexes for magnetism-related biomedical applications and demonstrated their potential as highly efficient MRI imaging agents. Fluorescence and optical imaging techniques are important tools for *in vivo* and cellular imaging, and they can provide vital information for cancer diagnosis and therapy in its early stages. In particular, for the fluorescence wavelength, near-infrared (NIR) light is

**2. Passive and active targeting for cancer imaging**

(**Figure 1**).

**2.1. Passive targeting**

(**Figure 2**) [27–29].

**Figure 1.** Schematic illustration of a multifunctional nanocomposite. Reproduced from Ref. [12] with permission of ACS Publications.

immune systems [10–13]. In this chapter, we explain the benefits of optical imaging and the importance of nanomaterial-based imaging agents for effective cancer therapy. We will focus on research on using nanomaterials as optical imaging agents and their diverse applications (**Figure 1**).

#### **2. Passive and active targeting for cancer imaging**

#### **2.1. Passive targeting**

in the clinic; they include positron emission tomography (PET), computed tomography (CT), magnetic resonance (MR) imaging, and optical imaging [2–4]. Molecular imaging techniques can identify the cancer mass on the basis of its physical properties, which may have major benefits for personalized diagnosis and for the prediction and monitoring of the response to therapy. Many researchers have made efforts to develop diverse imaging probes or contrast agents, thereby enabling the visualization of cellular function and the characterization and measurement of molecular processes in living organisms at the cellular and molecular levels without perturbing them. Such tools can help obtain more accurate information about early-stage cancer using molecular imaging [4]. Among the molecular imaging tools, optical imaging, which includes fluorescence and bioluminescent imaging, can provide particularly highly sensitive detection by using the various wavelengths emitted by fluorescent nanoparticles. In the UV and visible regions, light does not deeply penetrate into tissues, because it is easily absorbed and scattered by endogenous biomolecules (e.g., water and hemoglobin), and tissues generate strong auto-fluorescence [4]. However, light in the near-infrared (NIR) region (~650–900 nm) is minimally absorbed in living tissues and can penetrate more deeply, to a depth of several centimeters, with high signal-to-noise ratios (SNRs) [2]. The development of specific, sensitive, and targeted imaging probes is required for the success of optical imaging techniques in cancer diagnosis. Recently, nanomaterial-based optical imaging probes have been used extensively to non-invasively monitor the target biomolecules or biological pathways for cancer diagnosis and therapy compared with single molecule-based imaging agents. Fluorescent proteins and organic dyes are conventionally used to label cells and subcellular targets due to their small size, good biocompatibility, and water dispersibility. However, fluorescent nanomaterials such as quantum dots (QDs), gold nanoparticles, up-conversion nanocrystals, and silicon nanoparticles have shown several distinct advantages compared to fluorescent proteins and organic dyes [5–9]. These advantages include high resistance to photobleaching (photostability) and high quantum yields (QY), thus enabling the acquisition of optimal information of biological interest with high sensitivity in both *in vitro* and *in vivo* models [9]. In addition, nanomaterials (or nanoparticles) have the advantage that they can be easily modified with different molecules and delivered to the tumor along blood vessels with

**Figure 1.** Schematic illustration of a multifunctional nanocomposite. Reproduced from Ref. [12] with permission of ACS

Publications.

12 State of the Art in Nano-bioimaging

Various nanoparticle systems are being explored for their potential use in bioimaging for cancer diagnosis or treatment because of their unique properties, including their large surface-to-volume ratio, high biocompatibility, facile surface modification, and overall structural robustness. In addition, they have unique optical, magnetic, and electron properties, which make them ideal candidates for signal generation and transduction in the development of sensing systems [5–8, 12, 14–20]. Moreover, some nano-sized materials exhibit unique physical properties, such as a proper size, surface charge, stability, shape, and hydrophilicity, which can aid their effective delivery to the desired site. The delivery of nano-sized agents is affected by the enhanced permeability and retention (EPR) effect, which is a unique property of solid tumors that is related to their anatomical and pathological differences from normal tissues. Unlike normal tissues, when tumor tissue produces neovascularization, it contains a discontinuous or absent basement membrane, making it "leaky." Therefore, the pore sizes of the blood vessels in most peripheral human tumors are hundreds of nanometers in diameter. This EPR effect leads to the passive accumulation of large molecules and small particles in tumor tissues due to the cut-off size of the leaky vasculature and retention with long circulation times, which is called passive targeting [21–26]. For successful bioimaging via passive targeting, both a size ranging from 100 to 200 nm in diameter and a prolonged circulation half-life in the blood with biocompatibility are required. Hydrophilic materials such as poly(ethylene glycol) (PEG) have been extensively investigated as effective ways to provide hydrophilic "stealth" properties, resulting in both the inhibition of plasma protein (opsonin) absorption and decreased recognition by the mononuclear phagocytic system (MPS) in the reticuloendothelial system (RES), such as the liver and spleen, thus producing longer circulation times (**Figure 2**) [27–29].

In addition, positively charged (cationic) nanoparticles can easily enhance endocytosis or phagocytosis for cell labeling via electrostatic interactions with the negatively charged cellular membrane. Among bio-imaging techniques, well-tailored superparamagnetic nanocrystals are of great interest for cancer detection via magnetic resonance (MR) imaging due to their high sensitivity and specificity due to the nanoeffect. Lim et al. [30–32] reported the successful fabrication of various types of water-soluble PEGylated magnetic complexes for magnetism-related biomedical applications and demonstrated their potential as highly efficient MRI imaging agents. Fluorescence and optical imaging techniques are important tools for *in vivo* and cellular imaging, and they can provide vital information for cancer diagnosis and therapy in its early stages. In particular, for the fluorescence wavelength, near-infrared (NIR) light is

**Figure 2.** Main advantages of the PEGylated proteins. PEG is a shielding the protein surface from degradation agents by steric hindrance. Moreover, the increased size of the conjugate decreases the kidney clearance of the PEGylated protein. Reproduced from Ref. [27] with permission of Elsevier.

preferred for tissue and *in vivo* imaging compared to visible light because of its minimal damage to the tissue, which allows deep tissue penetration, and low auto-fluorescence interference due to the reduced scattering of long wavelength photons [9].

capable of spreading to other parts of the body by degrading the basement membrane and forming a new vascular structure. During angiogenesis, a variety of proangiogenic factors is secreted by tumor cells, including vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), basic fibroblast growth factor (bFGF), interleukin-8 (IL-8), and integrin

**Figure 3.** A schematic illustration showing methods used for active targeting of nanoparticles. (A) Antibody-based targeting, (B) Aptamer-based targeting, and (C) Ligand-based targeting of nanoparticels. Reproduced from Ref. [34] with

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 15

. Targeted-molecular imaging of vascular or angiogenesis can provide accurate anatomic details for effective cancer management. Aptamers (Apt) are short nucleic acid molecules that can bind to target antigens with high affinity and specificity. To understand neovascularization and angiogenesis in cancer, Aptαvβ3-conjugated magnetic nanoparticles (Aptαvβ3-MNPs) have been developed to enable the precise detection of integrin-expressing cancer cells using MRI imaging. This work demonstrated that Aptαvβ3-MNPs have the potential to be used for accurate tumor diagnosis [52]. In addition, vascular endothelial growth factor (VEGF121)/ rGel modified MRI imaging agents were developed to obtain sensitive angiogenesis imaging of orthotopic bladder tumors that showed the development of a clear neoangiogenic vascular distribution [53]. The tumor microenvironment plays a critical role in tumor initiation, progression, metastasis, and resistance to therapy [54–61]. The microenvironment differs from that of normal tissues because of the dynamic network within normal tissues, including blood and lymphatic vessels, extracellular matrix proteins, and both enzyme and immune components. These unique characteristics lead to a matrix remodeling (e.g., up-regulation of matrix proteins and activation of specific proteases), a deficiency of oxygen and other nutrients, a decreased pH (low pH), hypoxia and increased amounts of reactive oxygen species (ROS) [57]. The changes in the physiological characteristics of tumor microenvironments are consistent, regardless of the type of cancer, so it is possible to use these as a universal indicator for cancer detection. Vesicular pH plays a pivotal role in cell metabolism processes, such as proliferation and apoptosis. Choi et al. [58] developed a colorimetric redox-polyaniline nanoindicator to simply detect and quantify a broader biogenic pH range with superior sensitivity by employing one-dimensional turn-on of the FRET signal (**Figure 4**). They fabricated polyaniline-based

αv β3

permission of Springer.

#### **2.2. Active targeting**

Active targeting, is also called as ligand-mediated targeting, involves utilizing targeting moieties that are anchored on the surface of nanoparticles and form strong interactions with a particular cell surface marker (e.g., EGFR, HER2/neu, transferrin, CD44) of the target cancer (**Figure 3**) [33, 34].

Targeting moieties, such as antibodies, peptides (Arg-Glyc-Asp (RGD)), nucleic acids (aptamers), and polysaccharides (hyaluronan, dextran), lead to enhanced selective delivery and uptake in the target cells, tissues, organs, or subcellular domains and minimize uptake by the RES system [34–53]. Active tumor targeting is more efficient and specific than passive targeting, and can facilitate early cancer detection. In particular, active tumor-targeted imaging can quantify the target expression through molecular imaging, so it is an indispensable tool in diagnosis and disease management. For example, for the selective detection of tumors expressing a high level of epidermal growth factor receptors (EGFR), anti-EGFR antibodymodified nanoparticles are widely used as imaging agents for MR, CT, and optical imaging. CD44 is a cell surface glycoprotein that is overexpressed in breast cancer and gastric cancer stem cells and is associated with cancer growth, migration, invasion, and angiogenesis. Hyaluronan (HA), which is an immune–neutral polysaccharide, forms a specific interaction with CD44. Lim et al. [50, 51] developed a hyaluronan-modified magnetic nanoprobe for detecting CD44-overexpressing breast cancer via MR imaging, which showed superior targeting efficiency with MR sensitivity in *in vitro* and *in vivo* studies. Angiogenesis appears to be one of the most crucial steps in tumor translation to the metastatic form, in which it is

**Figure 3.** A schematic illustration showing methods used for active targeting of nanoparticles. (A) Antibody-based targeting, (B) Aptamer-based targeting, and (C) Ligand-based targeting of nanoparticels. Reproduced from Ref. [34] with permission of Springer.

preferred for tissue and *in vivo* imaging compared to visible light because of its minimal damage to the tissue, which allows deep tissue penetration, and low auto-fluorescence interference

**Figure 2.** Main advantages of the PEGylated proteins. PEG is a shielding the protein surface from degradation agents by steric hindrance. Moreover, the increased size of the conjugate decreases the kidney clearance of the PEGylated protein.

Active targeting, is also called as ligand-mediated targeting, involves utilizing targeting moieties that are anchored on the surface of nanoparticles and form strong interactions with a particular cell surface marker (e.g., EGFR, HER2/neu, transferrin, CD44) of the target cancer

Targeting moieties, such as antibodies, peptides (Arg-Glyc-Asp (RGD)), nucleic acids (aptamers), and polysaccharides (hyaluronan, dextran), lead to enhanced selective delivery and uptake in the target cells, tissues, organs, or subcellular domains and minimize uptake by the RES system [34–53]. Active tumor targeting is more efficient and specific than passive targeting, and can facilitate early cancer detection. In particular, active tumor-targeted imaging can quantify the target expression through molecular imaging, so it is an indispensable tool in diagnosis and disease management. For example, for the selective detection of tumors expressing a high level of epidermal growth factor receptors (EGFR), anti-EGFR antibodymodified nanoparticles are widely used as imaging agents for MR, CT, and optical imaging. CD44 is a cell surface glycoprotein that is overexpressed in breast cancer and gastric cancer stem cells and is associated with cancer growth, migration, invasion, and angiogenesis. Hyaluronan (HA), which is an immune–neutral polysaccharide, forms a specific interaction with CD44. Lim et al. [50, 51] developed a hyaluronan-modified magnetic nanoprobe for detecting CD44-overexpressing breast cancer via MR imaging, which showed superior targeting efficiency with MR sensitivity in *in vitro* and *in vivo* studies. Angiogenesis appears to be one of the most crucial steps in tumor translation to the metastatic form, in which it is

due to the reduced scattering of long wavelength photons [9].

Reproduced from Ref. [27] with permission of Elsevier.

**2.2. Active targeting**

14 State of the Art in Nano-bioimaging

(**Figure 3**) [33, 34].

capable of spreading to other parts of the body by degrading the basement membrane and forming a new vascular structure. During angiogenesis, a variety of proangiogenic factors is secreted by tumor cells, including vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), basic fibroblast growth factor (bFGF), interleukin-8 (IL-8), and integrin αv β3 . Targeted-molecular imaging of vascular or angiogenesis can provide accurate anatomic details for effective cancer management. Aptamers (Apt) are short nucleic acid molecules that can bind to target antigens with high affinity and specificity. To understand neovascularization and angiogenesis in cancer, Aptαvβ3-conjugated magnetic nanoparticles (Aptαvβ3-MNPs) have been developed to enable the precise detection of integrin-expressing cancer cells using MRI imaging. This work demonstrated that Aptαvβ3-MNPs have the potential to be used for accurate tumor diagnosis [52]. In addition, vascular endothelial growth factor (VEGF121)/ rGel modified MRI imaging agents were developed to obtain sensitive angiogenesis imaging of orthotopic bladder tumors that showed the development of a clear neoangiogenic vascular distribution [53]. The tumor microenvironment plays a critical role in tumor initiation, progression, metastasis, and resistance to therapy [54–61]. The microenvironment differs from that of normal tissues because of the dynamic network within normal tissues, including blood and lymphatic vessels, extracellular matrix proteins, and both enzyme and immune components. These unique characteristics lead to a matrix remodeling (e.g., up-regulation of matrix proteins and activation of specific proteases), a deficiency of oxygen and other nutrients, a decreased pH (low pH), hypoxia and increased amounts of reactive oxygen species (ROS) [57]. The changes in the physiological characteristics of tumor microenvironments are consistent, regardless of the type of cancer, so it is possible to use these as a universal indicator for cancer detection. Vesicular pH plays a pivotal role in cell metabolism processes, such as proliferation and apoptosis. Choi et al. [58] developed a colorimetric redox-polyaniline nanoindicator to simply detect and quantify a broader biogenic pH range with superior sensitivity by employing one-dimensional turn-on of the FRET signal (**Figure 4**). They fabricated polyaniline-based

**Figure 4.** (A) Schematic illustration of organic nanoindicator based on polyaniline nanoparticle for the detection of endolysosomal compartments. Synthesis steps of nanoindicator based on polyaniline in mesosilica template when using heterometal nanoparticle (IsNP) as oxidant. Emission of FPSNICy7 appears at endosomes. While migrating from endosomes to lysosomes, transition state of polyaniline transferred to emeraldine salt state due to the increment of proton concentration. The emission of FPSNICy3 gradually appears at lysosomes. (B) Redox switching property and sensitivity of PSNI from pH 3.95 to 7.23. Reproduced from Ref. [58] with permission of Springer.

nanoprobes that exhibited convertible transition states according to the proton concentration as an *in situ* indicator of the vesicular transport pH [58].

i.e., hyaluronic acid (HA)-based nanocontainers containing miRNA-34a beacons (bHNCs), for the intracellular recognition of miRNA-34a levels in metastatic breast cancer cells. They confirmed the microRNA-34a expression levels through *in vitro* and *in vivo* optical imaging

**Figure 5.** (A) Schematic illustration of the dual imaging process of anchored proteinase-targetable optomagentic nanoprobes with activatable fluorogenic peptides (MNC-ActFP). Reproduced from Ref. [60] with permission of Wiley-VCH. (B) Schematic illustration of miR-34a beacon delivery system for targeted intracellular recognition of miR-34a based on Hyaluronic acid (HA)-coated nanocontainers that encapsulate the miR-34a beacons (bHNCs). Reproduced

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 17

Current imaging techniques play an important role in enabling the early detection of several diseases, including cancer, due to their ability to locate tumors and assess the tumor activity. The characteristics of various imaging modalities are briefly summarized (**Table 1**) [7, 64]. However, these techniques are insufficient to provide reliable and accurate information at the disease site, due to their low sensitivity or limits in their spatial resolution (**Table 1**). Computed tomography (CT) is useful for tumor staging but offers poor soft tissue contrast, with resulting poor sensitivity and specificity in screening. Magnetic resonance imaging (MRI) offers excellent contrast without ionizing radiation but has temporal and financial needs that are likely inconsistent with high-throughput screening. Positron emission tomography (PET), which has very high sensitivity, can investigate various molecular and biochemical properties but is more suitable for monitoring the response to therapy than for detecting early lesions due to its limited spatial resolution. Therefore, multimodal imaging, i.e., the integration of two or more imaging techniques in a single examination, should offer the synergistic advantages of each to provide accurate information for tumor diagnosis such as high spatial resolution, soft tissue contrast, and biological information on the molecular level with high sensitivity [46, 65–73]. Recently, various types of hybrid nanoparticles have

using bHNCs (**Figure 5(B)**) [61].

from Ref. [61] with permission of ACS Publications.

**3. Multimodal imaging for cancer imaging**

The tumor pH is usually more acidic than that of normal tissues due to increased aerobic glycolysis, which is called the Warburg effect (tumor have a pH of 6.2–6.9, and normal tissues have a pH of 7.4) [62, 63]. This can promote tumor metastasis by generating an invasive environment for tearing down the extracellular matrix and for tissue remodeling. Many studies have reported signal "off–on" imaging agents activated by pH, such as fluorescence probes and MRI contrast agents that target the acidic pH conditions of tumors for tumor imaging [12, 13, 59]. Kim et al. [59] have developed a pH-responsive T1 (which is the recovery of magnetization along the longitudinal axis) contrast agent for MR imaging. Core–shell MnO@ Mn3 O4 urchin-shaped nanoparticles are synthesized via an anisotropic etching process. The manganese ions released from the MnO phase in the low-pH sites within tumor cells lead to an enhanced T1 contrast image for the entire tumor mass. In addition, specific stromal cell-derived proteases, such as matrix metalloproteases (MMP), matrix cysteine cathepsins, and serine proteases, are overexpressed in primary tumors. These proteases induce the epithelial-to-mesenchymal transition (EMT) and promote invasion and metastasis by degrading the extracellular membrane. Molecular imaging of the activity of proteases has the potential to determine tumor malignancy, guide the development of diagnostic tools, and evaluate the efficacy of treatment (**Figure 5(A)**) [60]. MMPs are the most prominent family of proteases associated with tumorigenesis. Their expression and activity are highly enhanced in many types of human cancer and are strongly implicated in advanced cancer states. Tumor microenvironment-targeted molecular imaging has the potential to provide clinically significant progress. Emerging evidence suggests that microRNAs can also function as a diagnostic biomarker for human cancers because they can act as tumor suppressor genes or oncogenes. Imaging the intracellular distribution of specific miRNAs should provide insight into the mechanisms of metastasis and invasion. Kim et al. [61] reported smart nanoprobes,

**Figure 5.** (A) Schematic illustration of the dual imaging process of anchored proteinase-targetable optomagentic nanoprobes with activatable fluorogenic peptides (MNC-ActFP). Reproduced from Ref. [60] with permission of Wiley-VCH. (B) Schematic illustration of miR-34a beacon delivery system for targeted intracellular recognition of miR-34a based on Hyaluronic acid (HA)-coated nanocontainers that encapsulate the miR-34a beacons (bHNCs). Reproduced from Ref. [61] with permission of ACS Publications.

i.e., hyaluronic acid (HA)-based nanocontainers containing miRNA-34a beacons (bHNCs), for the intracellular recognition of miRNA-34a levels in metastatic breast cancer cells. They confirmed the microRNA-34a expression levels through *in vitro* and *in vivo* optical imaging using bHNCs (**Figure 5(B)**) [61].

#### **3. Multimodal imaging for cancer imaging**

nanoprobes that exhibited convertible transition states according to the proton concentration

sensitivity of PSNI from pH 3.95 to 7.23. Reproduced from Ref. [58] with permission of Springer.

**Figure 4.** (A) Schematic illustration of organic nanoindicator based on polyaniline nanoparticle for the detection of endolysosomal compartments. Synthesis steps of nanoindicator based on polyaniline in mesosilica template when using heterometal nanoparticle (IsNP) as oxidant. Emission of FPSNICy7 appears at endosomes. While migrating from endosomes to lysosomes, transition state of polyaniline transferred to emeraldine salt state due to the increment of proton concentration. The emission of FPSNICy3 gradually appears at lysosomes. (B) Redox switching property and

The tumor pH is usually more acidic than that of normal tissues due to increased aerobic glycolysis, which is called the Warburg effect (tumor have a pH of 6.2–6.9, and normal tissues have a pH of 7.4) [62, 63]. This can promote tumor metastasis by generating an invasive environment for tearing down the extracellular matrix and for tissue remodeling. Many studies have reported signal "off–on" imaging agents activated by pH, such as fluorescence probes and MRI contrast agents that target the acidic pH conditions of tumors for tumor imaging [12, 13, 59]. Kim et al. [59] have developed a pH-responsive T1 (which is the recovery of magnetization along the longitudinal axis) contrast agent for MR imaging. Core–shell MnO@

 urchin-shaped nanoparticles are synthesized via an anisotropic etching process. The manganese ions released from the MnO phase in the low-pH sites within tumor cells lead to an enhanced T1 contrast image for the entire tumor mass. In addition, specific stromal cell-derived proteases, such as matrix metalloproteases (MMP), matrix cysteine cathepsins, and serine proteases, are overexpressed in primary tumors. These proteases induce the epithelial-to-mesenchymal transition (EMT) and promote invasion and metastasis by degrading the extracellular membrane. Molecular imaging of the activity of proteases has the potential to determine tumor malignancy, guide the development of diagnostic tools, and evaluate the efficacy of treatment (**Figure 5(A)**) [60]. MMPs are the most prominent family of proteases associated with tumorigenesis. Their expression and activity are highly enhanced in many types of human cancer and are strongly implicated in advanced cancer states. Tumor microenvironment-targeted molecular imaging has the potential to provide clinically significant progress. Emerging evidence suggests that microRNAs can also function as a diagnostic biomarker for human cancers because they can act as tumor suppressor genes or oncogenes. Imaging the intracellular distribution of specific miRNAs should provide insight into the mechanisms of metastasis and invasion. Kim et al. [61] reported smart nanoprobes,

as an *in situ* indicator of the vesicular transport pH [58].

16 State of the Art in Nano-bioimaging

Mn3 O4 Current imaging techniques play an important role in enabling the early detection of several diseases, including cancer, due to their ability to locate tumors and assess the tumor activity. The characteristics of various imaging modalities are briefly summarized (**Table 1**) [7, 64]. However, these techniques are insufficient to provide reliable and accurate information at the disease site, due to their low sensitivity or limits in their spatial resolution (**Table 1**).

Computed tomography (CT) is useful for tumor staging but offers poor soft tissue contrast, with resulting poor sensitivity and specificity in screening. Magnetic resonance imaging (MRI) offers excellent contrast without ionizing radiation but has temporal and financial needs that are likely inconsistent with high-throughput screening. Positron emission tomography (PET), which has very high sensitivity, can investigate various molecular and biochemical properties but is more suitable for monitoring the response to therapy than for detecting early lesions due to its limited spatial resolution. Therefore, multimodal imaging, i.e., the integration of two or more imaging techniques in a single examination, should offer the synergistic advantages of each to provide accurate information for tumor diagnosis such as high spatial resolution, soft tissue contrast, and biological information on the molecular level with high sensitivity [46, 65–73]. Recently, various types of hybrid nanoparticles have been used for multimodal imaging by combining the strengths of individual components into single nano-structured systems. Multimodal imaging probes enable both magnetic and optical imaging to provide great benefits for *in vivo* disease diagnosis and the *in situ* monitoring of living cells. In addition, it is reported that MR/CT multimodal nanoprobes can provide complementary information for tumor-associated blood vessels and the tumor microenvironment [71]. Uniformly sized tantalum oxide nanoparticles were synthesized using a microemulsion method and were modified using various silane derivatives, such as polyethylene glycol (PEG) and fluorescent dye molecules, through simple *in situ* sol-gel reaction. These nanoparticles exhibited remarkable performances in *in vivo* simultaneous fluorescence imaging as well as X-ray CT angiography and bimodal image-guided lymph node mapping [72].

Lim et al. [73] developed fluorescent magnetic nanoprobes to acquire biological information at different object levels, i.e., *in vivo* detection and *ex vivo* validation, for characterizing tumor angiogenesis, in which magnetic nanocrystals are encapsulated by the fluorescent amphiphilic polymer (**Figure 6**). Additionally, targeted multimodal imaging systems by modifying targeting moieties to increase the selective accumulation at the disease site has shown promising results. In this case, several factors should be considered, including the appropriate choice of a targeting moiety and its conjugation method. Yang et al. [49] developed

Cetuximab-conjugated fluorescent magnetic nanohybrids (CET-FMNHs) that served as effective agents for both magnetic resonance (MR) and fluorescence optical imaging of human

**Figure 6.** (A) Illustration of simultaneously self-assembled fluorescent magnetic nanoprobes (FMNPs) as multimodal biomedical imaging probes. (B) MR images of tumor-bearing mice after injection of the FMNPs (i: xenograft tumor model and ii: orthotopic bladder tumor model) and (C) fluorescence images of their excised tumor slides, respectively.

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 19

Recently, nanoparticles have provided significant progress in cancer theranostics due to their unique physicochemical properties, in which both diagnosis and therapeutic functions can be achieved simultaneously. Theranostics aims to provide image-guided cancer therapy by integrating imaging and therapy, which are particularly interesting fields in Nanomedicine [12]. Theranostic nanoparticles comprise at least three components: (i) the biological payload, (ii) the carrier, and (iii) surface modifiers (**Figure 1**) [74–93]. Biological payloads include imaging agents and therapeutic agents. Therefore, they can allow the simultaneous delivery of therapeutic agents to the tumor site and real-time tracking of their biodistribution *in vivo*. Optical imaging has advantages in theranostics because it allows the non-invasive monitoring of the progression of diseases and therapy [84]. For example, Misra et al. [85] synthesized blue-lightemitting ZnO quantum dots combined with biodegradable chitosan (N-acetylglucosamine) for tumor-targeted drug delivery (a ZnO-QD-chitosan-folate carrier), which was loaded with an anti-cancer drug (DOX). The DOX-loaded ZnO-QD-chitosan-folate carrier exhibited highly stable QDs because of its hydrophilicity and the cationic charge of chitosan as well as

Ryu et al. [86–89] developed chitosan-based nanoparticles (CNPs) that were labeled with Cy 5.5 for optical imaging and encapsulated with paclitaxel (PTX) as an anticancer drug

epithelial cancer.

**4. Optical-imaging-based cancer therapy**

Reproduced from Ref. [73] with permission of Elsevier.

**4.1. Optical imaging in drug delivery (Theranostics)**

a rapid drug release profile with a controlled release.


Reproduced from Ref. [12] with permission of ACS Publications.

**Table 1.** Characteristics of imaging modalities.

**Figure 6.** (A) Illustration of simultaneously self-assembled fluorescent magnetic nanoprobes (FMNPs) as multimodal biomedical imaging probes. (B) MR images of tumor-bearing mice after injection of the FMNPs (i: xenograft tumor model and ii: orthotopic bladder tumor model) and (C) fluorescence images of their excised tumor slides, respectively. Reproduced from Ref. [73] with permission of Elsevier.

Cetuximab-conjugated fluorescent magnetic nanohybrids (CET-FMNHs) that served as effective agents for both magnetic resonance (MR) and fluorescence optical imaging of human epithelial cancer.

#### **4. Optical-imaging-based cancer therapy**

been used for multimodal imaging by combining the strengths of individual components into single nano-structured systems. Multimodal imaging probes enable both magnetic and optical imaging to provide great benefits for *in vivo* disease diagnosis and the *in situ* monitoring of living cells. In addition, it is reported that MR/CT multimodal nanoprobes can provide complementary information for tumor-associated blood vessels and the tumor microenvironment [71]. Uniformly sized tantalum oxide nanoparticles were synthesized using a microemulsion method and were modified using various silane derivatives, such as polyethylene glycol (PEG) and fluorescent dye molecules, through simple *in situ* sol-gel reaction. These nanoparticles exhibited remarkable performances in *in vivo* simultaneous fluorescence imaging as well as X-ray CT angiography and bimodal image-guided lymph

Lim et al. [73] developed fluorescent magnetic nanoprobes to acquire biological information at different object levels, i.e., *in vivo* detection and *ex vivo* validation, for characterizing tumor angiogenesis, in which magnetic nanocrystals are encapsulated by the fluorescent amphiphilic polymer (**Figure 6**). Additionally, targeted multimodal imaging systems by modifying targeting moieties to increase the selective accumulation at the disease site has shown promising results. In this case, several factors should be considered, including the appropriate choice of a targeting moiety and its conjugation method. Yang et al. [49] developed

**resolution**

<1 cm Seconds to minutes

No limit Minutes to hours

minutes

Second to minutes

mm to cm

CT imaging X-ray No limit Minutes Noninvasiveness, high

**Advantage Disadvantage**

Relatively low spatial

Exposure to ionizing radiation, relatively low spatial resolution

Relatively high dose of ionizing radiation, limited soft tissue resolution, exposure to ionizing radiation

Limited spatial resolution, unsuitable for examination of digestive organs and

bone

resolution

Relative low sensitivity, long scan and post-processing time, mass quantity of probe may be needed

Noninvasiveness, no harmful effect by nonionizing radiation

Noninvasiveness, high spatial resolution

Noninvasiveness, high

Noninvasiveness, real time, low cost, no harmful effects by nonionizing

contrast resolution

sensitivity

radiation

node mapping [72].

18 State of the Art in Nano-bioimaging

Optical imaging

Ultrasound imaging

**Modality Energy source Depth Temporal** 

Visible light or near-infrared

magnetic field

High-frequency sound

PET imaging High-energy γ rays No limit 10 s to

Reproduced from Ref. [12] with permission of ACS Publications.

**Table 1.** Characteristics of imaging modalities.

MR imaging Radiofrequency

#### **4.1. Optical imaging in drug delivery (Theranostics)**

Recently, nanoparticles have provided significant progress in cancer theranostics due to their unique physicochemical properties, in which both diagnosis and therapeutic functions can be achieved simultaneously. Theranostics aims to provide image-guided cancer therapy by integrating imaging and therapy, which are particularly interesting fields in Nanomedicine [12]. Theranostic nanoparticles comprise at least three components: (i) the biological payload, (ii) the carrier, and (iii) surface modifiers (**Figure 1**) [74–93]. Biological payloads include imaging agents and therapeutic agents. Therefore, they can allow the simultaneous delivery of therapeutic agents to the tumor site and real-time tracking of their biodistribution *in vivo*. Optical imaging has advantages in theranostics because it allows the non-invasive monitoring of the progression of diseases and therapy [84]. For example, Misra et al. [85] synthesized blue-lightemitting ZnO quantum dots combined with biodegradable chitosan (N-acetylglucosamine) for tumor-targeted drug delivery (a ZnO-QD-chitosan-folate carrier), which was loaded with an anti-cancer drug (DOX). The DOX-loaded ZnO-QD-chitosan-folate carrier exhibited highly stable QDs because of its hydrophilicity and the cationic charge of chitosan as well as a rapid drug release profile with a controlled release.

Ryu et al. [86–89] developed chitosan-based nanoparticles (CNPs) that were labeled with Cy 5.5 for optical imaging and encapsulated with paclitaxel (PTX) as an anticancer drug (PTX-Cy5.5-CNP) (**Figure 7**). They confirmed that the PTX-Cy5.5-CNP was effectively delivered to the tumor sites by optical imaging and that it showed enhanced therapeutic efficacy in tumor tissues while minimizing its toxicity to normal tissues. Smart theranostic nanosystems that respond to environmental changes (e.g., pH) have been designed for controlled drug release, low drug loss and low side effects [90–92]. Wu et al. prepared nanogels via the *in situ* immobilization of CdSe quantum dots (QDs) in the interior of pH and temperature-responsive hydroxypropylcellulose-poly(acrylic acid) (HPC-PAA) semi-interpenetrating (semi-IPN) polymer networks (HPC-PAA-CdSe hybrid nanogels). These nanogels demonstrated potential as excellent drug carriers, providing a high drug loading capacity for TMZ as a model anticancer drug and offering the possibility of pH-regulated drug delivery [93]. Jang et al. [94] used nanovesicles containing poly(L-lysine-graft-imidazole) (PLI)/miR complexes (NVs/miR) to systemically deliver miR-34a for CD44 expression-based cancer therapy (**Figure 8**).

In this system, the PLI acts to deliver miRNA to the site of action via the buffering effect of the imidazole residues under endosomal pH. This systemic delivery of miR-34a using our NVs shows the most favorable delivery efficiency, a significant suppression of CD44 expression, and increased apoptosis in the *in vivo* models [94]. In optical imaging, fluorophores, such as fluorescent dyes, bioluminescent proteins and fluorescent proteins, are widely used to monitor molecular events. However, they are easily susceptible to photobleaching. Fluorescent nanoparticles (e.g., quantum dots, upconversion nanoparticles) were developed that complement the weakness of fluorophores; however, they also exhibited potential toxicity [95]. Among various nanoparticles, gold nanoparticles are the most widely used in the biomedical field because of their advantageous properties such as biocompatibility and facile modification [96–102]. According to their size, shape, and structure, they also have controllable surface plasmon resonance (SPR). Among gold nanoparticles, rod-shaped gold nanoparticles

(gold nanorods) can be used as direct NIR absorption imaging probes because their main

**Figure 8.** (A) Schematic illustration and characterization of nanovesicles containing PLI/miR complexes (NVs/miR) that proton buffering promoted by protonation of a pH-responsive cationic polymer, poly(L-lysine-graft-imidazole (PLI), at endosomal pH, (B) *in vivo* anti-tumor effects induced by NVs/miR-34a, (C) I optical images of Cy5.5-labeled NVs containing PLI/fluorescein-labeled miR (Cy5.5-NVs/FL-miR) in an MKN-74 gastric subcutaneous xenograft model after intravenous injection of Cy5.5-NVs/FL-miR at various time intervals (pre-injection, 0, 3, and 6 h) and (D) its photon counts from the tumor regions after injection of Cy5.5-NVs/FL-miR. (E) *Ex vivo* optical images of excised organs (liver, stomach, brain, lung, kidney, spleen, heart, and muscle) at 6 h after injection of Cy5.5-NVs/FL-miR. The intensity maps on the fluorescence images display normalized photon counts and (D) confocal microscopy images of tumor sections from mice treated with Cy5.5-NVs/FL-miR. Green, red, and blue represent FL from miR, Cy5.5 from NVs, and Hoechst

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 21

Choi et al. noted that cRGD-conjugated gold nanorods showed excellent tumor targeting ability via NIR absorption imaging with no cytotoxicity. Additionally, the nanorods showed sufficient cellular uptake in a glioblastoma *in vivo* model, thus demonstrating their potential

 integrin-targeted imaging probes [103, 104]. In particular, gold nanoparticles are useful for image-guided thermal therapy (also called hyperthermia or photothermal therapy) because they can absorb laser irradiation and convert the energy into a heat source via electron excitation and relaxation. Hyperthermia can induce apoptotic cell death in tumor tissues via heat generation, which provides a less invasive and localized therapy for cancer. As a result, it has been used to improve therapeutic efficacy and survival rates in combination with radiotherapy or chemotherapy for tumors. Choi et al. [105, 106] also prepared Cetuximab (CET)-conjugated gold nanorods and evaluated their hyperthermal properties under NIR irradiation (**Figure 9**). Gold nanorods have been frequently used to trigger hyperthermia in combination with an NIR laser, which is more effective for tissue penetration than are UV and visible light. After NIR laser irradiation, CET-PGNRs showed strong therapeutic efficacy in tumor-bearing mice, thus demonstrating the potential of CET-PGNRs for simultaneous

absorption band is located in the NIR region due to the longitudinal surface plasmon.

33342 from nucleus, respectively. Reproduced from Ref. [94] with permission of Elsevier.

as α<sup>v</sup> β3

**Figure 7.** Theragnostic chitosan-based nanoparticles (CNPs) for cancer imaging and chemotherapy. (A) Conceptual description of theragnostic nanoparticles labeled with Cy5.5 for imaging and encapsulated with PTX for cancer therapy (PTX–Cy5.5–CNP). (B) *In vivo* images of the tumor-bearing mice treated with PTX–Cy5.5–CNP of different drug concentrations (5, 10, and 20 mg/kg) every third day. Reproduced from Ref. [88] with permission of Elsevier.

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 21

(PTX-Cy5.5-CNP) (**Figure 7**). They confirmed that the PTX-Cy5.5-CNP was effectively delivered to the tumor sites by optical imaging and that it showed enhanced therapeutic efficacy in tumor tissues while minimizing its toxicity to normal tissues. Smart theranostic nanosystems that respond to environmental changes (e.g., pH) have been designed for controlled drug release, low drug loss and low side effects [90–92]. Wu et al. prepared nanogels via the *in situ* immobilization of CdSe quantum dots (QDs) in the interior of pH and temperature-responsive hydroxypropylcellulose-poly(acrylic acid) (HPC-PAA) semi-interpenetrating (semi-IPN) polymer networks (HPC-PAA-CdSe hybrid nanogels). These nanogels demonstrated potential as excellent drug carriers, providing a high drug loading capacity for TMZ as a model anticancer drug and offering the possibility of pH-regulated drug delivery [93]. Jang et al. [94] used nanovesicles containing poly(L-lysine-graft-imidazole) (PLI)/miR complexes (NVs/miR) to

20 State of the Art in Nano-bioimaging

systemically deliver miR-34a for CD44 expression-based cancer therapy (**Figure 8**).

In this system, the PLI acts to deliver miRNA to the site of action via the buffering effect of the imidazole residues under endosomal pH. This systemic delivery of miR-34a using our NVs shows the most favorable delivery efficiency, a significant suppression of CD44 expression, and increased apoptosis in the *in vivo* models [94]. In optical imaging, fluorophores, such as fluorescent dyes, bioluminescent proteins and fluorescent proteins, are widely used to monitor molecular events. However, they are easily susceptible to photobleaching. Fluorescent nanoparticles (e.g., quantum dots, upconversion nanoparticles) were developed that complement the weakness of fluorophores; however, they also exhibited potential toxicity [95]. Among various nanoparticles, gold nanoparticles are the most widely used in the biomedical field because of their advantageous properties such as biocompatibility and facile modification [96–102]. According to their size, shape, and structure, they also have controllable surface plasmon resonance (SPR). Among gold nanoparticles, rod-shaped gold nanoparticles

**Figure 7.** Theragnostic chitosan-based nanoparticles (CNPs) for cancer imaging and chemotherapy. (A) Conceptual description of theragnostic nanoparticles labeled with Cy5.5 for imaging and encapsulated with PTX for cancer therapy (PTX–Cy5.5–CNP). (B) *In vivo* images of the tumor-bearing mice treated with PTX–Cy5.5–CNP of different drug

concentrations (5, 10, and 20 mg/kg) every third day. Reproduced from Ref. [88] with permission of Elsevier.

**Figure 8.** (A) Schematic illustration and characterization of nanovesicles containing PLI/miR complexes (NVs/miR) that proton buffering promoted by protonation of a pH-responsive cationic polymer, poly(L-lysine-graft-imidazole (PLI), at endosomal pH, (B) *in vivo* anti-tumor effects induced by NVs/miR-34a, (C) I optical images of Cy5.5-labeled NVs containing PLI/fluorescein-labeled miR (Cy5.5-NVs/FL-miR) in an MKN-74 gastric subcutaneous xenograft model after intravenous injection of Cy5.5-NVs/FL-miR at various time intervals (pre-injection, 0, 3, and 6 h) and (D) its photon counts from the tumor regions after injection of Cy5.5-NVs/FL-miR. (E) *Ex vivo* optical images of excised organs (liver, stomach, brain, lung, kidney, spleen, heart, and muscle) at 6 h after injection of Cy5.5-NVs/FL-miR. The intensity maps on the fluorescence images display normalized photon counts and (D) confocal microscopy images of tumor sections from mice treated with Cy5.5-NVs/FL-miR. Green, red, and blue represent FL from miR, Cy5.5 from NVs, and Hoechst 33342 from nucleus, respectively. Reproduced from Ref. [94] with permission of Elsevier.

(gold nanorods) can be used as direct NIR absorption imaging probes because their main absorption band is located in the NIR region due to the longitudinal surface plasmon.

Choi et al. noted that cRGD-conjugated gold nanorods showed excellent tumor targeting ability via NIR absorption imaging with no cytotoxicity. Additionally, the nanorods showed sufficient cellular uptake in a glioblastoma *in vivo* model, thus demonstrating their potential as α<sup>v</sup> β3 integrin-targeted imaging probes [103, 104]. In particular, gold nanoparticles are useful for image-guided thermal therapy (also called hyperthermia or photothermal therapy) because they can absorb laser irradiation and convert the energy into a heat source via electron excitation and relaxation. Hyperthermia can induce apoptotic cell death in tumor tissues via heat generation, which provides a less invasive and localized therapy for cancer. As a result, it has been used to improve therapeutic efficacy and survival rates in combination with radiotherapy or chemotherapy for tumors. Choi et al. [105, 106] also prepared Cetuximab (CET)-conjugated gold nanorods and evaluated their hyperthermal properties under NIR irradiation (**Figure 9**). Gold nanorods have been frequently used to trigger hyperthermia in combination with an NIR laser, which is more effective for tissue penetration than are UV and visible light. After NIR laser irradiation, CET-PGNRs showed strong therapeutic efficacy in tumor-bearing mice, thus demonstrating the potential of CET-PGNRs for simultaneous

**Figure 9.** (A) Schematic illustration of CET-PGNRs as NIR absorption imaging and photothermal therapeutic agents for epithelial cancer. (B) Noninvasive NIR absorption *in vivo* images of tumor tissues for intravenous injected CET-PGNRs or PGNRs (control); white-dotted circles indicate the tumor regions. (C) Silver staining eosin. Tumor region was characterized by extensive pyknosis (green arrows) and cell vacuolization (white arrows) only in mice treated with CET-PGNRs after NIR laser irradiation. Reproduced from Ref. [12] with permission of ACS Publications.

absorption imaging and photothermal ablation of epithelial cancer cells with excellent targeting ability. Additionally, Choi et al. demonstrated highly sensitive terahertz (THz) molecular imaging using same probe (CET-PGNR) in both *in vitro* and *in vivo* models, indicating that its high thermal sensitivity can help extend photonic-based photothermal molecular imaging and be used for monitoring drug delivery processes and for early cancer diagnosis [105, 106]. Nam et al. developed "smart" gold nanoparticles that enable aggregation in mild acidic intracellular environments due to their hydrolysis-susceptible citraconic amide surface, which induces a shift in the absorption to longer wavelength, in the far-red and near-infrared (NIR) regions. This smart feature is useful for photothermal cancer therapy [107].

are highly specific to tumor cells. Lovell et al. [116] have developed hydrogels using crosslinked porphyrin co-monomers as strong optical tracers (**Figure 10(A)**). In *in vivo* studies, these could be used for the non-invasive fluorescence monitoring of subcutaneously implanted hydrogels over 2 months, without adverse effects or behavior. In addition, it was possible to non-invasively visualize where the gel was located and whether hydrogel degradation or photobleaching occurred. After surgical resection, while no residual fluorescence was detected in the mouse, hydrogel fluorescence was definitely recognized in the removed gel [116]. Hill et al. [117] demonstrated hyaluronic acid (HLA)-derived nanoparticles containing an indocyanine green (ICG) as near-infrared dye (NanoICG) for well delivery to tumors (**Figure 10(B)**). NanoICG exhibited quenched fluorescence and could be activated by disassembly in a mixed

presence of NanoICG. Reproduced from Refs. [116, 117] with permission of ACS Publications.

**Figure 10.** (A) Porphyrin-cross-linked hydrogels and noninvasive monitoring and image-guided surgical resection by using them. (i) Structures of mTCPP (green) and PEG diamine (red). (ii) Schematic of the hydrogel. (e), from left to right, (iii) fluorescence images of a mouse with the hydrogel implanted subcutaneously and monitored noninvasively. (iv) Screen captures from a fluorescence camera used to guide fluorescently the surgical removal of the hydrogel in real time. Fluorescence was readily apparent transdermally (T.D.) or through the open incision, as indicated. (B) Hydrophobic moieties conjugated to HLA drive self-assembly into nanoparticles that can entrap ICG. Indocyanine green-loaded nanoparticles for image-guided tumor surgery (i) hydrophobic moieties conjugated to HLA drive self-assembly into nanoparticles that can entrap ICG. (ii) Preoperative imaging and (iii) postoperative imaging of iRFP shows the location of MDA-MB-231 breast tumor xenograft. Red arrows indicated extracted tumors, where iRFP signal showed due to the

Recent Advances in Bioimaging for Cancer Research http://dx.doi.org/10.5772/intechopen.72725 23

in a breast tumor xenograft model. The NanoICG were more completely delivered to tumors compared to free ICG, with strong contrast enhancement in the tumor with a lower background signal in the surrounding tissue, thus demonstrating the potential of the NanoICG

Optical imaging is a powerful tool that can provide the real-time and direct observation of specific molecular events, biological pathways, and disease processes. As described in this chapter, design strategies for imaging probes are important for accurate imaging to enable effective cancer management both *in vitro* and *in vivo*. Nanomaterial-based imaging probes can obtain

O = 50:50). Strong fluorescence enhancement of the NanoICG was observed

solvent (DMSO:H<sup>2</sup>

**5. Conclusion**

as a probe.

#### **4.2. Optical imaging guided surgery**

The primary goal of cancer surgery is to maximize the tumor excision and minimize the collateral damage. Molecular imaging techniques are required to achieve these goals, leading to "image-guided surgery" [108–117]. Especially, optical imaging is the most suitable for imageguided surgery (or targeted surgery) because fluorescence signals can provide real-time guidance to differentiate positive tumor margins and local malignant masses from normal tissues during surgery, thereby increasing the long-term patient survival. Near-infrared (NIR) imaging has particular potential to remove all neoplastic tissue at the surgical site because it is possible to obtain a low background signal and perform non-invasive real-time monitoring. Image-guided surgery is suitable for tumors that are difficult to differentiate from adjacent normal tissues (such as breast cancers), tumors that are next to complex structures with crucial physiological functions (such as brain tumors), or tumors that have high local recurrence or positive margin rates. Suitable probes for image-guide surgery must specifically detect and target cancerous tissues by showing maximum signal from the target and minimum signal from the background.

A natural fluorophore called protoporphyrin (PpIX) has been clinically used for image-guided surgical resection of brain tumors (glioblastomas), demonstrating that its fluorescence signals

**Figure 10.** (A) Porphyrin-cross-linked hydrogels and noninvasive monitoring and image-guided surgical resection by using them. (i) Structures of mTCPP (green) and PEG diamine (red). (ii) Schematic of the hydrogel. (e), from left to right, (iii) fluorescence images of a mouse with the hydrogel implanted subcutaneously and monitored noninvasively. (iv) Screen captures from a fluorescence camera used to guide fluorescently the surgical removal of the hydrogel in real time. Fluorescence was readily apparent transdermally (T.D.) or through the open incision, as indicated. (B) Hydrophobic moieties conjugated to HLA drive self-assembly into nanoparticles that can entrap ICG. Indocyanine green-loaded nanoparticles for image-guided tumor surgery (i) hydrophobic moieties conjugated to HLA drive self-assembly into nanoparticles that can entrap ICG. (ii) Preoperative imaging and (iii) postoperative imaging of iRFP shows the location of MDA-MB-231 breast tumor xenograft. Red arrows indicated extracted tumors, where iRFP signal showed due to the presence of NanoICG. Reproduced from Refs. [116, 117] with permission of ACS Publications.

are highly specific to tumor cells. Lovell et al. [116] have developed hydrogels using crosslinked porphyrin co-monomers as strong optical tracers (**Figure 10(A)**). In *in vivo* studies, these could be used for the non-invasive fluorescence monitoring of subcutaneously implanted hydrogels over 2 months, without adverse effects or behavior. In addition, it was possible to non-invasively visualize where the gel was located and whether hydrogel degradation or photobleaching occurred. After surgical resection, while no residual fluorescence was detected in the mouse, hydrogel fluorescence was definitely recognized in the removed gel [116]. Hill et al. [117] demonstrated hyaluronic acid (HLA)-derived nanoparticles containing an indocyanine green (ICG) as near-infrared dye (NanoICG) for well delivery to tumors (**Figure 10(B)**). NanoICG exhibited quenched fluorescence and could be activated by disassembly in a mixed solvent (DMSO:H<sup>2</sup> O = 50:50). Strong fluorescence enhancement of the NanoICG was observed in a breast tumor xenograft model. The NanoICG were more completely delivered to tumors compared to free ICG, with strong contrast enhancement in the tumor with a lower background signal in the surrounding tissue, thus demonstrating the potential of the NanoICG as a probe.

#### **5. Conclusion**

absorption imaging and photothermal ablation of epithelial cancer cells with excellent targeting ability. Additionally, Choi et al. demonstrated highly sensitive terahertz (THz) molecular imaging using same probe (CET-PGNR) in both *in vitro* and *in vivo* models, indicating that its high thermal sensitivity can help extend photonic-based photothermal molecular imaging and be used for monitoring drug delivery processes and for early cancer diagnosis [105, 106]. Nam et al. developed "smart" gold nanoparticles that enable aggregation in mild acidic intracellular environments due to their hydrolysis-susceptible citraconic amide surface, which induces a shift in the absorption to longer wavelength, in the far-red and near-infrared (NIR)

**Figure 9.** (A) Schematic illustration of CET-PGNRs as NIR absorption imaging and photothermal therapeutic agents for epithelial cancer. (B) Noninvasive NIR absorption *in vivo* images of tumor tissues for intravenous injected CET-PGNRs or PGNRs (control); white-dotted circles indicate the tumor regions. (C) Silver staining eosin. Tumor region was characterized by extensive pyknosis (green arrows) and cell vacuolization (white arrows) only in mice treated with CET-

The primary goal of cancer surgery is to maximize the tumor excision and minimize the collateral damage. Molecular imaging techniques are required to achieve these goals, leading to "image-guided surgery" [108–117]. Especially, optical imaging is the most suitable for imageguided surgery (or targeted surgery) because fluorescence signals can provide real-time guidance to differentiate positive tumor margins and local malignant masses from normal tissues during surgery, thereby increasing the long-term patient survival. Near-infrared (NIR) imaging has particular potential to remove all neoplastic tissue at the surgical site because it is possible to obtain a low background signal and perform non-invasive real-time monitoring. Image-guided surgery is suitable for tumors that are difficult to differentiate from adjacent normal tissues (such as breast cancers), tumors that are next to complex structures with crucial physiological functions (such as brain tumors), or tumors that have high local recurrence or positive margin rates. Suitable probes for image-guide surgery must specifically detect and target cancerous tissues by showing maximum signal from the target and minimum signal from the background. A natural fluorophore called protoporphyrin (PpIX) has been clinically used for image-guided surgical resection of brain tumors (glioblastomas), demonstrating that its fluorescence signals

regions. This smart feature is useful for photothermal cancer therapy [107].

PGNRs after NIR laser irradiation. Reproduced from Ref. [12] with permission of ACS Publications.

**4.2. Optical imaging guided surgery**

22 State of the Art in Nano-bioimaging

Optical imaging is a powerful tool that can provide the real-time and direct observation of specific molecular events, biological pathways, and disease processes. As described in this chapter, design strategies for imaging probes are important for accurate imaging to enable effective cancer management both *in vitro* and *in vivo*. Nanomaterial-based imaging probes can obtain simultaneous imaging of multiple targets with high sensitivity, multimodal imaging, and imaging-guided therapy (theranostics) in combination with therapeutic agents. In particular, due to the advantages of optical imaging, the surgeon can simultaneously perform surgery while identifying where the cancer is located (imaging-guided surgery). These techniques will greatly contribute in reducing cancer recurrence and developing more effective cures.

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### **Acknowledgements**

This study was supported by the Ministry of Science and ICT (MSIT), Global Frontier Project through the Center for BioNano Health-Guard (H-GUARD\_2014M3A6B2060507) and by the KRIBB Research Initiative Program of the Republic of Korea.

## **Author details**

Jae-Woo Lim1,2, Seong Uk Son1 and Eun-Kyung Lim1,2\*

\*Address all correspondence to: eklim1112@kribb.re.kr

1 Hazards Monitoring BioNano Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea

2 Department of Nanobiotechnology, Korea Research Institute of Bioscience and Biotechnology, School of Biotechnology, Daejeon, Republic of Korea

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This study was supported by the Ministry of Science and ICT (MSIT), Global Frontier Project through the Center for BioNano Health-Guard (H-GUARD\_2014M3A6B2060507) and by the

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**Chapter 3**

**Provisional chapter**

**Carbon Quantum Dots for Bioimaging**

and applications of carbon quantum dots in bioimaging.

optical imaging and green synthesis

**Carbon Quantum Dots for Bioimaging**

DOI: 10.5772/intechopen.72723

Carbon is nature's most abundant and useful element. Carbon nanomaterials with small size and unique optical properties have attracted tremendous interest for their promising biomedical applications. Carbon nanoparticles that exhibit fluorescence property are called as carbon quantum dots and they have emerged as a new class of carbon-based nanomaterials. In this chapter, we look at the unique properties of carbon quantum dots, their synthesis, material as well as optical characterizations, origin of fluorescence nature

**Keywords:** carbon quantum dots, bioimaging, nontoxic fluorogens, fluorescence,

Fluorescent nanodots have drawn much attention in the twenty-first century for a wide range of applications specifically in biomedical field such as bioimaging, biosensing, drug delivery and photodynamic therapy. In the midst of various biomedical fields, bioimaging is one of the most powerful tools for live cell imaging studies via fluorescence microscopy. It endows with the direct visualization of processes occurring in biological species. Copious reports are available for the usage of organic and inorganic nanomaterials as fluorophores toward bio-

In bioimaging studies, it is necessary to use a fluorescent probe to view the image of the cells/ specimen species. Numerous organic fluorophores are commercially available which exhibits high-emission quantum yield (φ). The better one is Rhodamine 6G, which shows the φ value of 80%. But there are few laggings in the usage of organic fluorophores in bioimaging: they are prone to photobleaching and are easy to drip out from the cytoplasm to media, have

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.72723

Mariadoss Asha Jhonsi

Mariadoss Asha Jhonsi

**Abstract**

**1. Introduction**

imaging applications.

#### **Carbon Quantum Dots for Bioimaging Carbon Quantum Dots for Bioimaging**

#### Mariadoss Asha Jhonsi Mariadoss Asha Jhonsi

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.72723

**Abstract**

Carbon is nature's most abundant and useful element. Carbon nanomaterials with small size and unique optical properties have attracted tremendous interest for their promising biomedical applications. Carbon nanoparticles that exhibit fluorescence property are called as carbon quantum dots and they have emerged as a new class of carbon-based nanomaterials. In this chapter, we look at the unique properties of carbon quantum dots, their synthesis, material as well as optical characterizations, origin of fluorescence nature and applications of carbon quantum dots in bioimaging.

DOI: 10.5772/intechopen.72723

**Keywords:** carbon quantum dots, bioimaging, nontoxic fluorogens, fluorescence, optical imaging and green synthesis

#### **1. Introduction**

Fluorescent nanodots have drawn much attention in the twenty-first century for a wide range of applications specifically in biomedical field such as bioimaging, biosensing, drug delivery and photodynamic therapy. In the midst of various biomedical fields, bioimaging is one of the most powerful tools for live cell imaging studies via fluorescence microscopy. It endows with the direct visualization of processes occurring in biological species. Copious reports are available for the usage of organic and inorganic nanomaterials as fluorophores toward bioimaging applications.

In bioimaging studies, it is necessary to use a fluorescent probe to view the image of the cells/ specimen species. Numerous organic fluorophores are commercially available which exhibits high-emission quantum yield (φ). The better one is Rhodamine 6G, which shows the φ value of 80%. But there are few laggings in the usage of organic fluorophores in bioimaging: they are prone to photobleaching and are easy to drip out from the cytoplasm to media, have

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

less photostability (i.e., the fluorophore will undergo degradation while irradiating with light during the imaging process), narrow excitation and emission wavelength (no possibility of tuning the optical properties) and cytotoxicity (during the bioimaging process, organic fluorophore may change the metabolism of live cells), etc.

quantum dots are superior in terms of resistance to photobleaching, chemical inertness, facile surface functionalization, etc. Interestingly, carbon quantum dots are exhibiting low cytotoxicity, high aqueous solubility and are rich in emission quantum yield that entrusts them for the utilization in the field of biomedical research especially in *in vivo* and *in vitro* bioimaging. The discovery of fluorescent carbon nanoparticles was accidental, during the separation and purification of single-walled carbon nanotubes via electrophoresis by Xu in the year of 2004 [1]. After 2 years, Sun and his research group named the small carbon nanoparticles as carbon quantum dots derived from graphite powder using laser ablation technique. In these 12 years, carbon quantum dots have attracted most of the chemists as well as biologists owing to their distinct properties such as abundance in nature, inexpensiveness, facile synthesis, high surface area, flexible functionalization, nontoxicity, photostability, high emission quantum yield, high water soluble nature, etc. This chapter focuses on the synthesis, functionalization, electronic structure, origin of fluorescence property and process involved in the application of carbon quantum dots

During the last 10 years, there were numerous methods reported for the synthesis of carbon quantum dots, which can be broadly classified into two types such as top-down and bottomup approaches. In both the types, one needs to tackle the problems such as aggregation during the carbonization process, homogeneity as well as particle size control and surface properties. In order to overcome these obstacles, there are solutions given like adopting perfect synthetic routes and postsynthetic treatments. Carbon quantum dots can be synthesized from various precursors such as chemical, green and waste materials. In this section, few effective synthetic

This technique is based on the electrochemical carbonization of low-molecular weight organic compounds by applying direct current. Electrochemical workstation instrument can be used for this method. In this process, low-molecular weight organic compounds like alcohols undergo electrochemical carbonization reaction under basic conditions. Three-electrode system contains two Pt sheets as the working and counter electrodes, as well as a calomel electrode mounted on a freely adjustable Luggin capillary acted as the reference electrode; these three electrodes were fixed with a rubber plug, and the distance between the two Pt sheets to be about 3 cm. The precursor solution is prepared by mixing alcohol with water in the ratio 14:1 in a basic medium by adding sodium hydroxide under stirring. The duration of reaction is about 4 h at a suitable potential until the transparent solution turns dark brown in

molecules selected. Once the reaction is completed, equal volume of ethanol is added in the reaction mixture to salt out the NaOH, and the mixture is left overnight. Further evaporation

depending on the precursor

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 37

methods in view of simple, large-scale production and economical were discussed.

color. The current density can be varied from 15 to 100 mA cm<sup>2</sup>

in bioimaging.

**2. Synthesis of carbon quantum dots**

**2.1. Top-down synthetic routes**

*2.1.1. Electrochemical*

Compared to organic fluorophores, metal-based chalcogenide inorganic semiconductor nanocrystals such as quantum dots (QDs) like CdX (X = Se, Te) capped with various long-chain alkyl thiols were extensively used as fluorescent probe during the last decade. The advantages of semiconductor QDs over organic fluorophores are due to their unique property such as quantum confinement effect (i.e., change in particle of QDs leads to changes in optical properties, for example, increase in particle size will shift the absorption in the longer wavelength due to the reduction in bandgap energy), one can vary the optical properties (absorption, emission wavelengths and emission quantum yield) simply by tuning the particle size during the synthesis process or postsynthetic treatments. Moreover, quantum dots show high photostability compared to organic fluorophores since they have the core-shell structure capped with ligands. At the same time, their drawback is in view of biocompatibility, since most of the QDs exist with the presence of toxic heavy metals like Cd, Pb and Hg in their composition. Even though they were enfolded with the surface coverage, within the cell during the imaging analysis, there is a chance of release of those toxic metals into the medium that are harmful to the live cells.

So, in order to conquer the abovementioned problems of unfortunate biodegradability and toxicity, novel fluorescent materials with better optical and biological properties should be developed for bioimaging of live cells. In this context, carbon quantum dots (CQDs), one of the present century invented member of nanocarbon family (**Figure 1**), have emerged as potential candidates for application in such essential field. Compared to the conventional organic fluorophores and recent inorganic semiconductor QDs, the newly emerged carbon

**Figure 1.** Structures of nanocarbon family members (reproduced with permission from [2]).

quantum dots are superior in terms of resistance to photobleaching, chemical inertness, facile surface functionalization, etc. Interestingly, carbon quantum dots are exhibiting low cytotoxicity, high aqueous solubility and are rich in emission quantum yield that entrusts them for the utilization in the field of biomedical research especially in *in vivo* and *in vitro* bioimaging.

The discovery of fluorescent carbon nanoparticles was accidental, during the separation and purification of single-walled carbon nanotubes via electrophoresis by Xu in the year of 2004 [1]. After 2 years, Sun and his research group named the small carbon nanoparticles as carbon quantum dots derived from graphite powder using laser ablation technique. In these 12 years, carbon quantum dots have attracted most of the chemists as well as biologists owing to their distinct properties such as abundance in nature, inexpensiveness, facile synthesis, high surface area, flexible functionalization, nontoxicity, photostability, high emission quantum yield, high water soluble nature, etc. This chapter focuses on the synthesis, functionalization, electronic structure, origin of fluorescence property and process involved in the application of carbon quantum dots in bioimaging.

#### **2. Synthesis of carbon quantum dots**

During the last 10 years, there were numerous methods reported for the synthesis of carbon quantum dots, which can be broadly classified into two types such as top-down and bottomup approaches. In both the types, one needs to tackle the problems such as aggregation during the carbonization process, homogeneity as well as particle size control and surface properties. In order to overcome these obstacles, there are solutions given like adopting perfect synthetic routes and postsynthetic treatments. Carbon quantum dots can be synthesized from various precursors such as chemical, green and waste materials. In this section, few effective synthetic methods in view of simple, large-scale production and economical were discussed.

#### **2.1. Top-down synthetic routes**

#### *2.1.1. Electrochemical*

less photostability (i.e., the fluorophore will undergo degradation while irradiating with light during the imaging process), narrow excitation and emission wavelength (no possibility of tuning the optical properties) and cytotoxicity (during the bioimaging process, organic fluo-

Compared to organic fluorophores, metal-based chalcogenide inorganic semiconductor nanocrystals such as quantum dots (QDs) like CdX (X = Se, Te) capped with various long-chain alkyl thiols were extensively used as fluorescent probe during the last decade. The advantages of semiconductor QDs over organic fluorophores are due to their unique property such as quantum confinement effect (i.e., change in particle of QDs leads to changes in optical properties, for example, increase in particle size will shift the absorption in the longer wavelength due to the reduction in bandgap energy), one can vary the optical properties (absorption, emission wavelengths and emission quantum yield) simply by tuning the particle size during the synthesis process or postsynthetic treatments. Moreover, quantum dots show high photostability compared to organic fluorophores since they have the core-shell structure capped with ligands. At the same time, their drawback is in view of biocompatibility, since most of the QDs exist with the presence of toxic heavy metals like Cd, Pb and Hg in their composition. Even though they were enfolded with the surface coverage, within the cell during the imaging analysis, there is a chance of release of those toxic metals into the medium that are harmful to the live cells.

So, in order to conquer the abovementioned problems of unfortunate biodegradability and toxicity, novel fluorescent materials with better optical and biological properties should be developed for bioimaging of live cells. In this context, carbon quantum dots (CQDs), one of the present century invented member of nanocarbon family (**Figure 1**), have emerged as potential candidates for application in such essential field. Compared to the conventional organic fluorophores and recent inorganic semiconductor QDs, the newly emerged carbon

**Figure 1.** Structures of nanocarbon family members (reproduced with permission from [2]).

rophore may change the metabolism of live cells), etc.

36 State of the Art in Nano-bioimaging

This technique is based on the electrochemical carbonization of low-molecular weight organic compounds by applying direct current. Electrochemical workstation instrument can be used for this method. In this process, low-molecular weight organic compounds like alcohols undergo electrochemical carbonization reaction under basic conditions. Three-electrode system contains two Pt sheets as the working and counter electrodes, as well as a calomel electrode mounted on a freely adjustable Luggin capillary acted as the reference electrode; these three electrodes were fixed with a rubber plug, and the distance between the two Pt sheets to be about 3 cm. The precursor solution is prepared by mixing alcohol with water in the ratio 14:1 in a basic medium by adding sodium hydroxide under stirring. The duration of reaction is about 4 h at a suitable potential until the transparent solution turns dark brown in color. The current density can be varied from 15 to 100 mA cm<sup>2</sup> depending on the precursor molecules selected. Once the reaction is completed, equal volume of ethanol is added in the reaction mixture to salt out the NaOH, and the mixture is left overnight. Further evaporation of solvent, the solid product can be derived that needs separation and purification for the removal of unreacted small molecules by dialysis against water using membrane to obtain the carbon quantum dots. **Figure 2** shows the overview of preparation.

Advantages of this method are as follows: amorphous carbon quantum dots can be obtained by this technique that imparts high fluorescence quantum yield (maximum of 16%). Quantum confinement effect can be achieved by this technique such as size-dependent photoluminescent properties simply by tuning the applied current density. Purification of the product obtained is facile, and easy surface passivation is possible. At the same time, there are few limitations such as this method is economically costlier for large-scale production; surface defects cannot be avoided and production yield will be lower.

#### *2.1.2. Laser irradiation*

In this process, a carbon target in the presence of water vapor with an inert gas as a carrier under high temperature and pressure is irradiated with laser beam. In a typical procedure, carbon precursor is dispersed in some solvent by ultrasonication, and the suspension is dropped into a glass cell for laser irradiation. Generally, Nd:YAG pulsed laser with a second harmonic wavelength of ~530 nm is used to irradiate the suspension. After laser irradiation for different times, the reaction mixture undergoes centrifugation, purification and surface passivation processes to obtain fluorescent carbon quantum dots. **Figure 3** shows the process involved in laser irradiation technique. Advantages of the laser irradiation technique are that it is a fast synthetic route and environmentally friendly approach for the synthesis of carbon quantum dots, but this method is economically not favorable, skilled personal is necessary to conduct the synthesis and postsynthetic process such as surface passivation is necessary to impart fluorescent nature.

and amine molecules play a role of nitrogen dopants and surface-passivating agents in order to improve the emission quantum yields. Initially, different amounts of reaction medium and carbon precursor are mixed with distilled water. Further, the resultant transparent solution is heated in a microwave oven of 500 W for 2–10 min. Within a minute, color changes from colorless to pale yellow, and further, it increases to dark brown indicating the formation of carbon quantum dots. After cooled to room temperature, the product undergoes separation and purification processes to obtain fluorescent carbon quantum dots (**Figure 4**). Advantages of microwave pyrolysis route are as follows: simple, rapid and efficient method for the synthesis of carbon quantum dots [5]. At the same time, there are few limitations: being costly and the presence of harmful microwave radiation, which is to be handled with precautions.

**Figure 4.** Microwave pyrolysis approach for the synthesis of carbon quantum dots (reproduced with permission from [5]).

**Figure 3.** Schematic illustration of experimental setup for the synthesis of carbon quantum dots by laser irradiation

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 39

technique (reproduced with permission from [4]).

#### **2.2. Bottom-up synthetic routes**

#### *2.2.1. Microwave pyrolysis*

This method involves the microwave irradiation of organic compounds in presence of reaction medium. This is a rapid and low-cost method to prepare carbon quantum dots, and in general, sugar moieties were used as a carbon source and polymeric oligomers as reaction media

**Figure 2.** Electrochemical synthesis of C-dots. Under basic conditions (reproduced with permission from [3]).

of solvent, the solid product can be derived that needs separation and purification for the removal of unreacted small molecules by dialysis against water using membrane to obtain the

Advantages of this method are as follows: amorphous carbon quantum dots can be obtained by this technique that imparts high fluorescence quantum yield (maximum of 16%). Quantum confinement effect can be achieved by this technique such as size-dependent photoluminescent properties simply by tuning the applied current density. Purification of the product obtained is facile, and easy surface passivation is possible. At the same time, there are few limitations such as this method is economically costlier for large-scale production; surface

In this process, a carbon target in the presence of water vapor with an inert gas as a carrier under high temperature and pressure is irradiated with laser beam. In a typical procedure, carbon precursor is dispersed in some solvent by ultrasonication, and the suspension is dropped into a glass cell for laser irradiation. Generally, Nd:YAG pulsed laser with a second harmonic wavelength of ~530 nm is used to irradiate the suspension. After laser irradiation for different times, the reaction mixture undergoes centrifugation, purification and surface passivation processes to obtain fluorescent carbon quantum dots. **Figure 3** shows the process involved in laser irradiation technique. Advantages of the laser irradiation technique are that it is a fast synthetic route and environmentally friendly approach for the synthesis of carbon quantum dots, but this method is economically not favorable, skilled personal is necessary to conduct the synthesis and postsynthetic process such as surface passivation is necessary to impart fluorescent nature.

This method involves the microwave irradiation of organic compounds in presence of reaction medium. This is a rapid and low-cost method to prepare carbon quantum dots, and in general, sugar moieties were used as a carbon source and polymeric oligomers as reaction media

**Figure 2.** Electrochemical synthesis of C-dots. Under basic conditions (reproduced with permission from [3]).

carbon quantum dots. **Figure 2** shows the overview of preparation.

defects cannot be avoided and production yield will be lower.

*2.1.2. Laser irradiation*

38 State of the Art in Nano-bioimaging

**2.2. Bottom-up synthetic routes**

*2.2.1. Microwave pyrolysis*

**Figure 3.** Schematic illustration of experimental setup for the synthesis of carbon quantum dots by laser irradiation technique (reproduced with permission from [4]).

and amine molecules play a role of nitrogen dopants and surface-passivating agents in order to improve the emission quantum yields. Initially, different amounts of reaction medium and carbon precursor are mixed with distilled water. Further, the resultant transparent solution is heated in a microwave oven of 500 W for 2–10 min. Within a minute, color changes from colorless to pale yellow, and further, it increases to dark brown indicating the formation of carbon quantum dots. After cooled to room temperature, the product undergoes separation and purification processes to obtain fluorescent carbon quantum dots (**Figure 4**). Advantages of microwave pyrolysis route are as follows: simple, rapid and efficient method for the synthesis of carbon quantum dots [5]. At the same time, there are few limitations: being costly and the presence of harmful microwave radiation, which is to be handled with precautions.

**Figure 4.** Microwave pyrolysis approach for the synthesis of carbon quantum dots (reproduced with permission from [5]).

#### *2.2.2. Oxidative acid treatment*

This treatment includes the refluxion of waste soot in acidic medium followed by centrifugation, neutralization and purification via dialysis against water. Typically, a few gram of waste soot collected by combustion of either natural gas or any other fuel material is mixed with 5 M nitric acid and refluxed for 12 h. After cooled down to room temperature, fluorescent carbon particles were collected by centrifugation. Alternatively, the mixture was first neutralized by Na<sup>2</sup> CO3 , and then extensively dialyzed against double distilled water through dialysis membrane (MWCO 1000). **Figure 5** shows the images of carbon soot and carbon quantum dots derived after the oxidative acid treatment process. Advantages of this acid treatment are effective to introduce functional groups such as carbonyl, carboxyl, amines and epoxy, etc., toward greater water-soluble nature of carbon quantum dots, postsynthetic aggregation can be avoided, and without surface passivation, the prepared carbon quantum dots can be used for imaging applications. A disadvantage of this treatment process is defects may reduce the storage stability of prepared carbon quantum dots.

solvent. By adopting this technique, one can synthesis both hydrophilic and hydrophobic

**Figure 6.** Synthesis of blue emissive carbon quantum dots from gelatin via hydrothermal carbonization process (repro-

Compared with other routes, the hydrothermal carbonization process has some of the advantages such as low toxicological impact of materials and processes, the use of renewable resources, facile instrumentation techniques and high atom economy. This method is costeffective, ecofriendly and nontoxic. Using this technique, large-scale production is possible and reaction conditions such as time and temperature are adjustable. Postsynthetic surface passivation is not necessary. The only limitation of this method is poor control over particle sizes [7].

Carbon quantum dots can be synthesized from wide variety of precursors like both chemical and green resources. **Table** 1 shows the range of precursor materials reported for the synthesis of carbon quantum dots especially for bioimaging application with the value of emission

**(φ)**

14.7 3

oxidation 3 57

SO4 11.1 68

**Reference [8]**

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 41

**Precursor Synthetic method Quantum yield** 

Glucose Hydrothermal treatment at 200°C 1.1–2.4 55

Ascorbic acid Hydrothermal treatment at 140°C 5.7 53 Sugarcane juice Hydrothermal treatment at 120°C 5.76 62 Watermelon peels Carbonization at 220°C 7.1 58

etching

**Table 1.** Carbon quantum dots synthesized by green route for imaging applications [8].

Orange juice Hydrothermal treatment at 120°C 26 60 Gelatin Hydrothermal treatment at 200°C 31.6 67 Chitosan Hydrothermal treatment at 180°C 43 64

fluorescent carbon quantum dots simply by selecting the appropriate precursors.

**2.3. Sources of precursors**

Candle soot HNO<sup>3</sup>

Hair fiber H<sup>2</sup>

Phenol/formaldehyde resin, silica particle Carbonization at 900°C, NaOH

duced with permission from [7]).

quantum yield.

#### *2.2.3. Hydrothermal/solvothermal synthesis*

This is the most popular and facile method for the synthesis of fluorescent carbon quantum dots in which various sources such as chemical as well as green precursor can be used for the synthesis of carbon quantum dots. This technique involves a solution of organic precursor in the presence of either water or some organic solvent sealed in an autoclave (reactor setup which is made up of stainless steel outer and Teflon-coated inner lining to withstand high temperature and pressure, **Figure 6**) and reacted at high temperature (less than the critical temperature of the solvent taken). After complete carbonization, it is autoclaved to allow cooling down to room temperature naturally, and the products can be extracted with an organic

**Figure 5.** Oxidative acid treatment for the synthesis of green fluorescent carbon quantum dots and image of the functionalized carbon quantum dots. (reproduced with permission from [6]).

**Figure 6.** Synthesis of blue emissive carbon quantum dots from gelatin via hydrothermal carbonization process (reproduced with permission from [7]).

solvent. By adopting this technique, one can synthesis both hydrophilic and hydrophobic fluorescent carbon quantum dots simply by selecting the appropriate precursors.

Compared with other routes, the hydrothermal carbonization process has some of the advantages such as low toxicological impact of materials and processes, the use of renewable resources, facile instrumentation techniques and high atom economy. This method is costeffective, ecofriendly and nontoxic. Using this technique, large-scale production is possible and reaction conditions such as time and temperature are adjustable. Postsynthetic surface passivation is not necessary. The only limitation of this method is poor control over particle sizes [7].

#### **2.3. Sources of precursors**

*2.2.2. Oxidative acid treatment*

40 State of the Art in Nano-bioimaging

CO3

storage stability of prepared carbon quantum dots.

*2.2.3. Hydrothermal/solvothermal synthesis*

ized by Na<sup>2</sup>

This treatment includes the refluxion of waste soot in acidic medium followed by centrifugation, neutralization and purification via dialysis against water. Typically, a few gram of waste soot collected by combustion of either natural gas or any other fuel material is mixed with 5 M nitric acid and refluxed for 12 h. After cooled down to room temperature, fluorescent carbon particles were collected by centrifugation. Alternatively, the mixture was first neutral-

membrane (MWCO 1000). **Figure 5** shows the images of carbon soot and carbon quantum dots derived after the oxidative acid treatment process. Advantages of this acid treatment are effective to introduce functional groups such as carbonyl, carboxyl, amines and epoxy, etc., toward greater water-soluble nature of carbon quantum dots, postsynthetic aggregation can be avoided, and without surface passivation, the prepared carbon quantum dots can be used for imaging applications. A disadvantage of this treatment process is defects may reduce the

This is the most popular and facile method for the synthesis of fluorescent carbon quantum dots in which various sources such as chemical as well as green precursor can be used for the synthesis of carbon quantum dots. This technique involves a solution of organic precursor in the presence of either water or some organic solvent sealed in an autoclave (reactor setup which is made up of stainless steel outer and Teflon-coated inner lining to withstand high temperature and pressure, **Figure 6**) and reacted at high temperature (less than the critical temperature of the solvent taken). After complete carbonization, it is autoclaved to allow cooling down to room temperature naturally, and the products can be extracted with an organic

**Figure 5.** Oxidative acid treatment for the synthesis of green fluorescent carbon quantum dots and image of the

functionalized carbon quantum dots. (reproduced with permission from [6]).

, and then extensively dialyzed against double distilled water through dialysis

Carbon quantum dots can be synthesized from wide variety of precursors like both chemical and green resources. **Table** 1 shows the range of precursor materials reported for the synthesis of carbon quantum dots especially for bioimaging application with the value of emission quantum yield.


**Table 1.** Carbon quantum dots synthesized by green route for imaging applications [8].

#### **2.4. Surface functionalization and passivation**

Modification of the surface of carbon quantum dots is necessary for selective application like bioimaging which can be achieved by either surface passivation or functionalization (**Figure 7**). The former one reduces the detrimental effect of surface contamination to their optical properties and to impart high fluorescent intensity. This can be done by formation of a thin insulating layer of coating materials such as oligomers (poly ethylene glycol (PEG)), thionyl chloride, thiols and spiropyrans, etc., on the surface of carbon quantum dots. The process of acid treatment and surface passivation enhances the quantum yield of carbon quantum dots to the maximum of 55–60% which can be attained by the soft shell of passivation agents that surround the hard fluorescent core of the carbon quantum dots. Thus, one can achieve the improved fluorescence emissions.

The later process such as surface functionalization (**Figure 8**) is important due to the introduction of functional groups like, carbonyl, carboxyl and amines which can impose various surface defects on carbon quantum dots. These defects can act as surface energy traps and lead to variations in fluorescence emission behavior of carbon quantum dots. Surface functionalization can be attained by surface chemistry or interactions like coordination, π-π interactions and covalent bonding, etc. Since the carbon quantum dots are oxygenous in nature, they are feasible to covalent bonding with functionalizing agents. Compared to bare carbon quantum dots, the functionalized one are excellent in photoreversibility, high stability, good biocompatibility and low toxicity.

Sometimes, few compounds may use as both passivating and functionalizing agent in which there is no need of additional modification steps during the postsynthetic treatments [11]. High emission quantum yield is essential for carbon quantum dots in order to overcome their counterparts such as organic dye molecules and inorganic semiconductor quantum dots. Other than surface passivation and functionalization, one can use the doping of carbon quantum dots with heteroatoms and nitrogen which can enhance the quantum yield up to 83%.

This section introduces some commonly used sophisticated techniques for the characteriza-

These are highly useful to analyze the surface morphology, particle size, structure and even more composition of carbon quantum dots (**Figure 9**). Few powerful microscopes such as high-resolution scanning electron microscope (HR-SEM), transmission electron microscope (TEM) and atomic force microscope (AFM) are able to resolve the structure of carbon quantum dots up to atomic resolution. The TEM specimen can be prepared by depositing a few drops of a diluted carbon dot solution onto a carbon-coated copper grid, followed by complete evaporation of the water solvent. Diameter of carbon quantum dots can be calculated

D = 2 × r. In this, A is the area of particles occupied, r is the radius of particles and D is the diameter of the particles [12]. The AFM specimen on a mica surface is usually prepared as similar to TEM analysis and both tapping and noncontact modes can be used for the AFM

Diffraction techniques are mostly used for structural determination (amorphous/crystalline) and average particle size analysis (crystallite size). Powder X-ray diffraction (XRD) and small-

Wide range of spectroscopic techniques can be used for the analysis of optical properties of carbon quantum dots. These techniques are useful for chemical state analysis (bonding or

, r = √(A/π) and

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 43

by using Image J software resulting in the area of particles present: A = π r<sup>2</sup>

image measurement. SEM measurement is usually done for powder sample.

angle X-ray scattering (SAXS) are the commonly used techniques.

**3. Characterization techniques**

tion of carbon quantum dots.

**3.2. Diffraction techniques**

**3.3. Spectroscopic techniques**

**3.1. Microscopes**

**Figure 7.** Graphical representation of surface passivation and functionalization of carbon quantum dots (reproduced with permission from [9]).

**Figure 8.** Carbon quantum dots synthesized from citric acid and ascorbic acid functionalized with (a) polyethylene glycol, (b) polyvinylpyrrolidone and (c) bovine serum albumin (reproduced with permission from [10]).

The later process such as surface functionalization (**Figure 8**) is important due to the introduction of functional groups like, carbonyl, carboxyl and amines which can impose various surface defects on carbon quantum dots. These defects can act as surface energy traps and lead to variations in fluorescence emission behavior of carbon quantum dots. Surface functionalization can be attained by surface chemistry or interactions like coordination, π-π interactions and covalent bonding, etc. Since the carbon quantum dots are oxygenous in nature, they are feasible to covalent bonding with functionalizing agents. Compared to bare carbon quantum dots, the functionalized one are excellent in photoreversibility, high stability, good biocompatibility and low toxicity.

Sometimes, few compounds may use as both passivating and functionalizing agent in which there is no need of additional modification steps during the postsynthetic treatments [11]. High emission quantum yield is essential for carbon quantum dots in order to overcome their counterparts such as organic dye molecules and inorganic semiconductor quantum dots. Other than surface passivation and functionalization, one can use the doping of carbon quantum dots with heteroatoms and nitrogen which can enhance the quantum yield up to 83%.

#### **3. Characterization techniques**

This section introduces some commonly used sophisticated techniques for the characterization of carbon quantum dots.

#### **3.1. Microscopes**

**2.4. Surface functionalization and passivation**

42 State of the Art in Nano-bioimaging

with permission from [9]).

Modification of the surface of carbon quantum dots is necessary for selective application like bioimaging which can be achieved by either surface passivation or functionalization (**Figure 7**). The former one reduces the detrimental effect of surface contamination to their optical properties and to impart high fluorescent intensity. This can be done by formation of a thin insulating layer of coating materials such as oligomers (poly ethylene glycol (PEG)), thionyl chloride, thiols and spiropyrans, etc., on the surface of carbon quantum dots. The process of acid treatment and surface passivation enhances the quantum yield of carbon quantum dots to the maximum of 55–60% which can be attained by the soft shell of passivation agents that surround the hard fluorescent core of the carbon quantum dots. Thus, one can achieve the improved fluorescence emissions.

**Figure 7.** Graphical representation of surface passivation and functionalization of carbon quantum dots (reproduced

**Figure 8.** Carbon quantum dots synthesized from citric acid and ascorbic acid functionalized with (a) polyethylene

glycol, (b) polyvinylpyrrolidone and (c) bovine serum albumin (reproduced with permission from [10]).

These are highly useful to analyze the surface morphology, particle size, structure and even more composition of carbon quantum dots (**Figure 9**). Few powerful microscopes such as high-resolution scanning electron microscope (HR-SEM), transmission electron microscope (TEM) and atomic force microscope (AFM) are able to resolve the structure of carbon quantum dots up to atomic resolution. The TEM specimen can be prepared by depositing a few drops of a diluted carbon dot solution onto a carbon-coated copper grid, followed by complete evaporation of the water solvent. Diameter of carbon quantum dots can be calculated by using Image J software resulting in the area of particles present: A = π r<sup>2</sup> , r = √(A/π) and D = 2 × r. In this, A is the area of particles occupied, r is the radius of particles and D is the diameter of the particles [12]. The AFM specimen on a mica surface is usually prepared as similar to TEM analysis and both tapping and noncontact modes can be used for the AFM image measurement. SEM measurement is usually done for powder sample.

#### **3.2. Diffraction techniques**

Diffraction techniques are mostly used for structural determination (amorphous/crystalline) and average particle size analysis (crystallite size). Powder X-ray diffraction (XRD) and smallangle X-ray scattering (SAXS) are the commonly used techniques.

#### **3.3. Spectroscopic techniques**

Wide range of spectroscopic techniques can be used for the analysis of optical properties of carbon quantum dots. These techniques are useful for chemical state analysis (bonding or

**Figure 9.** High-resolution TEM and AFM images of carbon quantum dots (reproduced with permission from [13]).

charge transfer among the atoms) and electronic structure (bandgap energy, level of impurity, band formation and possibilities of electronic transitions, etc.). This includes UV-visible-near IR absorption (both transmission and reflection mode), Fourier transform infrared (FT-IR), atomic absorption spectroscopy (AAS), nuclear magnetic resonance (NMR, both <sup>1</sup> H and 13C NMR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and electron spectroscopy (both spin and resonance, ESR and EPR) (**Figure 10**).

**3.5. Structure of carbon quantum dots**

range of 2–10 nm, they are called GQDs.

carbon nanodots (CNDs).

(X = S, Se, Te).

Fluorescent nanodots can be classified into four types (**Figure 12**) such as semiconductor quantum dots (SQDs), graphene quantum dots (GQDs), carbon quantum dots (CQDs) and

**Figure 10.** (a) XPS survey spectrum, (b) FTIR spectrum, (c) excitation-dependent emission spectra and (d) fluorescence

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 45

decay of carbon dots prepared from tamarind (reproduced with permission from [14]).

SQDs are nanometer scale semiconductor crystals composed of group II metal ions as building blocks, and are defined as particles with physical dimensions smaller than the exciton Bohr radius (~7 nm). The excitons in these particles are confined in the spatial dimensions with quantized energy states. The best examples for SQDs are chalcogenide-based CdX QDs

CNDs are amorphous quasispherical nanodots that lack in quantum confinement, and when the nanodots present as π-conjugated single sheet, i.e., a disk of graphene sheet in the size

CQDs are typically quasispherical nanoparticles comprising amorphous to nanocrystalline cores with predominantly graphitic or turbostratic carbon (sp2 carbon) or graphene and graphene oxide sheets fused by diamond-like sp3 hybridized carbon insertions. CQDs exhibit

Carbon quantum dots typically show two optical absorption band (**Figure 11**) in the UV region with extended tail in the visible range. The two absorption shoulders are attributed to the π-π\* transitions in C=C bonds and n-π\* transition of C=O and other oxygenous carboncontaining functional groups.

#### **3.4. Other techniques**

Other than the abovementioned techniques, few techniques such as elemental analysis, zeta potential analyzer, dynamic light scattering analysis, fluorescence spectroscopy and timecorrelated single photon counting (TCSPC) techniques are useful for the study of percentage of elemental composition, surface charge/dispersivity nature, hydrodynamic particle size (average particle size in solution medium), emission nature (wavelength of emission as well as emission quantum yield) and excited-state lifetime of carbon quantum dots, respectively.

**Figure 10.** (a) XPS survey spectrum, (b) FTIR spectrum, (c) excitation-dependent emission spectra and (d) fluorescence decay of carbon dots prepared from tamarind (reproduced with permission from [14]).

#### **3.5. Structure of carbon quantum dots**

charge transfer among the atoms) and electronic structure (bandgap energy, level of impurity, band formation and possibilities of electronic transitions, etc.). This includes UV-visible-near IR absorption (both transmission and reflection mode), Fourier transform infrared (FT-IR),

**Figure 9.** High-resolution TEM and AFM images of carbon quantum dots (reproduced with permission from [13]).

NMR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and electron spectroscopy (both spin and resonance, ESR and EPR) (**Figure 10**). Carbon quantum dots typically show two optical absorption band (**Figure 11**) in the UV region with extended tail in the visible range. The two absorption shoulders are attributed to the π-π\* transitions in C=C bonds and n-π\* transition of C=O and other oxygenous carbon-

Other than the abovementioned techniques, few techniques such as elemental analysis, zeta potential analyzer, dynamic light scattering analysis, fluorescence spectroscopy and timecorrelated single photon counting (TCSPC) techniques are useful for the study of percentage of elemental composition, surface charge/dispersivity nature, hydrodynamic particle size (average particle size in solution medium), emission nature (wavelength of emission as well as emission quantum yield) and excited-state lifetime of carbon quantum dots, respectively.

H and 13C

atomic absorption spectroscopy (AAS), nuclear magnetic resonance (NMR, both <sup>1</sup>

containing functional groups.

**3.4. Other techniques**

44 State of the Art in Nano-bioimaging

Fluorescent nanodots can be classified into four types (**Figure 12**) such as semiconductor quantum dots (SQDs), graphene quantum dots (GQDs), carbon quantum dots (CQDs) and carbon nanodots (CNDs).

SQDs are nanometer scale semiconductor crystals composed of group II metal ions as building blocks, and are defined as particles with physical dimensions smaller than the exciton Bohr radius (~7 nm). The excitons in these particles are confined in the spatial dimensions with quantized energy states. The best examples for SQDs are chalcogenide-based CdX QDs (X = S, Se, Te).

CNDs are amorphous quasispherical nanodots that lack in quantum confinement, and when the nanodots present as π-conjugated single sheet, i.e., a disk of graphene sheet in the size range of 2–10 nm, they are called GQDs.

CQDs are typically quasispherical nanoparticles comprising amorphous to nanocrystalline cores with predominantly graphitic or turbostratic carbon (sp2 carbon) or graphene and graphene oxide sheets fused by diamond-like sp3 hybridized carbon insertions. CQDs exhibit

**Figure 11.** Absorption, excitation and emission bands of carbon quantum dots (reproduced with permission from [15]).

and strong emission in the visible region [18]. In addition, due to surface passivation/functionalization, the defect becomes more stable to facilitate more effective radiative recombina-

**Figure 13.** (a) Bandgap transitions caused by π-π domains and (b) transition caused by surface defects on carbon

The quantum yield (φ) of carbon dots can be calculated by using quinine sulfate as a reference compound in which φ value is reported as 0.53 [20]. For the measurement of *φ*, the optical density of tamarind carbon dots (TCDs) in water (η = 1.33) was fixed to less than 0.1

the sample and reference, emission spectra were recorded at the same excitation at 360 nm.

S /*I*

where the subscript 'S' refers to the samples, the subscript 'R' refers to quinine sulfate, *A* is the absorbance at the excitation wavelength, *I* is the integrated emission area and *η* is the solvent

Carbon quantum dots with enhanced emission quantum yield are necessary for better imaging of cells. Other than surface passivation, doping and codoping of heteroatoms such as nitrogen and sulfur imparts high quantum efficiency. Recently, it is reported that about 80–83% of quantum yield can be achieved by doping of carbon quantum dots with nitrogen and Mg ion. Doping with metal ions also improves the optical properties in addition with creation of novel functionalities. But one has to concern about the chance of increase in toxicity by doping with metal ion. Compared to metal ion doping, heteroatoms show better advantages due to their

Owing to the close resemblance between nitrogen and carbon, the former one is preferentially used as a dopant for carbon quantum dots. Here, nitrogen can donate its electrons to carbon quantum dots, which change the electronic configuration leading to improvement in quantum yield. Nitrogen can be incorporated with carbon quantum dots either during the synthesis

) for TCDs was calculated by using Eq. (1)

SO4

R) (*η*<sup>S</sup> /*η*R)<sup>2</sup> φR (1)

(*η* = 1.33). For both

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 47

tion of surface-confined electron and hole leads to more bright emissions.

at the wavelength of 360 nm. Quinine sulfate is dissolved in 0.1 M H<sup>2</sup>

*3.6.1. Enhanced fluorescent properties of carbon quantum dots by doping*

Fluorescence quantum yield (*φ*<sup>F</sup>

refraction index.

φ<sup>F</sup> = (*A*R/*A*S) (*I*

quantum dots (reproduced with permission from [18]).

atomic size comparable with carbon quantum dots.

**Figure 12.** Classification of fluorescent nanodots: semiconductor quantum dots (SQDs), graphene quantum dots (GQDs), carbon quantum dots (CQDs) and carbon nanodots (CNDs) (reproduced with permission from [16]).

quantum confinement effect (size-dependent optical properties). Depending on the synthetic route, the oxygen content in the oxidized CQDs ranges from 5 to 50% (weight). Figure shows the difference among the various fluorescent nanodots with their plausible structure.

#### **3.6. Fluorescent properties of carbon quantum dots**

The exact origins of the fluorescence emission nature of carbon quantum dots remain debatable, and lot of research is ongoing to draw a clear picture of the fluorescence mechanism. For the two types of emissions observed for carbon quantum dots such as excitation dependent/ excitation independent, two classes of mechanism have been proposed (**Figure 13**). The first class is bandgap transitions caused by π-domains, and the second class is associated with surface defects on carbon quantum dots [17].

The bandgap electronic transitions display strong absorption in the ultraviolet region, but weak emission and the surface defect-derived origin exhibits weak absorption in the near-UV

#### Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 47

**Figure 13.** (a) Bandgap transitions caused by π-π domains and (b) transition caused by surface defects on carbon quantum dots (reproduced with permission from [18]).

and strong emission in the visible region [18]. In addition, due to surface passivation/functionalization, the defect becomes more stable to facilitate more effective radiative recombination of surface-confined electron and hole leads to more bright emissions.

The quantum yield (φ) of carbon dots can be calculated by using quinine sulfate as a reference compound in which φ value is reported as 0.53 [20]. For the measurement of *φ*, the optical density of tamarind carbon dots (TCDs) in water (η = 1.33) was fixed to less than 0.1 at the wavelength of 360 nm. Quinine sulfate is dissolved in 0.1 M H<sup>2</sup> SO4 (*η* = 1.33). For both the sample and reference, emission spectra were recorded at the same excitation at 360 nm. Fluorescence quantum yield (*φ*<sup>F</sup> ) for TCDs was calculated by using Eq. (1)

$$\phi\_{\rm p} = \left(A\_{\rm k}/A\_{\rm s}\right) \left(I\_{\rm s}/I\_{\rm k}\right) \left(\eta\_{\rm s}/\eta\_{\rm k}\right)^{2} \phi\_{\rm k} \tag{1}$$

where the subscript 'S' refers to the samples, the subscript 'R' refers to quinine sulfate, *A* is the absorbance at the excitation wavelength, *I* is the integrated emission area and *η* is the solvent refraction index.

#### *3.6.1. Enhanced fluorescent properties of carbon quantum dots by doping*

quantum confinement effect (size-dependent optical properties). Depending on the synthetic route, the oxygen content in the oxidized CQDs ranges from 5 to 50% (weight). Figure shows

**Figure 12.** Classification of fluorescent nanodots: semiconductor quantum dots (SQDs), graphene quantum dots (GQDs),

**Figure 11.** Absorption, excitation and emission bands of carbon quantum dots (reproduced with permission from [15]).

The exact origins of the fluorescence emission nature of carbon quantum dots remain debatable, and lot of research is ongoing to draw a clear picture of the fluorescence mechanism. For the two types of emissions observed for carbon quantum dots such as excitation dependent/ excitation independent, two classes of mechanism have been proposed (**Figure 13**). The first class is bandgap transitions caused by π-domains, and the second class is associated with

The bandgap electronic transitions display strong absorption in the ultraviolet region, but weak emission and the surface defect-derived origin exhibits weak absorption in the near-UV

the difference among the various fluorescent nanodots with their plausible structure.

carbon quantum dots (CQDs) and carbon nanodots (CNDs) (reproduced with permission from [16]).

**3.6. Fluorescent properties of carbon quantum dots**

46 State of the Art in Nano-bioimaging

surface defects on carbon quantum dots [17].

Carbon quantum dots with enhanced emission quantum yield are necessary for better imaging of cells. Other than surface passivation, doping and codoping of heteroatoms such as nitrogen and sulfur imparts high quantum efficiency. Recently, it is reported that about 80–83% of quantum yield can be achieved by doping of carbon quantum dots with nitrogen and Mg ion. Doping with metal ions also improves the optical properties in addition with creation of novel functionalities. But one has to concern about the chance of increase in toxicity by doping with metal ion. Compared to metal ion doping, heteroatoms show better advantages due to their atomic size comparable with carbon quantum dots.

Owing to the close resemblance between nitrogen and carbon, the former one is preferentially used as a dopant for carbon quantum dots. Here, nitrogen can donate its electrons to carbon quantum dots, which change the electronic configuration leading to improvement in quantum yield. Nitrogen can be incorporated with carbon quantum dots either during the synthesis via adding nitrogen-containing precursors or postsynthetic functionalization by agents built with nitrogen atom such as amine derivatives. Sulfur, phosphorous and boron atoms have also been as dopants in view of enhancing the fluorescence quantum yield of carbon quantum dots. Codoping of multiple heteroatoms in carbon quantum dots has gained more attention because of the synergistic effect between codoped heteroatoms and carbon quantum dots creating unique electronic structure [19].

cellular toxicity, compared to RPMI, DMEM is more prone to pH changes. So in view of minimizing the pH changes, (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), a

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 49

It is also necessary to maintain a physiological temperature to avoid the cellular detachment or changes in morphology during prolonged exposure of cells. Generally, 37°C is maintained by temperature regulatory system to avoid the rapid evaporation of the medium during prolonged imaging process. Phototoxicity and photobleaching are the two common challenges of live cell imaging. For instance, changes in membrane structure, cell death, vacuolation and blebbing are the possible effect of high-energy light radiation such as laser or ultraviolet light as a light source. This is because when the light radiation interacts with the cells, the rise in temperature due to excitation of light active molecules may stimulate the formation of free radicals (which may attack cellular membrane, lipids, etc.) and laser light may trigger heat stress (oxidative stress). So in order to reduce the oxidative stress and extreme changes in the temperature of medium, it is necessary to use minimum energy/low-intense light radiation source (**Figure 15**). Loss of fluorescent signals during overtime of live cell imaging is called photobleaching. Photosensitivity of fluorescent dyes, the expression level of fluorescent proteins and size of imaging objects are the factors influencing the photobleaching process. Live cell imaging of small fluorescent vesicles is more susceptible to photobleaching compared to the image acqui-

As discussed in the above section, the factors affecting the live cell bioimaging are cell viability, efficiency as well as resolution of confocal microscope and nature of the fluorescent component used. The last one such as a fluorescent contrast agent, which should possess biocompatibility and low biocytotoxicity, is necessary for straightforward fluorescence imaging of live cells and tissues. Depending on the encapsulation/functionalization, carbon quantum dots are either localized in the cell membrane or cytoplasm. Distribution of carbon quantum

It is necessary to check the cytotoxic nature of carbon quantum dots before using it as a fluorescent contrast agent in bioimaging. For that, 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay is generally followed in which the type of interest cells

**Figure 15.** Morphological changes in BHK cells due to phototoxicity such as (A) spindle-shaped membranes, (B) vacuolation and (C) rounding of cells. As shown in (D), the BHK cells displayed normal cell shape before imaging but prolonged exposure to activation laser caused membrane blebbing (indicated by arrow) and cell death (E) (reproduced

dots throughout the cytoplasm is also important for the high resolution of the image.

zwitterionic organic chemical, buffering agent is generally used in imaging studies.

sition of larger fluorescent organelles like nucleus.

with permission from [21]).

**4.2. Role of carbon quantum dots in successful bioimaging**

#### **4. Application of carbon quantum dots: bioimaging**

Live cell bioimaging is becoming an increasingly popular tool for elucidation of biological mechanisms and is instrumental in unraveling the dynamics and functions of many cellular processes. Bioimaging is a method for direct visualization of biological processes in real time which often used to gain information on the 3D structure of the observed specimen from the outside, i.e., without physical interference. Bioimaging spans the observation of subcellular structures using light, fluorescence, electrons, ultrasound, X-ray, magnetic resonance and positrons as sources for imaging. It can be used to follow cellular processes, quantify ion or metabolite levels and measure interactions of molecules live. Appropriate tracers, e.g., specific fluorochromes, and advanced microscopic instruments, e.g., confocal laser scanning microscopes (CLSM, **Figure 14**), are a prerequisite for most applications.

#### **4.1. Basic requirements for successful imaging**

Imaging of biological processes in cells is highly dependent on the conditions provided. In view of avoiding the cellular stress, the environmental conditions should be nearly close to natural cellular ambience. Depending on the type of cell, the medium has to be changed. Generally, Dulbecco's modification of MEM (DMEM) and Roswell Park Memorial Institute (RPMI) are used as medium in which serum is added to provide all the essential nutrients for cell growth. Most of the mammalian cells grow between the pH 7.2–7.4. In bicarbonate-based medium, buffering is made by CO<sup>2</sup> whose withdrawal leads to cell growth. Considering

**Figure 14.** Bioimaging equipment with confocal facility (reproduced with permission from [21]).

cellular toxicity, compared to RPMI, DMEM is more prone to pH changes. So in view of minimizing the pH changes, (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), a zwitterionic organic chemical, buffering agent is generally used in imaging studies.

It is also necessary to maintain a physiological temperature to avoid the cellular detachment or changes in morphology during prolonged exposure of cells. Generally, 37°C is maintained by temperature regulatory system to avoid the rapid evaporation of the medium during prolonged imaging process. Phototoxicity and photobleaching are the two common challenges of live cell imaging. For instance, changes in membrane structure, cell death, vacuolation and blebbing are the possible effect of high-energy light radiation such as laser or ultraviolet light as a light source. This is because when the light radiation interacts with the cells, the rise in temperature due to excitation of light active molecules may stimulate the formation of free radicals (which may attack cellular membrane, lipids, etc.) and laser light may trigger heat stress (oxidative stress). So in order to reduce the oxidative stress and extreme changes in the temperature of medium, it is necessary to use minimum energy/low-intense light radiation source (**Figure 15**).

Loss of fluorescent signals during overtime of live cell imaging is called photobleaching. Photosensitivity of fluorescent dyes, the expression level of fluorescent proteins and size of imaging objects are the factors influencing the photobleaching process. Live cell imaging of small fluorescent vesicles is more susceptible to photobleaching compared to the image acquisition of larger fluorescent organelles like nucleus.

#### **4.2. Role of carbon quantum dots in successful bioimaging**

via adding nitrogen-containing precursors or postsynthetic functionalization by agents built with nitrogen atom such as amine derivatives. Sulfur, phosphorous and boron atoms have also been as dopants in view of enhancing the fluorescence quantum yield of carbon quantum dots. Codoping of multiple heteroatoms in carbon quantum dots has gained more attention because of the synergistic effect between codoped heteroatoms and carbon quantum dots cre-

Live cell bioimaging is becoming an increasingly popular tool for elucidation of biological mechanisms and is instrumental in unraveling the dynamics and functions of many cellular processes. Bioimaging is a method for direct visualization of biological processes in real time which often used to gain information on the 3D structure of the observed specimen from the outside, i.e., without physical interference. Bioimaging spans the observation of subcellular structures using light, fluorescence, electrons, ultrasound, X-ray, magnetic resonance and positrons as sources for imaging. It can be used to follow cellular processes, quantify ion or metabolite levels and measure interactions of molecules live. Appropriate tracers, e.g., specific fluorochromes, and advanced microscopic instruments, e.g., confocal laser scanning

Imaging of biological processes in cells is highly dependent on the conditions provided. In view of avoiding the cellular stress, the environmental conditions should be nearly close to natural cellular ambience. Depending on the type of cell, the medium has to be changed. Generally, Dulbecco's modification of MEM (DMEM) and Roswell Park Memorial Institute (RPMI) are used as medium in which serum is added to provide all the essential nutrients for cell growth. Most of the mammalian cells grow between the pH 7.2–7.4. In bicarbonate-based

whose withdrawal leads to cell growth. Considering

ating unique electronic structure [19].

48 State of the Art in Nano-bioimaging

**4. Application of carbon quantum dots: bioimaging**

microscopes (CLSM, **Figure 14**), are a prerequisite for most applications.

**Figure 14.** Bioimaging equipment with confocal facility (reproduced with permission from [21]).

**4.1. Basic requirements for successful imaging**

medium, buffering is made by CO<sup>2</sup>

As discussed in the above section, the factors affecting the live cell bioimaging are cell viability, efficiency as well as resolution of confocal microscope and nature of the fluorescent component used. The last one such as a fluorescent contrast agent, which should possess biocompatibility and low biocytotoxicity, is necessary for straightforward fluorescence imaging of live cells and tissues. Depending on the encapsulation/functionalization, carbon quantum dots are either localized in the cell membrane or cytoplasm. Distribution of carbon quantum dots throughout the cytoplasm is also important for the high resolution of the image.

It is necessary to check the cytotoxic nature of carbon quantum dots before using it as a fluorescent contrast agent in bioimaging. For that, 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay is generally followed in which the type of interest cells

**Figure 15.** Morphological changes in BHK cells due to phototoxicity such as (A) spindle-shaped membranes, (B) vacuolation and (C) rounding of cells. As shown in (D), the BHK cells displayed normal cell shape before imaging but prolonged exposure to activation laser caused membrane blebbing (indicated by arrow) and cell death (E) (reproduced with permission from [21]).

was harvested and the cell concentration was adjusted to 1 × 104 cells/ml; cells were placed in a 96-well flat-bottom culture plates (180 μl/well) and incubated with various concentrations (0.78, 3.185, 12.5, 25.0, 50.0, 100.0 and 200.0 μl/ml) of carbon quantum dots (in 20 μl). All cultures were incubated for 72 h at 37°C and 5% CO<sup>2</sup> in a humidified incubator. Viable cell concentration was checked by MTT (3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide) assay.

Similarly, for the study of intracellular uptake, the cell line (maintained in Dulbecco's modified Eagle's medium or DMEM supplemented with 10% fetal bovine serum or FBS) was trypsinized and seeded in tissue culture plates at 3 × 104 cells/well. After overnight incubation inside humidified 5% CO<sup>2</sup> incubator for cell attachment, the cells were treated with the carbon quantum dots at a final concentration of 200 μg/ml in 300 μl of media and incubated for 12 h. Prior to the imaging experiment, the cells were washed three times with fresh media.

passivation can be used as a labeling agent if it exhibits high emission quantum yield. The exact mechanism of carbon quantum dots uptake by cells remains to be elucidated, at the same time it is suggested that internalization with significant infiltration in to the cell nucleus. Carbon quantum dots can be used as fluorescent markers to probe various cellular organelles including lysosome/ endosome, golgi body, mitochondria and endoplasmic reticulum (**Figure 16**). For *in vivo*, intravenous injection is used and the organs were harvested and sliced for imaging. Heart, liver, spleen, kidneys, lungs, brain and small intestine can be viewed (**Figure 17**). CQDs can be efficiently and rapidly excreted from the body after injection in different routes. Their blood clearance was quick—only 1 h postintravenous injection. The retention time is somewhat longer after subcutaneous and intramuscular injection. Finally, the imaging process is done under confocal microscope with laser excitation of 405 and 488 nm, and fluorescence was collected in blue and green region.

Carbon Quantum Dots for Bioimaging http://dx.doi.org/10.5772/intechopen.72723 51

**Figure 17.** Fluorescence images of tumor-bearing mice (reproduced with permission from [21]).

Since the discovery of carbon quantum dots in a decade back, they were used as fluorescent contrast agents for imaging of live cells. The defects present in carbon quantum dots play an important role in the fluorescence nature. They can be synthesized by various simple methods using variety of precursors. Unfortunately, the high emission quantum yield of carbon quantum dots still remains rare and is essential to use them in bioimaging application. Moreover, the well-defined composition and structure of carbon quantum dots are not explored well. The origin of fluorescence from carbon quantum dots is also still in debate which follows different mechanisms. Imaging of nucleus of cell using carbon quantum dots is not yet reported, and the sensitivity or selectivity of bioimaging needs to be improved. So, in future, it is necessary to prepare carbon quantum dots which will overcome the abovementioned unexplored properties, and deep research to be done for the use of bioconjugated carbon quantum dots as

theranostics agents for targeted drug delivery and therapeutic applications.

**5. Concluding remarks**

**Author details**

Mariadoss Asha Jhonsi

Address all correspondence to: asha@bsauniv.ac.in

B. S. Abdur Rahman Crescent University, Chennai, India

This internalization of carbon quantum dots by the cells is a temperature-dependent process that happens at the ambient temperature (37°C). In general, carbon quantum dots likely translocate into the cell by endocytosis (i.e., process in which a substance gains entry into a cell without passing through the cell membrane resulting in the formation of an intracellular vesicle by virtue of the invagination of the plasma membrane and membrane fusion). The uptake of carbon quantum dots can be enhanced by coupling of carbon quantum with few membrane translocating peptides, so that it can facilitate the translocation process by overcoming the cell membrane barrier.

The excitation-dependent emission behavior of carbon quantum dots allows one to control and choose the excitation and emission wavelength. Carbon quantum dots with or without surface

**Figure 16.** (a) Cell viability by MTT assay, (b) MG-63 cells under bright field, by excitation at (c) 488 nm and (d) 405 nm (reproduced with permission from [21]).

**Figure 17.** Fluorescence images of tumor-bearing mice (reproduced with permission from [21]).

passivation can be used as a labeling agent if it exhibits high emission quantum yield. The exact mechanism of carbon quantum dots uptake by cells remains to be elucidated, at the same time it is suggested that internalization with significant infiltration in to the cell nucleus. Carbon quantum dots can be used as fluorescent markers to probe various cellular organelles including lysosome/ endosome, golgi body, mitochondria and endoplasmic reticulum (**Figure 16**). For *in vivo*, intravenous injection is used and the organs were harvested and sliced for imaging. Heart, liver, spleen, kidneys, lungs, brain and small intestine can be viewed (**Figure 17**). CQDs can be efficiently and rapidly excreted from the body after injection in different routes. Their blood clearance was quick—only 1 h postintravenous injection. The retention time is somewhat longer after subcutaneous and intramuscular injection. Finally, the imaging process is done under confocal microscope with laser excitation of 405 and 488 nm, and fluorescence was collected in blue and green region.

#### **5. Concluding remarks**

was harvested and the cell concentration was adjusted to 1 × 104 cells/ml; cells were placed in a 96-well flat-bottom culture plates (180 μl/well) and incubated with various concentrations (0.78, 3.185, 12.5, 25.0, 50.0, 100.0 and 200.0 μl/ml) of carbon quantum dots (in 20 μl). All cul-

centration was checked by MTT (3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium

Similarly, for the study of intracellular uptake, the cell line (maintained in Dulbecco's modified Eagle's medium or DMEM supplemented with 10% fetal bovine serum or FBS) was trypsinized and seeded in tissue culture plates at 3 × 104 cells/well. After overnight incubation

quantum dots at a final concentration of 200 μg/ml in 300 μl of media and incubated for 12 h.

This internalization of carbon quantum dots by the cells is a temperature-dependent process that happens at the ambient temperature (37°C). In general, carbon quantum dots likely translocate into the cell by endocytosis (i.e., process in which a substance gains entry into a cell without passing through the cell membrane resulting in the formation of an intracellular vesicle by virtue of the invagination of the plasma membrane and membrane fusion). The uptake of carbon quantum dots can be enhanced by coupling of carbon quantum with few membrane translocating peptides, so that it can facilitate the translocation process by over-

The excitation-dependent emission behavior of carbon quantum dots allows one to control and choose the excitation and emission wavelength. Carbon quantum dots with or without surface

**Figure 16.** (a) Cell viability by MTT assay, (b) MG-63 cells under bright field, by excitation at (c) 488 nm and (d) 405 nm

Prior to the imaging experiment, the cells were washed three times with fresh media.

incubator for cell attachment, the cells were treated with the carbon

in a humidified incubator. Viable cell con-

tures were incubated for 72 h at 37°C and 5% CO<sup>2</sup>

bromide) assay.

inside humidified 5% CO<sup>2</sup>

50 State of the Art in Nano-bioimaging

coming the cell membrane barrier.

(reproduced with permission from [21]).

Since the discovery of carbon quantum dots in a decade back, they were used as fluorescent contrast agents for imaging of live cells. The defects present in carbon quantum dots play an important role in the fluorescence nature. They can be synthesized by various simple methods using variety of precursors. Unfortunately, the high emission quantum yield of carbon quantum dots still remains rare and is essential to use them in bioimaging application. Moreover, the well-defined composition and structure of carbon quantum dots are not explored well. The origin of fluorescence from carbon quantum dots is also still in debate which follows different mechanisms. Imaging of nucleus of cell using carbon quantum dots is not yet reported, and the sensitivity or selectivity of bioimaging needs to be improved. So, in future, it is necessary to prepare carbon quantum dots which will overcome the abovementioned unexplored properties, and deep research to be done for the use of bioconjugated carbon quantum dots as theranostics agents for targeted drug delivery and therapeutic applications.

#### **Author details**

Mariadoss Asha Jhonsi

Address all correspondence to: asha@bsauniv.ac.in

B. S. Abdur Rahman Crescent University, Chennai, India

### **References**

[1] Xu XY, Ray R, Gu YL, Ploehn HJ, Gearheart L, Raker K, Scrivens WA. Electrophoretic analysis and purification of fluorescent single-walled carbon nanotube fragments. Journal of the American Chemical Society. 2014;**126**:12736-12737

[15] Yue X, Chun-Jing T, Hong H, Chao-Qun S, Ya-Kun Z, Qun-Feng Y, Ai-Jun W. Green synthesis of fluorescent carbon quantum dots for detection of Hg2+. Chinese Journal of

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[16] Cayuela A, Soriano ML, Carrillo-Carrión C, Valcárcel M. Semiconductor and carbonbased fluorescent nanodots: The need for consistency. Chemical Communications. 2016;

[17] Cao L, Meziani MJ, Sahu S, Sun Y-P. Photoluminescence properties of graphene versus other carbon nanomaterials. Accounts of Chemical Research. 2013;**46**:171-180

[18] Demchenko P, Dekaliuk MO. Novel fluorescent carbonic nanomaterials for sensing and

[19] Xu Q, Kuang T, Liu Y, Cai L, Peng X, Sreeprasad TS, Zhao P, Yu Z, Li N. Heteroatomdoped carbon dots: Synthesis, characterization, properties, photoluminescence mechanism and biological applications. Journal of Materials Chemistry B. 2016;**4**:7204-7219 [20] Adams MJ, Highfield JG, Kirkbright GF. Determination of absolute fluorescence quantum efficiency of quinine bisulfate in aqueous medium by optoacoustic spectrometry.

[21] Terence TTT, Clement K, Mary MLNg. Microscopy: Science, Technology, Applications

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[1] Xu XY, Ray R, Gu YL, Ploehn HJ, Gearheart L, Raker K, Scrivens WA. Electrophoretic analysis and purification of fluorescent single-walled carbon nanotube fragments.

[2] Demchenko AP, Dekaliuk MO. Novel fluorescent carbonic nanomaterials for sensing

[3] Deng J, Qiujun L, Mi N, Li H, Liu M, Mancai X, Tan L, Xie Q, Zhang Y, Yao S. Electrochemical synthesis of carbon nanodots directly from alcohols. Chemistry—A

[4] Li X, Wang H, Shimizu Y, Pyatenko A, Kawaguchi K, Koshizaki N. Preparation of carbon quantum dots with tunable photoluminescence by rapid laser passivation in ordinary

[5] Zhu H, Wang X, Li Y, Wang Z, Yang F, Yang X. Microwave synthesis of fluorescent carbon nanoparticles with electrochemiluminescence properties. Chemical Communications.

[6] Ray SC, Saha A, Jana NR, Sarkar R. Fluorescent carbon nanoparticle: Synthesis, characterization and bio-imaging application. Journal of Physical Chemistry C. 2009;**113**(43):

[7] Liang Q, Ma W, Shi Y, Li Z, Yang X. Easy synthesis of highly fluorescent carbon quantum dots from gelatin and their luminescent properties and applications. Carbon. 2013;

[8] Lim SY, Shen W, Gao Z. Carbon quantum dots and their applications. Chemical Society

[9] Park Y, Yoo J, Lim B, Kwon W, Rheea S-W. Improving functionality of carbon nanodots: Doping and surface functionalization. Journal of Materials Chemistry A. 2016;**4**:

[10] Milosavljevic V, Moulick A, Kopel P, Adam V, Kizek R. Microwave Preparation of Carbon Quantum Dots with Different Surface Modification. Available from: web2.men-

[11] Dong YQ, Wang RX, Li H, Shao JW, Chi YW, Lin XM, Chen GN. Polyamine-functionalized

[13] Hua X, Yang X, Li G, Zhao C, Liao X. Green synthesis of fluorescent carbon dots for selective detection of tartrazine in food samples. Journal of Agricultural and Food Chemistry.

[14] Jhonsi MA, Thulasi S. A novel fluorescent carbon dots derived from tamarind. Chemical

carbon quantum dots for chemical sensing. Carbon. 2012;**50**:2810-2815

and imaging. Methods and Applications in Fluorescence. 2013;**1**:042001:17

Journal of the American Chemical Society. 2014;**126**:12736-12737

organic solvents. Chemical Communications. 2011;**47**:932-934

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delu.cz/af\_239\_nanotech/J\_Met\_Nano/0314

[12] https://www.youtube.com/watch?v=JQAZ--c9YfI


**Chapter 4**

Provisional chapter

**Bioimaging and Bio-Sensing Techniques for Lung**

Bioimaging and Bio-Sensing Techniques for Lung Cancer

DOI: 10.5772/intechopen.72724

Early cancer detection and suitable treatment improve the 5-year survival rates of lung cancer significantly. Many cancer diagnostic approaches have been investigated, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some drawbacks such as expensive and time-consuming. Electromagnetic tomography (EMT) has been proposed as a promising diagnostic tool for lung cancer detection. In addition, developing label-free and cost-effective biosensors for target tumor markers detection have attracted attentions worldwide. This chapter reviews the recently developed EMT

Keywords: biomedical imaging, biomarker, biosensor, lung cancer, nanoparticles,

Cancer is a major public health problem worldwide and lung cancer is the leading cause of cancer related deaths [1], which has much lower survival rate than other cancers such as breast cancer [2]. Early diagnosis of cancer is critical, which is expected to contribute significantly to

Many medical imaging methods have been intensively investigated for cancer detection, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound. They have some drawbacks, such as, expensive and insufficient sensitivity to detect early-stage cancers. CT is the current gold standard medical imaging tool for diagnosis of lung disease, which able to study some features of biological objects such as lesion size, morphological lesion characterization, and follow-up of lesion growth. However, it

> © The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

and bio-sensing techniques for early-stage lung cancer detection.

**Cancer Detection**

Detection

Abstract

1. Introduction

Lulu Wang and Jinzhang Xu

Lulu Wang and Jinzhang Xu

electromagnetic imaging

improve the 5-year survival rates [3].

http://dx.doi.org/10.5772/intechopen.72724

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

Provisional chapter

#### **Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection** Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

DOI: 10.5772/intechopen.72724

Lulu Wang and Jinzhang Xu

Additional information is available at the end of the chapter Lulu Wang and Jinzhang Xu

http://dx.doi.org/10.5772/intechopen.72724 Additional information is available at the end of the chapter

#### Abstract

Early cancer detection and suitable treatment improve the 5-year survival rates of lung cancer significantly. Many cancer diagnostic approaches have been investigated, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some drawbacks such as expensive and time-consuming. Electromagnetic tomography (EMT) has been proposed as a promising diagnostic tool for lung cancer detection. In addition, developing label-free and cost-effective biosensors for target tumor markers detection have attracted attentions worldwide. This chapter reviews the recently developed EMT and bio-sensing techniques for early-stage lung cancer detection.

Keywords: biomedical imaging, biomarker, biosensor, lung cancer, nanoparticles, electromagnetic imaging

#### 1. Introduction

Cancer is a major public health problem worldwide and lung cancer is the leading cause of cancer related deaths [1], which has much lower survival rate than other cancers such as breast cancer [2]. Early diagnosis of cancer is critical, which is expected to contribute significantly to improve the 5-year survival rates [3].

Many medical imaging methods have been intensively investigated for cancer detection, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound. They have some drawbacks, such as, expensive and insufficient sensitivity to detect early-stage cancers. CT is the current gold standard medical imaging tool for diagnosis of lung disease, which able to study some features of biological objects such as lesion size, morphological lesion characterization, and follow-up of lesion growth. However, it

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.


Table 1. Conventional lung screening methods [9].

produces unsafe radiations which may increase cancer risk [4]. To solve this problem, LDCT with lower radiation has been applied for imaging of lung [5]. However, LDCT is associated with high false positive rate (up to 96.4%) [6], this may increase morbidity from unnecessary surgical treatment and also serious psychological burden to the subjects. 18F-Fluorodeoxyglucose PET/CT has been applied in oncological imaging without achieve reliable results [7, 8]. Table 1 demonstrates the conventional medical imaging methods for lung diseases detection [9].

demonstrates the current available biomarkers for lung cancer detection [15–35]. DNA biomarkers provide useful information on the process of tumor growth but they are insufficient sensitivity to detect early-stage tumors due to low concentrations of cancer markers [36]. Protein biomarkers are the major indicator of lung cancer, which can be classified as predictive and prognostic markers [37]. Predictive protein markers provide information of the particular therapeutic inter-

Gene biomarkers p53, p16, K-ras, microRNAs, miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205, miR-183,

miR-133b, hsa-mir-155, hsa-let-7a-2, TERT, TERF2, POT1, MiR-449c

Annexin II, APOA1, carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 19-9 (CA19-9), cytokeratin fragment 21-1 (CYFRA21-1), CD59 glycoprotein, transthyretin (TTR), GM2 activator protein (GM2AP), haptoglobin-R 2, Ig-free light chain, neuronspecific enolase (NSE), nitrated ceruloplasmin, plasma kallikrein B1, ProGRP, retinol binding protein (RBP), squamous cell carcinoma (SCC), vascular endothelial growth factor (VEGF), TPA, tumor M2-pyruvate kinase, ENO1, Neuroendocrine markers, HER2, TAG-72.3, hnRNP-A2/B1, PCNA,

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

http://dx.doi.org/10.5772/intechopen.72724

57

miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143, miR-145, miR-206,

Carcinoembryonic antigen (CEA) is the most common proteomic biomarker to distinguish malignant and benign tissues. Normally, serum level of CEA is about 2.5–5 ng/mL in healthy subjects [36]. Neuron-specific enolase (NSE) is a useful marker to investigate neuronal differentiation and to visualize the entire nervous and neuroendocrine systems. It exhibits calciumdependent manner to perform its functions and needs magnesium as a cofactor for catalysis and stabilization of the dimer. Serum levels of NSE are related to some diseases such as Alzheimer, Huntington's chorea, neuroblastoma, and small cell lung cancer (SCLC). Compared to CEA, NSE is more sensitive and specific serum marker for SCLC [37]. Serum levels of NSE is higher than 9 ng/mL in patients with lung cancer. The subjects are considered with SCLS if the levels of NSE are higher than 35 ng/mL. The combination of NSE with other markers such as CYFRA 21-1 and CEA offered more effective and reliable detection in univar-

Annexin II and enolase 1 (ENO1) are another common lung cancer biomarkers [38]. Chromogranin A (CgA) is an acidic glycoprotein, which belongs to the granin family of neuroendocrine secretory proteins. The threshold level of CgA is 50 ng/mL in patients with lung cancer. The serum levels of CgA were much higher in SCLC patients than that in the control groups, and there was an association between survival time and serum levels of CgA [39]. SCLC patients observed the best responses, but the percentage of this histological type

Cytokeratin-19 is the smallest human cytokeratin, which has been recommended as a high sensitive and specific marker for lung cancer, particularly in NSCLS. All adenocarcinomas tested have been positive for CYFRA 21-1, which was about 80% of patients with lung cancers [40]. The specificity and sensitivity of CYFRA 21-1 was found higher than the other protein markers such

vention, while prognostic protein markers offer the overall information of the subjects.

CD34, c-erbB2, FHIT, CTNNB1, MUC1, Cyclin D1

2.1. Proteomic biomarkers

Type Biomarker

Table 2. Lung cancer markers.

Proteomic biomarkers

iate and multivariate analysis of lung cancers.

composes of only 20% of all patients with lung cancer.

Recently, electromagnetic tomography (EMT) has been proposed as a promising tool for diagnosis of early-stage diseases such as lung and brain due to its low-cost and high-sensitivity [10].

Biopsy is another common method to distinguish cancerous and benign tissues, but it is expensive and requires trained physicians [11]. Cytokeratin 21-1 (CYFRA21-1) is a sensitive and specific marker for non-small cell lung cancer (NSCLC), especially in squamous cell carcinoma [12]. Biosensors are analytical devices to identify a target sequence by hybridization with complementary probes immobilized on a solid substrate. Biosensors have attracted increased attention due to they have many advantages such as low-cost, easy-to-use and easy to fabricate. Over the past few years, various nanoparticles have been applied to develop biosensors to increase the sensitivity. Other factors affect stability, reproducibility, and sensitivity, including electrode design and probe immobilization. However, biosensor-based approaches are time-consuming and less sensitive for the low marker concentrations at early stages [13]. Therefore, developing a high-sensitivity label-free method for rapid diagnosis of lung diseases is urgently needed.

This paper describes the recent achievements on bio-imaging and bio-sensing approaches for identifying lung cancer. Recent trends in EMT and bio-sensing methods are also reviewed. Several EMT sensor systems, including benefits, limitations, and future research directions are addressed. The rest of this paper is organized as follows: Section 2 describes biomarkers for lung cancer detection; Section 3 reviews biosensor techniques for target lung markers detection; Section 4 presents EMT approaches and measurement systems for imaging of biological tissues; Section 5 presents current trends and future perspectives.

#### 2. Biomarkers for lung cancer detection

Genetic and proteomics-based biomarkers are the two major types of biomarkers, which can be identified in patients through tumor cells, urine, sputum, blood, or other body fluids [14]. Table 2


Table 2. Lung cancer markers.

produces unsafe radiations which may increase cancer risk [4]. To solve this problem, LDCT with lower radiation has been applied for imaging of lung [5]. However, LDCT is associated with high false positive rate (up to 96.4%) [6], this may increase morbidity from unnecessary surgical treatment and also serious psychological burden to the subjects. 18F-Fluorodeoxyglucose PET/CT has been applied in oncological imaging without achieve reliable results [7, 8]. Table 1

Type Advantage Disadvantage Time

CT Reliable Expensive, false negative scans, low sensitivity, radiation risks 5 min

Few seconds

40–60 min

90–240 min

Chest X-ray Reliable Ionizing radiation, low sensitivity and specificity, sensitivity drops with

MRI Reliable Some types of cancers cannot be detected such as ductal and lobular

PET Reliable Expensive, need for radioactive substance and sophisticated instrument, not suitable for subjects with other complications

tissue density increases

carcinoma, expensive

Table 1. Conventional lung screening methods [9].

56 State of the Art in Nano-bioimaging

Recently, electromagnetic tomography (EMT) has been proposed as a promising tool for diagnosis of early-stage diseases such as lung and brain due to its low-cost and high-sensitivity [10].

Biopsy is another common method to distinguish cancerous and benign tissues, but it is expensive and requires trained physicians [11]. Cytokeratin 21-1 (CYFRA21-1) is a sensitive and specific marker for non-small cell lung cancer (NSCLC), especially in squamous cell carcinoma [12]. Biosensors are analytical devices to identify a target sequence by hybridization with complementary probes immobilized on a solid substrate. Biosensors have attracted increased attention due to they have many advantages such as low-cost, easy-to-use and easy to fabricate. Over the past few years, various nanoparticles have been applied to develop biosensors to increase the sensitivity. Other factors affect stability, reproducibility, and sensitivity, including electrode design and probe immobilization. However, biosensor-based approaches are time-consuming and less sensitive for the low marker concentrations at early stages [13]. Therefore, developing a high-sensitivity label-free method for rapid diagnosis of lung diseases is urgently needed.

This paper describes the recent achievements on bio-imaging and bio-sensing approaches for identifying lung cancer. Recent trends in EMT and bio-sensing methods are also reviewed. Several EMT sensor systems, including benefits, limitations, and future research directions are addressed. The rest of this paper is organized as follows: Section 2 describes biomarkers for lung cancer detection; Section 3 reviews biosensor techniques for target lung markers detection; Section 4 presents EMT approaches and measurement systems for imaging of biological

Genetic and proteomics-based biomarkers are the two major types of biomarkers, which can be identified in patients through tumor cells, urine, sputum, blood, or other body fluids [14]. Table 2

tissues; Section 5 presents current trends and future perspectives.

2. Biomarkers for lung cancer detection

demonstrates the conventional medical imaging methods for lung diseases detection [9].

demonstrates the current available biomarkers for lung cancer detection [15–35]. DNA biomarkers provide useful information on the process of tumor growth but they are insufficient sensitivity to detect early-stage tumors due to low concentrations of cancer markers [36]. Protein biomarkers are the major indicator of lung cancer, which can be classified as predictive and prognostic markers [37]. Predictive protein markers provide information of the particular therapeutic intervention, while prognostic protein markers offer the overall information of the subjects.

#### 2.1. Proteomic biomarkers

Carcinoembryonic antigen (CEA) is the most common proteomic biomarker to distinguish malignant and benign tissues. Normally, serum level of CEA is about 2.5–5 ng/mL in healthy subjects [36]. Neuron-specific enolase (NSE) is a useful marker to investigate neuronal differentiation and to visualize the entire nervous and neuroendocrine systems. It exhibits calciumdependent manner to perform its functions and needs magnesium as a cofactor for catalysis and stabilization of the dimer. Serum levels of NSE are related to some diseases such as Alzheimer, Huntington's chorea, neuroblastoma, and small cell lung cancer (SCLC). Compared to CEA, NSE is more sensitive and specific serum marker for SCLC [37]. Serum levels of NSE is higher than 9 ng/mL in patients with lung cancer. The subjects are considered with SCLS if the levels of NSE are higher than 35 ng/mL. The combination of NSE with other markers such as CYFRA 21-1 and CEA offered more effective and reliable detection in univariate and multivariate analysis of lung cancers.

Annexin II and enolase 1 (ENO1) are another common lung cancer biomarkers [38]. Chromogranin A (CgA) is an acidic glycoprotein, which belongs to the granin family of neuroendocrine secretory proteins. The threshold level of CgA is 50 ng/mL in patients with lung cancer. The serum levels of CgA were much higher in SCLC patients than that in the control groups, and there was an association between survival time and serum levels of CgA [39]. SCLC patients observed the best responses, but the percentage of this histological type composes of only 20% of all patients with lung cancer.

Cytokeratin-19 is the smallest human cytokeratin, which has been recommended as a high sensitive and specific marker for lung cancer, particularly in NSCLS. All adenocarcinomas tested have been positive for CYFRA 21-1, which was about 80% of patients with lung cancers [40]. The specificity and sensitivity of CYFRA 21-1 was found higher than the other protein markers such as CEA and squamous cell carcinoma (SCC) to evaluate NSCLS. The combination of CYFRA 21-1 and other proteomic markers could increase the positive results of lung cancers [41].

However, it is difficult to detect lung cancer with the present markers because they are nonspecific indicators. To improve the accurate, many researchers have investigated the protein biomarker panel that consists of CEA, retinol binding protein (RBP), R1-antitrypsin (AAT), and squamous cell carcinoma (SCC) antigen for accurate disease detection [42]. The sensitivity was also improved by the biomarker panel consists of CEA and some specific biomarkers such as ENO1, SCC, NSE, CYFRA21-1 [43].

#### 2.2. Gene biomarkers

The p53 protein is not normally detected in healthy lung tissue. Approximately 50% of NSCLC patients have been reported with p53 mutation, and the spectrum changed between 34% and 82%. p53 expression was observed in about 58% of lung cancer patients [44]. In addition, the poor correlation relationship between bcl-2 and p53 over-expression was observed in lung cancer patients [45].

p16 methylation was detected in lung cancer patients, in particularly, in chromate lung cancers and smokers. p16 methylation was found in approximately 21~51% of NSCLC patients, while p16 loss of heterozygosity was observed in about 54~100% of NSCLC patients [46, 47].

Ras genes are responsible for the cancer-causing activities of the Harvey (H-ras) and Kirsten (K-ras) sarcoma viruses. Ras mutations were discovered in lung cancer patients (20~25%) and patients with specific cancers (up to 90%). Approximately 60% of Ras mutations were confined to codon 12 of K-ras [48]. K-Ras mutation was also discovered in lung cancer patients (up to 78%) and in patients with NSCLS, pleural effusion, sputum, serum, and bronchoalveolar lavage fluid [49]. Some telomere-related genes such as telomerase reverse transcriptase (TERT), telomerase-associated factor 2 (TERF2) and protection of telomeres 1 (POT1) are affected on lung diseases [50, 51]. The telomeres are the territories of repetitive DNA that exist at the end of the chromosomes and are responsible for the protection of the chromosome ends.

Tumor growth is associated with silence and overexpression miRNAs, thus overexpress miRNAs has potential to become a useful clinical diagnostic tool for early lung diseases detection [52]. Seven upregulated (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143 and miR-145) miRNAs have been investigated for lung marker detection [53]. Additionally, serum miR-206 and miR-133b have been considered as potential markers for lung carcinogenesis [51]. High hsa-mir-155 and low hsa-let-7a-2 can detect lung cancer correctly [54]. MiR-449c with the target marker c-Myc has been applied for NSCLS, which could suppress cancer cells growth in vivo [55].

fiber, evanescent wave fiber, and resonant mirror biosensors are the main types of optical biosensors. SPR-based sensors are more attractive for lung cancer markers detection, which can be classified as label-free and real-time affinity reaction detection systems. A highprecision optical system was developed to detect CYFRA21-1 based on magnetic enzymelinked immunoassay [73]. Experimental results demonstrated that the proposed optical system has potential to become a powerful tool for rapid diagnostic of lung cancer marker with several advantages such as compactness, sensitive, and fast. A plasmonic optical fiber immunosensor was also developed by Ribaut et al. to detect cytokeratin [74]. Their research findings offered an important milestone towards the clinical detection of biomarkers in tissues. Quartz is a popular crystal to develop analytic devices such as quartz crystal microbalance (QCM) sensor. QCM-based sensors can detect point mutation in lung cancer patients [75], which measure frequency changes in quartz crystal resonators based on adsorbate recognition,

Biomarker Capture agent Sample Transducer Limit of

Simulated blood sample

COX-2 Polyclona

p53 (wild & total)

ALCAM & hCG

K-ras point mutation

DNA mutations antibody

ds-DNA & antibody

VEGF VEGFreceptor-1 Serum Electrochemical - 10–70 pg/mL [56]

VEGF165 Aptamer Serum Fluorescent - 1.25 pM–1.25 μM [58] LAG3 protein Antibody Plasma SPRi-MALDITOP MS - - [59] TP53 gene DNA SPR and QCM - 0.3–2 μM [60]

CEA Antibody Serum SPR - - [62]

p53 ssDNA - Electrochemiluminescence - - [64]

EGFR Aptamer Serum Optical - - [66] CA 19-9 Antibody - SPR 66.7 U/mL - [67] ALCAM Antibody 10% Serum SPRi 6 ng/mL - [68]

TAGLN2 Antibody 10%Serum SPRi 3 ng/mL [70]

ssDNA Serum SPR 50 nM [71]

PNA - SPR - [72]


p53 antibody p53 antigen Serum Microcantilever biosensor - 20 ng/mL–

antibody 10%Serum SPRi 45–100 ng/

Table 3. The recently developed biosensors for target lung tumor markers detection.

Aptamer - Electrochemical 15 nM - [57]

SPR 1.35 <sup>10</sup><sup>4</sup>

Fluorescence 1.02 <sup>10</sup><sup>4</sup>

detection

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

http://dx.doi.org/10.5772/intechopen.72724

ng/mL

ng/mL

1.06 pM

mL

Linear range Refs.

[61]

59

[63]

[69]

3.64x10<sup>4</sup> – 3.64x102 ng/mL

7.46x10<sup>4</sup> – 7.46x10 ng/mL

20 μg/mL


#### 3. Biosensors for lung cancer biomarker detection

Table 3 shows some recent developed biosensors for detecting lung tumor markers [56–72]. Fluorescence, interferometric, surface plasmon resonance biosensors (SPR), optrode-based


Table 3. The recently developed biosensors for target lung tumor markers detection.

as CEA and squamous cell carcinoma (SCC) to evaluate NSCLS. The combination of CYFRA 21-1

However, it is difficult to detect lung cancer with the present markers because they are nonspecific indicators. To improve the accurate, many researchers have investigated the protein biomarker panel that consists of CEA, retinol binding protein (RBP), R1-antitrypsin (AAT), and squamous cell carcinoma (SCC) antigen for accurate disease detection [42]. The sensitivity was also improved by the biomarker panel consists of CEA and some specific biomarkers such

The p53 protein is not normally detected in healthy lung tissue. Approximately 50% of NSCLC patients have been reported with p53 mutation, and the spectrum changed between 34% and 82%. p53 expression was observed in about 58% of lung cancer patients [44]. In addition, the poor correlation relationship between bcl-2 and p53 over-expression was observed in lung

p16 methylation was detected in lung cancer patients, in particularly, in chromate lung cancers and smokers. p16 methylation was found in approximately 21~51% of NSCLC patients, while

Ras genes are responsible for the cancer-causing activities of the Harvey (H-ras) and Kirsten (K-ras) sarcoma viruses. Ras mutations were discovered in lung cancer patients (20~25%) and patients with specific cancers (up to 90%). Approximately 60% of Ras mutations were confined to codon 12 of K-ras [48]. K-Ras mutation was also discovered in lung cancer patients (up to 78%) and in patients with NSCLS, pleural effusion, sputum, serum, and bronchoalveolar lavage fluid [49]. Some telomere-related genes such as telomerase reverse transcriptase (TERT), telomerase-associated factor 2 (TERF2) and protection of telomeres 1 (POT1) are affected on lung diseases [50, 51]. The telomeres are the territories of repetitive DNA that exist at the end

Tumor growth is associated with silence and overexpression miRNAs, thus overexpress miRNAs has potential to become a useful clinical diagnostic tool for early lung diseases detection [52]. Seven upregulated (miR-21, miR-210, miR-182, miR-31, miR-200b, miR-205 and miR-183) and eight downregulated (miR-126-3p, miR-30a, miR-30d, miR-486-5p, miR-451a, miR-126-5p, miR-143 and miR-145) miRNAs have been investigated for lung marker detection [53]. Additionally, serum miR-206 and miR-133b have been considered as potential markers for lung carcinogenesis [51]. High hsa-mir-155 and low hsa-let-7a-2 can detect lung cancer correctly [54]. MiR-449c with the target marker c-Myc has been applied for NSCLS, which could suppress cancer cells growth in vivo [55].

Table 3 shows some recent developed biosensors for detecting lung tumor markers [56–72]. Fluorescence, interferometric, surface plasmon resonance biosensors (SPR), optrode-based

p16 loss of heterozygosity was observed in about 54~100% of NSCLC patients [46, 47].

of the chromosomes and are responsible for the protection of the chromosome ends.

3. Biosensors for lung cancer biomarker detection

and other proteomic markers could increase the positive results of lung cancers [41].

as ENO1, SCC, NSE, CYFRA21-1 [43].

2.2. Gene biomarkers

58 State of the Art in Nano-bioimaging

cancer patients [45].

fiber, evanescent wave fiber, and resonant mirror biosensors are the main types of optical biosensors. SPR-based sensors are more attractive for lung cancer markers detection, which can be classified as label-free and real-time affinity reaction detection systems. A highprecision optical system was developed to detect CYFRA21-1 based on magnetic enzymelinked immunoassay [73]. Experimental results demonstrated that the proposed optical system has potential to become a powerful tool for rapid diagnostic of lung cancer marker with several advantages such as compactness, sensitive, and fast. A plasmonic optical fiber immunosensor was also developed by Ribaut et al. to detect cytokeratin [74]. Their research findings offered an important milestone towards the clinical detection of biomarkers in tissues.

Quartz is a popular crystal to develop analytic devices such as quartz crystal microbalance (QCM) sensor. QCM-based sensors can detect point mutation in lung cancer patients [75], which measure frequency changes in quartz crystal resonators based on adsorbate recognition, and the mass changes caused by selective binding can be detected by the corresponding changes in crystals. The advantages of piezoelectric sensors include easy-to-use, cost-effective, and sensitive.

Electrochemical biosensors measure the changes of dielectric properties, dimension, shape and charge distribution while antibody–antigen complex occurred on the electrode surface [76]. Electrochemical biosensors offer high sensitivity and specificity for lung tumor markers detection. Electrochemical-based transducers generally consists of semiconductors and screenprinted electrodes for constructing the biosensors, which able to detect molecules such as proteins, antibody, DNA, antigen and heavy metal ions. The recent advances in electrochemical nano-biosensors offer promising for diagnosis of molecules with significant benefits in inexpensive, simplicity, reliability and fast-response, high sensitivity and specificity.

#### 4. Electromagnetic inductance tomography for lung cancer detection

Electromagnetic tomography (EMT) has attracted many attentions worldwide since it offers a promising alternative to existing medical imaging methods, such as CT or MRI. The approach uses non-ionizing radiation in the low GHz region of the EM spectrum. EMT approach is a safe and cost-effective diagnostic tool and provides structural and functional imaging in one device. Various EMT approaches have been applied for biomedical imaging with particular focus on imaging lung, brain, heart, liver tissue and biological tissues [77–90]. Table 4 presents some recently developed EMT systems.

Watson et al. [91] developed an EMT with phase-stable amplifier for biomedical application. The phase-stable amplifiers and the gradiometers configurations need not be mutually exclusive, and it was reported that the highest measurement precision could be achieved by utilizing both approaches. The EMT image quality would be improved by increasing the number of transmitters and receivers, however, such method also increases the cost, complexity and operation time of the EMT system. A rotational EMT system containing a transceiver RF coil was developed for biomedical application. Compared to the conventional systems, the proposed rotational system offered a better field penetration depth towards the center of image.

electromagnetic problem, and the gradient-based approach was used to solve the inverse problem. The reconstructed images of head phantom are displayed in Figure 2. Their research findings demonstrated that EMT approach has the potential to become a useful tool for brain

Figure 1. (a) The EMT system developed by Semenov et al. [92]; (b) a photograph of the EMT experimental setup using a

More recently, Wang et al. [93] proposed a single frequency EMT based approach for small lung tumor detection in human thorax models. As shown in Figure 3, the system made of 16 coils and each of them worked as both transmitter and receiver. The thorax model was located in the middle of the tank and was energized with a magnetic field generated by coils located outside of the tank wall. During data collection, the transmitting coils transmitted EM signals into the thorax, and the receiving coils measured the scattered magnetic fields from the thorax.

Referring to Figure 3, if a point Q is located within the thorax model, the complex visibility

<sup>&</sup>gt; (1)

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

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61

A reconstructed image of the thorax model was obtained using the measured data.

Vi,j ! ¼< H ! scat r ! i � <sup>H</sup> !<sup>∗</sup> scat r ! j

stroke detection in the future.

head phantom for the imaging experiment.

data for any two coils can be obtained as [94]:

Semenov et al. [92] investigated the ability of EMT technology to detect brain stroke within a human head phantom (see Figure 1). The FDTD method was applied to solve the 3D


Table 4. Some recently developed EMT systems.

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection http://dx.doi.org/10.5772/intechopen.72724 61

and the mass changes caused by selective binding can be detected by the corresponding changes in crystals. The advantages of piezoelectric sensors include easy-to-use, cost-effective,

Electrochemical biosensors measure the changes of dielectric properties, dimension, shape and charge distribution while antibody–antigen complex occurred on the electrode surface [76]. Electrochemical biosensors offer high sensitivity and specificity for lung tumor markers detection. Electrochemical-based transducers generally consists of semiconductors and screenprinted electrodes for constructing the biosensors, which able to detect molecules such as proteins, antibody, DNA, antigen and heavy metal ions. The recent advances in electrochemical nano-biosensors offer promising for diagnosis of molecules with significant benefits in

inexpensive, simplicity, reliability and fast-response, high sensitivity and specificity.

4. Electromagnetic inductance tomography for lung cancer detection

Electromagnetic tomography (EMT) has attracted many attentions worldwide since it offers a promising alternative to existing medical imaging methods, such as CT or MRI. The approach uses non-ionizing radiation in the low GHz region of the EM spectrum. EMT approach is a safe and cost-effective diagnostic tool and provides structural and functional imaging in one device. Various EMT approaches have been applied for biomedical imaging with particular focus on imaging lung, brain, heart, liver tissue and biological tissues [77–90]. Table 4 presents

Watson et al. [91] developed an EMT with phase-stable amplifier for biomedical application. The phase-stable amplifiers and the gradiometers configurations need not be mutually exclusive, and it was reported that the highest measurement precision could be achieved by utilizing both approaches. The EMT image quality would be improved by increasing the number of transmitters and receivers, however, such method also increases the cost, complexity and operation time of the EMT system. A rotational EMT system containing a transceiver RF coil was developed for biomedical application. Compared to the conventional systems, the proposed rotational system offered a better field penetration depth towards the center of image. Semenov et al. [92] investigated the ability of EMT technology to detect brain stroke within a human head phantom (see Figure 1). The FDTD method was applied to solve the 3D

Frequency Sampling rate Driving level Phase noise

Bath Medical system 10 MHz 100MS/s 30 mA 4 25 R2 = 0.9996 Cardiff Mk2 system [82, 83] 10 MHz 120MS/s 100mArms 9 119 R2 = 0.9998 Craz Mk2 system [84] 50 kHz~ 1.5 MHz 60M/s Max. 200 mA N/A N/A N/A Glamorgan system [85] 10 MHz N/A N/A N/A 27 N/A Phillips system [81] 10 MHz 192kS/s 50mArms 12.5 102 R2 = 0.9878

(m<sup>o</sup> ) Phase drift (mo )

Linearity

and sensitive.

60 State of the Art in Nano-bioimaging

some recently developed EMT systems.

Table 4. Some recently developed EMT systems.

Figure 1. (a) The EMT system developed by Semenov et al. [92]; (b) a photograph of the EMT experimental setup using a head phantom for the imaging experiment.

electromagnetic problem, and the gradient-based approach was used to solve the inverse problem. The reconstructed images of head phantom are displayed in Figure 2. Their research findings demonstrated that EMT approach has the potential to become a useful tool for brain stroke detection in the future.

More recently, Wang et al. [93] proposed a single frequency EMT based approach for small lung tumor detection in human thorax models. As shown in Figure 3, the system made of 16 coils and each of them worked as both transmitter and receiver. The thorax model was located in the middle of the tank and was energized with a magnetic field generated by coils located outside of the tank wall. During data collection, the transmitting coils transmitted EM signals into the thorax, and the receiving coils measured the scattered magnetic fields from the thorax. A reconstructed image of the thorax model was obtained using the measured data.

Referring to Figure 3, if a point Q is located within the thorax model, the complex visibility data for any two coils can be obtained as [94]:

$$
\overrightarrow{V\_{i,j}} = \vec{H}\_{\text{scat}} \left( \overrightarrow{r}\_i \right) \cdot \overrightarrow{H}\_{\text{scat}}^\* \left( \overrightarrow{r}\_j \right) > \tag{1}
$$

Where r ! <sup>i</sup> and r !

E ! ¼ jω A ! �∇Ω.

Where Js !

1=R<sup>2</sup>

Define the intensity of thorax as:

<sup>j</sup> denote the coil locations, <> means the time average, Table 3 lists all symbols

! <sup>¼</sup> <sup>P</sup><sup>N</sup> <sup>i</sup> Vi,j �!

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

http://dx.doi.org/10.5772/intechopen.72724

, N ≥ 3, i 6¼ j.

63

!0 � � (2)

! � �=λ0, <sup>λ</sup><sup>0</sup> indicates

! � �dV (5)

(4)

(6)

<sup>j</sup>2<sup>π</sup> uij ð Þ <sup>l</sup>þvijm dudv (3)

!� yi

. The finite element approach was applied to

was simulated by:

and abbreviations. The total complex visibility data of N coils is V

4π � �<sup>2</sup>

<sup>~</sup>I lð Þ¼ ; <sup>m</sup>

�

If all coils located at the same height, then a 2D image can be reconstructed:

σð Þþ s jωε0ε<sup>0</sup>

ðð V uð Þ ; <sup>v</sup> <sup>e</sup>

� �

r

!� xi

To study the feasibility of EMT for lung tumor detection, Wang et al. developed a numerical system using MATLAB software. The system made of 16 circular coils. The electric current

compute the voltage and the measured region was divided into triangular meshes. The work-

<sup>0</sup> ∇� A � � !

Eq. (4) can be rewritten from Maxwell's formulas by calculating the total electric field

2 <sup>0</sup>JM !

�! , HT �! ¼ H ! inc þ H ! scat.

h iG r!;r<sup>0</sup>

! � �=λ<sup>0</sup> and vij <sup>¼</sup> yj

!

þ jωσ A !

> þ jωμ0JS ! ∇

<sup>k</sup>0<sup>R</sup> <sup>þ</sup> <sup>3</sup> ð Þ k0R <sup>2</sup>

<sup>0</sup><sup>b</sup> ffi <sup>3</sup> <sup>μ</sup><sup>r</sup> � <sup>1</sup> � �=R<sup>2</sup>

2

� �, <sup>a</sup> and <sup>b</sup> are proportional to

.

� 2 HT �! s !� � � <sup>H</sup><sup>∗</sup> T �! s

I s!� � <sup>¼</sup> <sup>j</sup>ωμ<sup>0</sup>

Where l ¼ sinθcosϕ and m ¼ sinθsinϕ, uij ¼ xj

density generated from transmitter was 1A/m<sup>2</sup>

!� � <sup>¼</sup> �<sup>j</sup>

! , JM �!

H ! scat r<sup>0</sup> !� � <sup>¼</sup> <sup>k</sup>

<sup>k</sup>0<sup>R</sup> <sup>1</sup> � <sup>j</sup>

2

k0R

4πωμ<sup>0</sup>

ing frequency was 2 MHz. The excitation current density Js

Js !

The scattered field measured by any receiver can be modeled as [95]:

ð

Js ! � ∇ � � � <sup>∇</sup> <sup>þ</sup> <sup>k</sup>

<sup>¼</sup> <sup>j</sup>ωμ<sup>0</sup> <sup>μ</sup><sup>r</sup> � <sup>1</sup> � � HT

V

The following formula can be applied to compute the magnetic field:

2 0 4π ð

V

� �, <sup>b</sup> <sup>¼</sup> <sup>μ</sup><sup>r</sup> � <sup>1</sup> � � �<sup>1</sup> <sup>þ</sup> <sup>3</sup><sup>j</sup>

<sup>0</sup><sup>a</sup> ffi � <sup>μ</sup><sup>r</sup> � <sup>1</sup> � �=R<sup>2</sup> and <sup>k</sup>

a H ! þb H! �br � �b<sup>r</sup> � i<sup>G</sup> <sup>b</sup>r;r<sup>0</sup> ! � �dV <sup>h</sup>

<sup>¼</sup> <sup>∇</sup> � <sup>μ</sup>�<sup>1</sup>

the wavelength of free space (see Figure 3).

H ! scat r<sup>0</sup>

Where <sup>a</sup> <sup>¼</sup> <sup>μ</sup>rε<sup>r</sup> � <sup>j</sup> <sup>μ</sup>ð Þ <sup>r</sup>�<sup>1</sup>

(i.e. k0R ≪ 1). Hence k

¼ jωε0ð Þ ε<sup>r</sup> � 1 E

Figure 2. 3D reconstruction of the human head phantom featuring a h-stroke model. Three slices of the real part of the 3D ε-distribution, (a) axial slice; (b) coronal slice; (c) sagittal slice [92].

Figure 3. (a) The proposed EMT system by Wang et al. [93]; (b) a setup for any pair of coils.

Where r ! <sup>i</sup> and r ! <sup>j</sup> denote the coil locations, <> means the time average, Table 3 lists all symbols and abbreviations. The total complex visibility data of N coils is V ! <sup>¼</sup> <sup>P</sup><sup>N</sup> <sup>i</sup> Vi,j �! , N ≥ 3, i 6¼ j. Define the intensity of thorax as:

$$I\left(\stackrel{\rightarrow}{s}\right) = \left(\frac{j\omega\mu\_0}{4\pi}\right)^2 \left|\sigma(\mathbf{s}) + j\omega\varepsilon\_0 \varepsilon\_r'\right|^2 \overrightarrow{H\_T}\left(\stackrel{\rightarrow}{s}\right) \cdot \overrightarrow{H\_T}^\*\left(\stackrel{\rightarrow}{s}'\right) \tag{2}$$

If all coils located at the same height, then a 2D image can be reconstructed:

Figure 2. 3D reconstruction of the human head phantom featuring a h-stroke model. Three slices of the real part of the 3D

ε-distribution, (a) axial slice; (b) coronal slice; (c) sagittal slice [92].

62 State of the Art in Nano-bioimaging

Figure 3. (a) The proposed EMT system by Wang et al. [93]; (b) a setup for any pair of coils.

$$\tilde{I}(l,m) = \iint V(\mu,\upsilon)e^{j2\pi\left(u\_{\vec{\eta}}l+\upsilon\_{\vec{\eta}}m\right)}dud\upsilon\tag{3}$$

Where l ¼ sinθcosϕ and m ¼ sinθsinϕ, uij ¼ xj !� xi ! � �=λ<sup>0</sup> and vij <sup>¼</sup> yj !� yi ! � �=λ0, <sup>λ</sup><sup>0</sup> indicates the wavelength of free space (see Figure 3).

To study the feasibility of EMT for lung tumor detection, Wang et al. developed a numerical system using MATLAB software. The system made of 16 circular coils. The electric current density generated from transmitter was 1A/m<sup>2</sup> . The finite element approach was applied to compute the voltage and the measured region was divided into triangular meshes. The working frequency was 2 MHz. The excitation current density Js ! was simulated by:

$$
\overrightarrow{J\_s} = \nabla \times \left(\mu\_0^{-1} \nabla \times \overrightarrow{A}\right) + j\omega\sigma \,\overrightarrow{A} \tag{4}
$$

Eq. (4) can be rewritten from Maxwell's formulas by calculating the total electric field E ! ¼ jω A ! �∇Ω.

The scattered field measured by any receiver can be modeled as [95]:

$$\overrightarrow{H}\_{\text{scat}}\left(\overrightarrow{r\_0}\right) = \frac{-j}{4\pi\omega\mu\_0} \int\_V \left[ \left(\overrightarrow{J\_s} \cdot \nabla\right) \times \nabla + k\_0^2 \overrightarrow{J\_M} + j\omega\mu\_0 \overrightarrow{J\_S} \cdot \nabla \right] G\left(\overrightarrow{r}, \overrightarrow{r\_0}\right) dV\tag{5}$$

Where Js ! ¼ jωε0ð Þ ε<sup>r</sup> � 1 E ! , JM �! <sup>¼</sup> <sup>j</sup>ωμ<sup>0</sup> <sup>μ</sup><sup>r</sup> � <sup>1</sup> � � HT �! , HT �! ¼ H ! inc þ H ! scat.

The following formula can be applied to compute the magnetic field:

$$\overrightarrow{H}\_{\text{scat}}\left(\overrightarrow{r\_0}\right) = \frac{k\_0^2}{4\pi} \int\_V \left[ \left( a \, \overrightarrow{H} + b \left( \overrightarrow{H} \, \cdot \widehat{\underline{r}} \right) \widehat{\underline{r}} \right) G \left( \widehat{r}, \overrightarrow{r\_0} \right) dV \right. \tag{6}$$

Where <sup>a</sup> <sup>¼</sup> <sup>μ</sup>rε<sup>r</sup> � <sup>j</sup> <sup>μ</sup>ð Þ <sup>r</sup>�<sup>1</sup> <sup>k</sup>0<sup>R</sup> <sup>1</sup> � <sup>j</sup> k0R � �, <sup>b</sup> <sup>¼</sup> <sup>μ</sup><sup>r</sup> � <sup>1</sup> � � �<sup>1</sup> <sup>þ</sup> <sup>3</sup><sup>j</sup> <sup>k</sup>0<sup>R</sup> <sup>þ</sup> <sup>3</sup> ð Þ k0R <sup>2</sup> � �, <sup>a</sup> and <sup>b</sup> are proportional to 1=R<sup>2</sup> (i.e. k0R ≪ 1). Hence k 2 <sup>0</sup><sup>a</sup> ffi � <sup>μ</sup><sup>r</sup> � <sup>1</sup> � �=R<sup>2</sup> and <sup>k</sup> 2 <sup>0</sup><sup>b</sup> ffi <sup>3</sup> <sup>μ</sup><sup>r</sup> � <sup>1</sup> � �=R<sup>2</sup> .

Figure 4. Simulation result of lung phantom obtained by Wang et al. [93].

Born Approximation was applied to solve the forward problem, thus Eq. (6) changes to [90]:

$$\overrightarrow{H}\_{\text{scat}}\left(\overrightarrow{r\_0}\right) = \frac{1}{4\pi} \int\_V \frac{\mu\_r - 1}{R^2} \left[ -\overrightarrow{H} + \Im\left(\overrightarrow{H} \cdot \hat{\underline{r}}\right) \hat{\underline{r}} \right] G\left(\overrightarrow{r}, \overrightarrow{r\_0}\right) dV\tag{7}$$

algorithm and hardware implementation system with particular focus on the development of

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

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65

Developing biosensors with implementation of biomarkers have attracted many attentions from researchers worldwide in the past few years. Up to date, cancer markers are still in discovery stage and the current evidences are too restricted for early lung cancer detection. Proteomic biomarkers have been applied within a panel of protein biomarkers but they are not recommended to be used as individual biomarkers for lung cancer detection. Applying individual marker does not helpful for clinicians to obtain enough information of cancer tissue such as the stage of cancer, treatment and state of subject. The major problem of biosensor-based techniques is related to integration of lung cancer detection in primary healthcare. QCM-based biosensors are more suitable and reliable for clinical surgery compared to other biosensors. The limitations of biosensors include small target size, marker levels, the possibility of high non-specific binding in the case of serum or real patient samples. Recent research trends of nano-biosensor techniques for diagnosis of molecules offer great potential for early lung cancer detection, however, these techniques are not mature for clinical trials. Future investigations should be address directly to

low-cost and compact RF coils and coil arrays to produce high quality images.

improve the selectivity, sensitivity, accuracy, and multiplexing capacity of biosensors.

The author gratefully acknowledges the financial supports from the National Natural Science Foundation of China (Grant No. 61701159), the Natural Science Foundation of Anhui Province (Grant No. 101413246), the Foundation for Oversea Master Project from Ministry of Education of the People's Republic of China (Grant No. 2160311028), and the start-up funding from the

1 School of Instrument Science and Opto-electronics Engineering, Hefei University of

2 Institute of Biomedical Technologies, Auckland University of Technology, Auckland,

3 School of Electrical Engineering and Automation, Hefei University of Technology, Hefei,

[1] World Health Organization. Cancer fact sheet 2017. Available at: http://www.who.int/

Acknowledgements

Author details

Lulu Wang1,2\* and Jinzhang Xu3

Technology, Hefei, China

New Zealand

References

China

Hefei University of Technology (Grant No. 407037164).

\*Address all correspondence to: luluwang2015@hfut.edu.cn

mediacentre/factsheets/fs297/en/ [Accessed 22.09.2017.]

Simulation result (see Figure 4) showed that various arbitrary shaped lung tumors with random sizes and locations could be identified in the thorax images. The proposed EMT approach offered crucial priority information that can be exploited to improve the capabilities of diagnostics methods. The advantages of the proposed method include simplified imaging processing due to the image quantity is proportional to the dielectric properties contrast.

#### 5. Current trends and future perspectives

The current available lung screening approaches are effective but have some limitations as detailed above. EMT-based approaches have the potential to become an additional or alternative method to CT for lung disease detection. However, these techniques have some drawbacks, such as heavy computational imaging algorithm, difficult hardware systems for clinical applications, and limited spatial resolution. To solve these challenges, many researchers focused on developing a high dynamic hardware implementation system. Additionally, many investigators used more coils to improve the image quality. However, such method increases the mutual coupling signals between coils, which may reduce the detection accuracy. Moreover, the cost and complexities of the hardware implementation system also increased with increasing the number of coils. To solve this problem, a single coil could be applied to replace the multi-coil array. Recent research findings suggested that optimization of coil array configurations offer some potential benefits in high image resolution, low-cost, and operating time. The multipleinput-multiple-output technique may also help to reduce the complexity of the hardware system. In the future, more investigations of EMT technique should be taken to improve the image algorithm and hardware implementation system with particular focus on the development of low-cost and compact RF coils and coil arrays to produce high quality images.

Developing biosensors with implementation of biomarkers have attracted many attentions from researchers worldwide in the past few years. Up to date, cancer markers are still in discovery stage and the current evidences are too restricted for early lung cancer detection. Proteomic biomarkers have been applied within a panel of protein biomarkers but they are not recommended to be used as individual biomarkers for lung cancer detection. Applying individual marker does not helpful for clinicians to obtain enough information of cancer tissue such as the stage of cancer, treatment and state of subject. The major problem of biosensor-based techniques is related to integration of lung cancer detection in primary healthcare. QCM-based biosensors are more suitable and reliable for clinical surgery compared to other biosensors. The limitations of biosensors include small target size, marker levels, the possibility of high non-specific binding in the case of serum or real patient samples. Recent research trends of nano-biosensor techniques for diagnosis of molecules offer great potential for early lung cancer detection, however, these techniques are not mature for clinical trials. Future investigations should be address directly to improve the selectivity, sensitivity, accuracy, and multiplexing capacity of biosensors.

#### Acknowledgements

Born Approximation was applied to solve the forward problem, thus Eq. (6) changes to [90]:

Simulation result (see Figure 4) showed that various arbitrary shaped lung tumors with random sizes and locations could be identified in the thorax images. The proposed EMT approach offered crucial priority information that can be exploited to improve the capabilities of diagnostics methods. The advantages of the proposed method include simplified imaging processing due to the image quantity is proportional to the dielectric properties contrast.

The current available lung screening approaches are effective but have some limitations as detailed above. EMT-based approaches have the potential to become an additional or alternative method to CT for lung disease detection. However, these techniques have some drawbacks, such as heavy computational imaging algorithm, difficult hardware systems for clinical applications, and limited spatial resolution. To solve these challenges, many researchers focused on developing a high dynamic hardware implementation system. Additionally, many investigators used more coils to improve the image quality. However, such method increases the mutual coupling signals between coils, which may reduce the detection accuracy. Moreover, the cost and complexities of the hardware implementation system also increased with increasing the number of coils. To solve this problem, a single coil could be applied to replace the multi-coil array. Recent research findings suggested that optimization of coil array configurations offer some potential benefits in high image resolution, low-cost, and operating time. The multipleinput-multiple-output technique may also help to reduce the complexity of the hardware system. In the future, more investigations of EMT technique should be taken to improve the image

þ3 H ! �br � � br

G r!;r<sup>0</sup> !ÞdV

(7)

�

h i

H ! scat r<sup>0</sup> !� �

64 State of the Art in Nano-bioimaging

5. Current trends and future perspectives

¼ 1 4π ð

Figure 4. Simulation result of lung phantom obtained by Wang et al. [93].

V

μ<sup>r</sup> � 1 <sup>R</sup><sup>2</sup> � <sup>H</sup> !

The author gratefully acknowledges the financial supports from the National Natural Science Foundation of China (Grant No. 61701159), the Natural Science Foundation of Anhui Province (Grant No. 101413246), the Foundation for Oversea Master Project from Ministry of Education of the People's Republic of China (Grant No. 2160311028), and the start-up funding from the Hefei University of Technology (Grant No. 407037164).

## Author details

Lulu Wang1,2\* and Jinzhang Xu3

\*Address all correspondence to: luluwang2015@hfut.edu.cn

1 School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Hefei, China

2 Institute of Biomedical Technologies, Auckland University of Technology, Auckland, New Zealand

3 School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China

#### References

[1] World Health Organization. Cancer fact sheet 2017. Available at: http://www.who.int/ mediacentre/factsheets/fs297/en/ [Accessed 22.09.2017.]

[2] Reed MF, Molloy M, Dalton EL, Howington JA. Survival after resection for lung cancer is the outcome that matters. American Journal of Surgery. 2004;188(5):598-602

Journal of Thoracic Oncology Official Publication of the International Association for the

Bioimaging and Bio-Sensing Techniques for Lung Cancer Detection

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67

[17] Dong Y, Zheng X, Yang Z, Sun M, Zhang G, An X, et al. Serum carcinoembryonic antigen, neuron-specific enolase as biomarkers for diagnosis of nonsmall cell lung cancer.

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**Chapter 5**

**Provisional chapter**

**Research Status and Prospect for CT Imaging**

**Research Status and Prospect for CT Imaging**

DOI: 10.5772/intechopen.73032

Computed tomography (CT) is a very valuable imaging method and plays an important role in clinical diagnosis. As people pay more and more attention to radiation doses these years, decreasing CT radiation dose without affecting image quality is a hot direction for research of medical imaging in recent years. This chapter introduces the research status of low-dose technology from following aspects: low-dose scan implementation, reconstruction methods and image processing methods. Furthermore, other technologies related to the development tendency of CT, such as automatic tube current modulation technology, rapid peak kilovoltage (kVp) switching technology, dual-source CT technology and Nano-CT, are also summarized. Finally, the future research prospect are dis-

**Keywords:** low-dose CT, spectral CT, dual-source CT, nano-CT, image reconstruction,

Computed tomography (CT), also referred to as computerized axial tomography (CAT), is a noninvasive and high-tech medical examination that uses X-ray to produce cross-sectional images of the body. With these cross-sectional images, doctors can visualize anatomical structures and tissues inside the body, like small nodules or tumors, which they cannot see with a plain film X-ray. This does not violate the outer surface of the body, in other words, non-invasively. Since the first practical CT instrument developed in the 1970s by Godfrey N. Hounsfield (he received the Nobel Prize in 1979), X-ray CT technology has developed dramatically and become a standard imaging procedure for virtually all parts of the body in thousands of facilities throughout the world. Nowadays, CT scanners are used for a variety of reasons, for example, diagnostic and treatment planning, therapeutic and interventional

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.73032

**Abstract**

cussed and analyzed.

image enhancement

**1. Introduction**

purposes.

Yi Liu

Yi Liu


**Provisional chapter**

## **Research Status and Prospect for CT Imaging**

**Research Status and Prospect for CT Imaging**

DOI: 10.5772/intechopen.73032

#### Yi Liu Yi Liu Additional information is available at the end of the chapter

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2010;224:1-4

2008;29:S431

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.73032

#### **Abstract**

Computed tomography (CT) is a very valuable imaging method and plays an important role in clinical diagnosis. As people pay more and more attention to radiation doses these years, decreasing CT radiation dose without affecting image quality is a hot direction for research of medical imaging in recent years. This chapter introduces the research status of low-dose technology from following aspects: low-dose scan implementation, reconstruction methods and image processing methods. Furthermore, other technologies related to the development tendency of CT, such as automatic tube current modulation technology, rapid peak kilovoltage (kVp) switching technology, dual-source CT technology and Nano-CT, are also summarized. Finally, the future research prospect are discussed and analyzed.

**Keywords:** low-dose CT, spectral CT, dual-source CT, nano-CT, image reconstruction, image enhancement

#### **1. Introduction**

Computed tomography (CT), also referred to as computerized axial tomography (CAT), is a noninvasive and high-tech medical examination that uses X-ray to produce cross-sectional images of the body. With these cross-sectional images, doctors can visualize anatomical structures and tissues inside the body, like small nodules or tumors, which they cannot see with a plain film X-ray. This does not violate the outer surface of the body, in other words, non-invasively. Since the first practical CT instrument developed in the 1970s by Godfrey N. Hounsfield (he received the Nobel Prize in 1979), X-ray CT technology has developed dramatically and become a standard imaging procedure for virtually all parts of the body in thousands of facilities throughout the world. Nowadays, CT scanners are used for a variety of reasons, for example, diagnostic and treatment planning, therapeutic and interventional purposes.

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

Generally, X-ray CT go through six generations [1]. The first generation, with parallel-beam geometry, only has single X-ray source and single X-ray detector cell to collect all the data for a single slice. The projection data were acquired in approximately 5 minutes, and the tomographic image was reconstructed in approximately 20 minutes. The second generation scanner uses fan-beam geometry and has multiple detectors, thus multiple projections obtained during each traversal past the patient with the acquisition time for one tomogram 1 minute. Both the first and second generation CT works in a translate/rotate model. In the third generation CT, a fan beam of X-rays is used and a curved detector array consisting of several hundred independent detectors is mechanically coupled to the X-ray source, and both rotate in synchrony, that is, rotate/rotate mode. The fourth generation CT also uses fan-beam geometry but with ring of stationary detections array. Only the X-ray tube revolves around the patient, namely, rotate/stationary mode. For third and fourth generation scanners, acquisition times are similar, less than 10 seconds for one tomogram. In the fifth-generation CT, the detector array remains stationary, while a high-energy electron beams is electronically swept along a semicircular tungsten strip anode. Its scanning time is about 50 ms, which is fast enough to image the beating heart without significant motion artifacts. The sixth generation CT is emerged due to the requirement for faster scan times, and in particular, for fast multiple scans for three-dimensional imaging. Both third and fourth generation fan-beam geometries achieve this using self-lubricating slip-ring technology to make the electrical connections with rotating components. It can produce one continuous volume set of data for entire region.

topics of several speakers are related to dose protection. The International Commission on Radiation Protection (ICRP) also recommended that radiation doses should all be kept as low as reasonably achievable (ALARA). This means that radiation dose should be as little as possible on the premise that CT images can meet clinical requirement. "Low-dose" has emerged

Research Status and Prospect for CT Imaging http://dx.doi.org/10.5772/intechopen.73032 75

Low-dose CT was first proposed by Naidich in 1990 and applied to the lung [5]. Their experiments showed that high-quality lung images could be obtained with less radiation doses. But, due to limitations of hardware and software, the image quality are not completely meet the requirements of clinical diagnosis at that moment. Fortunately, the developments of science and technology laid solid foundations for all kinds of low-dose CT technology, and more and more radiologists and researchers have applied themselves to low-dose CT imaging, for example, CT lung screening [6] and CT cardiac screening [7]. In addition, low-dose scan for children has received more attention [8]. On one hand, CT radiation dose reduction is partly dependent on the hardware optimization. On the other hand, it is related to personalized scan parameters, including the number of scans, the tube current and scanning time in milliampere-seconds (mAs), the tube voltage in the kilovolt peaks (kVp), the size of the patient, the axial scan range, the scan pitch (the degree of overlap

For any CT scan, the most direct factors that affect the radiation dose are X-ray intensity and exposure time. The clinically common way to achieve the low-dose scan is to lower milliampere-seconds (mAs) or peak kilovoltage (kVp) setting in the scanning protocol, to reduce the intensity of X-ray. **Figure 1** shows a CT phantom reconstruction at standard dose, while lowering the mAs leads to a lower signal-to-noise ratio (SNR) and the decrease of density resolution due to the introduction of noise and streak artifacts [9], such as in **Figure 2**. Thus, it is difficult to distinguish similar density regions. Lowering the kVp causes a worse penetration, greatly reducing SNR. For example, if the tube voltage drops from 120 to 80 kVp, the tube current must be increased by four times to maintain the same SNR [10]. The differences between the two approaches therefore make them used in different applications, for instance, the way of

between adjacent CT slices) and the specific design of the scanner being used.

**Figure 1.** CT phantom reconstruction at standard dose (120 kV, 240 mAs).

as one of the important direction of CT development.

From the first generation to the sixth generation, CT pursues higher speed, spatial resolution and density resolution. At present, these three aspects are still goals of CT manufacturers, but beyond that low-dose scanning is the fourth aspect that CT manufacturers pay real attention to, and become the development direction of CT technology. Overall, the trend of X-ray CT now is mainly in low-dose CT, ultra-low-dose CT and spectral CT, to obtain clear positioning and qualitative diagnosis using the least X-ray radiation.

#### **2. Low-dose CT**

The application requirements for CT have almost covered all clinical departments, and have been commonly used in medical institutions. However, by the nature of CT scanning, larger radiation doses are involved compared to conventional X-ray imaging procedures, which may lead to adverse health effects. Many literatures show that X-ray radiation will increase radiation-induced cancer risks in adults and particularly in children. The research published in "New England Journal of Medicine" in 2007 shows that 1.5–2% of the tumors may be due to CT radiation. For example, when the effective dose is 10 mSv in an adult abdominal examination, the risk of cancer will increase 1/2000 [2]. And, more remarkable, children are particularly vulnerable to radiation dose damage [3, 4]. There is a growing concern on the significance of minimizing the radiation dose delivered to patients during X-ray CT. It is worth noting that the relative noise in CT images will increase as the radiation dose is decreased. And a tradeoff should be found between radiation dose and imaging quality. At international conferences on radiology in recent years, such as the radiological society of north American (RSNA), the topics of several speakers are related to dose protection. The International Commission on Radiation Protection (ICRP) also recommended that radiation doses should all be kept as low as reasonably achievable (ALARA). This means that radiation dose should be as little as possible on the premise that CT images can meet clinical requirement. "Low-dose" has emerged as one of the important direction of CT development.

Generally, X-ray CT go through six generations [1]. The first generation, with parallel-beam geometry, only has single X-ray source and single X-ray detector cell to collect all the data for a single slice. The projection data were acquired in approximately 5 minutes, and the tomographic image was reconstructed in approximately 20 minutes. The second generation scanner uses fan-beam geometry and has multiple detectors, thus multiple projections obtained during each traversal past the patient with the acquisition time for one tomogram 1 minute. Both the first and second generation CT works in a translate/rotate model. In the third generation CT, a fan beam of X-rays is used and a curved detector array consisting of several hundred independent detectors is mechanically coupled to the X-ray source, and both rotate in synchrony, that is, rotate/rotate mode. The fourth generation CT also uses fan-beam geometry but with ring of stationary detections array. Only the X-ray tube revolves around the patient, namely, rotate/stationary mode. For third and fourth generation scanners, acquisition times are similar, less than 10 seconds for one tomogram. In the fifth-generation CT, the detector array remains stationary, while a high-energy electron beams is electronically swept along a semicircular tungsten strip anode. Its scanning time is about 50 ms, which is fast enough to image the beating heart without significant motion artifacts. The sixth generation CT is emerged due to the requirement for faster scan times, and in particular, for fast multiple scans for three-dimensional imaging. Both third and fourth generation fan-beam geometries achieve this using self-lubricating slip-ring technology to make the electrical connections with rotating components. It can produce one continuous volume set of data for entire region.

From the first generation to the sixth generation, CT pursues higher speed, spatial resolution and density resolution. At present, these three aspects are still goals of CT manufacturers, but beyond that low-dose scanning is the fourth aspect that CT manufacturers pay real attention to, and become the development direction of CT technology. Overall, the trend of X-ray CT now is mainly in low-dose CT, ultra-low-dose CT and spectral CT, to obtain clear positioning

The application requirements for CT have almost covered all clinical departments, and have been commonly used in medical institutions. However, by the nature of CT scanning, larger radiation doses are involved compared to conventional X-ray imaging procedures, which may lead to adverse health effects. Many literatures show that X-ray radiation will increase radiation-induced cancer risks in adults and particularly in children. The research published in "New England Journal of Medicine" in 2007 shows that 1.5–2% of the tumors may be due to CT radiation. For example, when the effective dose is 10 mSv in an adult abdominal examination, the risk of cancer will increase 1/2000 [2]. And, more remarkable, children are particularly vulnerable to radiation dose damage [3, 4]. There is a growing concern on the significance of minimizing the radiation dose delivered to patients during X-ray CT. It is worth noting that the relative noise in CT images will increase as the radiation dose is decreased. And a tradeoff should be found between radiation dose and imaging quality. At international conferences on radiology in recent years, such as the radiological society of north American (RSNA), the

and qualitative diagnosis using the least X-ray radiation.

**2. Low-dose CT**

74 State of the Art in Nano-bioimaging

Low-dose CT was first proposed by Naidich in 1990 and applied to the lung [5]. Their experiments showed that high-quality lung images could be obtained with less radiation doses. But, due to limitations of hardware and software, the image quality are not completely meet the requirements of clinical diagnosis at that moment. Fortunately, the developments of science and technology laid solid foundations for all kinds of low-dose CT technology, and more and more radiologists and researchers have applied themselves to low-dose CT imaging, for example, CT lung screening [6] and CT cardiac screening [7]. In addition, low-dose scan for children has received more attention [8]. On one hand, CT radiation dose reduction is partly dependent on the hardware optimization. On the other hand, it is related to personalized scan parameters, including the number of scans, the tube current and scanning time in milliampere-seconds (mAs), the tube voltage in the kilovolt peaks (kVp), the size of the patient, the axial scan range, the scan pitch (the degree of overlap between adjacent CT slices) and the specific design of the scanner being used.

For any CT scan, the most direct factors that affect the radiation dose are X-ray intensity and exposure time. The clinically common way to achieve the low-dose scan is to lower milliampere-seconds (mAs) or peak kilovoltage (kVp) setting in the scanning protocol, to reduce the intensity of X-ray. **Figure 1** shows a CT phantom reconstruction at standard dose, while lowering the mAs leads to a lower signal-to-noise ratio (SNR) and the decrease of density resolution due to the introduction of noise and streak artifacts [9], such as in **Figure 2**. Thus, it is difficult to distinguish similar density regions. Lowering the kVp causes a worse penetration, greatly reducing SNR. For example, if the tube voltage drops from 120 to 80 kVp, the tube current must be increased by four times to maintain the same SNR [10]. The differences between the two approaches therefore make them used in different applications, for instance, the way of

**Figure 1.** CT phantom reconstruction at standard dose (120 kV, 240 mAs).

analyzed the large sample of projection data and considered that noise in the low-dose CT sinogram after logarithm transform and calibration could be modeled as a signal-dependent variable and the sample variance depended on the sample mean by an exponential relationship [16]. Then Wang proposed several penalized weighted least-squares (PWLS) approaches on the noisy sinogram based on this model to adaptively remove non-stationary noise [17–19]. Ma designed a generalized Gibbs prior that exploited nonlocal information of the projection data and used the FBP method to finish the final CT reconstruction [20]. To obtain a more accurate model, Zhang studied the property of the projection data and found an important character that isolated noise points may exist in some areas of the sinogram [21]. Soon he proposed a noise reduction scheme which includes isolated data removal and segmentationbased filtering [22]. Denoising techniques based on wavelet transformation are also applied to projection restorations. Sahiner and Yagle showed how to restore noisy projections in wavelet domain (using wavelet transformation) [23]. Wang proposed wavelet coefficient local adaptive (WCLA) for the noisy sinogram and their method was proved to be effective in removing noise while maintaining the diagnostic image details [24]. Mahmood proposed a graph-based sinogram denoising method, which makes the sinogram as an ideal candidate for graph-based denoising since it generally has a piecewise smooth structure [25]. In addition, many sophisticated denoising techniques are used and improved for projection space denoising, for exam-

Research Status and Prospect for CT Imaging http://dx.doi.org/10.5772/intechopen.73032 77

ple, bilateral filtering [26–28], nonlocal means filtering [29, 30] and fuzzy filter [31, 32].

edge in projection data is not definite, resulting in sharpness loss in image domain.

**2.2. Iterative reconstruction**

In this category, filtering process and reconstruction process are independent of each other, thus it is well facilitated for system integration. Furthermore, the calculation amount is usually far less than iterative reconstruction and advantages on computing speed is obvious. Projection denoising takes noise properties in projections into account, this makes filters restore the projection data effectively, yet has the potential disadvantage that the definition of

With rapid advances in computing power and the reduction in costs for that power, all the major CT vendors now offer iterative reconstruction (IR). It benefits from Shepp and Vardi who introduced maximum likelihood expectation maximization (MLEM) into the field of reconstruction [33]. Nowadays iterative reconstruction algorithm has been a hot issue in the field of CT reconstruction with one important reason that IR enables diagnostic image clarity on low-dose scans [34–36]. An IR algorithm first establishes a statistical model of Gaussian or Poisson distribution based on the physical model of the imaging system and statistical characteristics of projection data. Then, the corresponding energy equation is solved in the image space by an iterative algorithm. The reconstructed image quality is better than that reconstructed by the traditional analytic method. Another important algorithm, maximum a posterior (MAP) [37, 38], is very popular and frequently used in IR. MAP is based on Bayesian theory, and introduces the prior information of image space as a penalty term, thus can effectively suppress noise and keep the edge. MAP improves the quality of reconstruction obviously and is far superior to analytical reconstruction algorithms on scattering noise and artifacts elimination, so it is very suitable for low-dose CT reconstruction. How to design an efficient prior is the key point of MAP and has been one of the research hotspots of iterative reconstruction algorithm. The traditional iterative

**Figure 2.** CT phantom reconstruction at low dose (120 kV, 30 mAs).

lowering tube current is often used for lesions with high contrast, such as calcifications, while the way of lowering tube voltage is often used for iodine-based contrast imaging [11].

In order to remove noise and artifacts mentioned above, researchers studied a lot of reconstruction algorithms based on the existing CT equipment, hoping to improve the image quality by designing the appropriate algorithm under the limited hardware conditions. Based on this, many techniques have been proposed to remove noise and artifacts in low-dose CT [12]. They are generally categorized into three major types such as projection restorations, iterative reconstruction (IR) and post-processing methods.

#### **2.1. Projection restorations**

Since the advent of the CT system, the analytic reconstruction algorithm, represented by filtered back projection (FBP), is the mainstream algorithm for two-dimensional CT system and the Feldkamp-Davis-Kress (FDK) algorithm is still the first selection of three-dimensional CT system. This is because the analytic algorithms are simple, thus fast and easy to realize. However, in a low-dose scanning, the projections are contaminated with excessive quantum noise, while the analytic algorithms lack effective ability for noise suppression; this makes the reconstructed images from a low-dose scan that are severely degraded with noise and artifacts. In order to solve this problem, some researchers treat the projection data as an image (called sinogram) and suppress excessive quantum noise in it by kinds of methods, making the projection data close to that at standard dose. Thus, reconstructions with suppressed noise and artifacts can be reconstructed from the denoised projections by analytical reconstruction methods. To cope with the excessive quantum noise in projection data, researchers have proposed different techniques to restore noise-corrupted projections. Hsieh modeled the noise in projection data and proposed an adaptive filtering to achieve streak artifact reduction in CT reconstruction [13]. In the study of Elbakri, the detected photon numbers are considered to follow a Poisson distribution plus a background Gaussian noise with zero mean, and then a penalized Poisson likelihood maximization algorithm was then proposed [14, 15]. Li statistically analyzed the large sample of projection data and considered that noise in the low-dose CT sinogram after logarithm transform and calibration could be modeled as a signal-dependent variable and the sample variance depended on the sample mean by an exponential relationship [16]. Then Wang proposed several penalized weighted least-squares (PWLS) approaches on the noisy sinogram based on this model to adaptively remove non-stationary noise [17–19]. Ma designed a generalized Gibbs prior that exploited nonlocal information of the projection data and used the FBP method to finish the final CT reconstruction [20]. To obtain a more accurate model, Zhang studied the property of the projection data and found an important character that isolated noise points may exist in some areas of the sinogram [21]. Soon he proposed a noise reduction scheme which includes isolated data removal and segmentationbased filtering [22]. Denoising techniques based on wavelet transformation are also applied to projection restorations. Sahiner and Yagle showed how to restore noisy projections in wavelet domain (using wavelet transformation) [23]. Wang proposed wavelet coefficient local adaptive (WCLA) for the noisy sinogram and their method was proved to be effective in removing noise while maintaining the diagnostic image details [24]. Mahmood proposed a graph-based sinogram denoising method, which makes the sinogram as an ideal candidate for graph-based denoising since it generally has a piecewise smooth structure [25]. In addition, many sophisticated denoising techniques are used and improved for projection space denoising, for example, bilateral filtering [26–28], nonlocal means filtering [29, 30] and fuzzy filter [31, 32].

In this category, filtering process and reconstruction process are independent of each other, thus it is well facilitated for system integration. Furthermore, the calculation amount is usually far less than iterative reconstruction and advantages on computing speed is obvious. Projection denoising takes noise properties in projections into account, this makes filters restore the projection data effectively, yet has the potential disadvantage that the definition of edge in projection data is not definite, resulting in sharpness loss in image domain.

#### **2.2. Iterative reconstruction**

lowering tube current is often used for lesions with high contrast, such as calcifications, while

In order to remove noise and artifacts mentioned above, researchers studied a lot of reconstruction algorithms based on the existing CT equipment, hoping to improve the image quality by designing the appropriate algorithm under the limited hardware conditions. Based on this, many techniques have been proposed to remove noise and artifacts in low-dose CT [12]. They are generally categorized into three major types such as projection restorations, iterative

Since the advent of the CT system, the analytic reconstruction algorithm, represented by filtered back projection (FBP), is the mainstream algorithm for two-dimensional CT system and the Feldkamp-Davis-Kress (FDK) algorithm is still the first selection of three-dimensional CT system. This is because the analytic algorithms are simple, thus fast and easy to realize. However, in a low-dose scanning, the projections are contaminated with excessive quantum noise, while the analytic algorithms lack effective ability for noise suppression; this makes the reconstructed images from a low-dose scan that are severely degraded with noise and artifacts. In order to solve this problem, some researchers treat the projection data as an image (called sinogram) and suppress excessive quantum noise in it by kinds of methods, making the projection data close to that at standard dose. Thus, reconstructions with suppressed noise and artifacts can be reconstructed from the denoised projections by analytical reconstruction methods. To cope with the excessive quantum noise in projection data, researchers have proposed different techniques to restore noise-corrupted projections. Hsieh modeled the noise in projection data and proposed an adaptive filtering to achieve streak artifact reduction in CT reconstruction [13]. In the study of Elbakri, the detected photon numbers are considered to follow a Poisson distribution plus a background Gaussian noise with zero mean, and then a penalized Poisson likelihood maximization algorithm was then proposed [14, 15]. Li statistically

the way of lowering tube voltage is often used for iodine-based contrast imaging [11].

reconstruction (IR) and post-processing methods.

**Figure 2.** CT phantom reconstruction at low dose (120 kV, 30 mAs).

**2.1. Projection restorations**

76 State of the Art in Nano-bioimaging

With rapid advances in computing power and the reduction in costs for that power, all the major CT vendors now offer iterative reconstruction (IR). It benefits from Shepp and Vardi who introduced maximum likelihood expectation maximization (MLEM) into the field of reconstruction [33]. Nowadays iterative reconstruction algorithm has been a hot issue in the field of CT reconstruction with one important reason that IR enables diagnostic image clarity on low-dose scans [34–36]. An IR algorithm first establishes a statistical model of Gaussian or Poisson distribution based on the physical model of the imaging system and statistical characteristics of projection data. Then, the corresponding energy equation is solved in the image space by an iterative algorithm. The reconstructed image quality is better than that reconstructed by the traditional analytic method. Another important algorithm, maximum a posterior (MAP) [37, 38], is very popular and frequently used in IR. MAP is based on Bayesian theory, and introduces the prior information of image space as a penalty term, thus can effectively suppress noise and keep the edge. MAP improves the quality of reconstruction obviously and is far superior to analytical reconstruction algorithms on scattering noise and artifacts elimination, so it is very suitable for low-dose CT reconstruction. How to design an efficient prior is the key point of MAP and has been one of the research hotspots of iterative reconstruction algorithm. The traditional iterative reconstruction algorithm usually uses the neighborhood correlation of image space to construct a Markov field prior model [39, 40]. In this model, noise suppression is greatly affected by the noise level of projection data, and the constraint ability is declined when the projection data is seriously noisy. While some prior constructed by non-convex potential function may introduce additional staircase artifacts [41]. Bian proposed a total variation minimization lowdose CT reconstruction method based on a divergence constraint, which eliminates the block artifacts of the traditional total variation priors [42]. Chen considered the excellent denoising capability of nonlocal algorithm and proposed an adaptive-weighting nonlocal prior statistical reconstruction approach [43]. The proposed prior imposes an effective resolution-preserving and noise-removing regularization for reconstructions, and specially has a good recovery ability for region of gradated density. Zhang explored an adaptive Markov random field (MRF) based penalty term which utilizes previous normal-dose scan to obtain the MRF coefficients and incorporated it into the PWLS image reconstruction framework [44]. Li proposed a hybrid nonlocal means regularization model for iterative reconstruction of low-dose CT perfusion to overcome the limitation of the conventional prior-image-induced penalty [45].

image contrast and blur the image edge. Furthermore, since such filters are usually defined in small scale regions, it is impossible to suppress high-frequency noise in projection data, typically with almost no effect on metal artifacts. Wavelet-based method to a certain extent can remedy the defects of small scale spatial filtering, and effectively preserve the texture information while suppressing high-frequency noise [54, 55]. Zhong presented wavelet coefficient magnitude sum (WCMS) and experiments showed that 60% of the noise could be removed [56]. Borsdorf proposed a correlation-based wavelet method for noise reduction in low-dose CT images [57]. Large-scale nonlocal mean filter is another commonly used post-processing algorithm, which carry out the nonlinear filtering correction in the current position by searching the matching information according to the self-similarity of the tissues under various doses in a large scale. This method has good performance in noise elimination and edge preservation. Chen proposed a large-scale nonlocal means (LNLM) filter to improve abdomen lowdose CT images by exploiting large-scale structure similarity knowledge, which was further combined with a multiscale directional diffusion scheme to reduce the streak artifacts in thoracic CT images [58]. Ma proposed a new nonlocal mean algorithm by combining nonlocal mean and the results obtained from previous normal-dose scans to deal with low-dose CT, and the image artifacts are solved in a certain extent by means of image guidance techniques [59]. In [60], feature knowledge in available CT database is incorporated into weight update in LNLM strategy, and a notable image quality enhancement was reported. Dictionary learning and sparse representation were also used for reconstruction and enhancement for low-dose X-ray imaging [61–64]. The dictionary technique studies from normal-dose CT images (feature extraction) guide the low-dose CT image processing. Dictionary technology combines the advantages of large-scale nonlocal filtering and image guidance technology, and has very good extendibility. However, they have the limitation of computation time. Recently, the deep learning technology is popular and shows great potential in image denoising. Chen trained a deep convolutional neural network (CNN) to transform low-dose CT images toward normaldose CT images, patch by patch and visual and quantitative evaluation demonstrates a competing performance of the proposed method [65]. Wu proposed a cascaded training network for low-dose CT image denoising, where the trained CNN was applied on the training dataset to initiate new trainings and remove artifacts [66]. Wolterink proposed to train a CNN jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise [67]. Kang applied a CNN to wavelet coefficients of low-dose CT images and showed that wavelet domain CNN was efficient in removing the noises from low-dose CT

Research Status and Prospect for CT Imaging http://dx.doi.org/10.5772/intechopen.73032 79

In addition to X-ray intensity, to shorten scanning time can also reduce the radiation dose dramatically, which can be achieved by reducing projection angles (sparse angles or incomplete angles) in acquisition process. Due to the projection, data of CT systems usually have high redundancy, under the condition of less sampling angles, the missing data can be repaired to get a complete projection data set, and the reconstruction quality can be improved using the repaired data. In the decade, dictionary learning and TV (total variance) constraint are two effective techniques to estimate the missing projection data [70–76]. Recently, the convolutional neural network was also performed in sparse-view reconstruction (down to 50 views)

compared to an image domain CNN [68, 69].

on parallel-beam X-ray CT [77].

However, IR techniques such as algebraic reconstruction technique (ART) always have high computation loads (e.g., up to several hours per data set), which have prevented fast clinical applications. It is urgent to improve the reconstruction speed and researchers have proposed a variety of methods to speed up the convergence rate of IR algorithms, for example, orderedsubsets image reconstructions [46–48]. However, the practical application of IR is still limited by hardware level. Fortunately, the development of parallel computing technology has played an important role in the application of IR. The computation time of IR can be greatly reduced by using the graphics processing units (GPUs) [49–51]. It is worth noting that IR techniques require access to the raw projection data (projection restoration also has this problem) and are highly dependent on special scanner model, that is, requiring more detailed information such as scanning geometry, photon statistics, data-acquisition, correction physics, thus highly dependent on specific scanner models. Its limitation appeals a more broadly used denoising method that can perform on different systems, and leads us to think more about denoising after reconstruction.

#### **2.3. Post-processing method**

Image post-processing techniques, working on the image space alone, are retrospectively applied and relatively simple to implement without access to the raw projection data. Since post-processing methods directly enhance the existing CT images, they do not need to improve or replace the existing equipment, thus easy to be used and promoted. The main difficulty comes from the non-stationary mottle noise and streak-like artifacts, which often distribute over the whole CT image. These mottle noise and streak artifacts are caused by the back-projection process within the FBP algorithms, and are difficult to remove because they do not obey to specific distribution models. Various sophisticated techniques, considering the strong structural and statistical properties of objects in image space, have been proposed for improving the quality of low-dose CT images. In [52, 53], the low-dose CT reconstruction images are filtered by nonlinear or anisotropic filters, which can smooth the image effectively meanwhile preserve edges to some extent. But this kind of algorithms is easy to reduce the image contrast and blur the image edge. Furthermore, since such filters are usually defined in small scale regions, it is impossible to suppress high-frequency noise in projection data, typically with almost no effect on metal artifacts. Wavelet-based method to a certain extent can remedy the defects of small scale spatial filtering, and effectively preserve the texture information while suppressing high-frequency noise [54, 55]. Zhong presented wavelet coefficient magnitude sum (WCMS) and experiments showed that 60% of the noise could be removed [56]. Borsdorf proposed a correlation-based wavelet method for noise reduction in low-dose CT images [57]. Large-scale nonlocal mean filter is another commonly used post-processing algorithm, which carry out the nonlinear filtering correction in the current position by searching the matching information according to the self-similarity of the tissues under various doses in a large scale. This method has good performance in noise elimination and edge preservation. Chen proposed a large-scale nonlocal means (LNLM) filter to improve abdomen lowdose CT images by exploiting large-scale structure similarity knowledge, which was further combined with a multiscale directional diffusion scheme to reduce the streak artifacts in thoracic CT images [58]. Ma proposed a new nonlocal mean algorithm by combining nonlocal mean and the results obtained from previous normal-dose scans to deal with low-dose CT, and the image artifacts are solved in a certain extent by means of image guidance techniques [59]. In [60], feature knowledge in available CT database is incorporated into weight update in LNLM strategy, and a notable image quality enhancement was reported. Dictionary learning and sparse representation were also used for reconstruction and enhancement for low-dose X-ray imaging [61–64]. The dictionary technique studies from normal-dose CT images (feature extraction) guide the low-dose CT image processing. Dictionary technology combines the advantages of large-scale nonlocal filtering and image guidance technology, and has very good extendibility. However, they have the limitation of computation time. Recently, the deep learning technology is popular and shows great potential in image denoising. Chen trained a deep convolutional neural network (CNN) to transform low-dose CT images toward normaldose CT images, patch by patch and visual and quantitative evaluation demonstrates a competing performance of the proposed method [65]. Wu proposed a cascaded training network for low-dose CT image denoising, where the trained CNN was applied on the training dataset to initiate new trainings and remove artifacts [66]. Wolterink proposed to train a CNN jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise [67]. Kang applied a CNN to wavelet coefficients of low-dose CT images and showed that wavelet domain CNN was efficient in removing the noises from low-dose CT compared to an image domain CNN [68, 69].

reconstruction algorithm usually uses the neighborhood correlation of image space to construct a Markov field prior model [39, 40]. In this model, noise suppression is greatly affected by the noise level of projection data, and the constraint ability is declined when the projection data is seriously noisy. While some prior constructed by non-convex potential function may introduce additional staircase artifacts [41]. Bian proposed a total variation minimization lowdose CT reconstruction method based on a divergence constraint, which eliminates the block artifacts of the traditional total variation priors [42]. Chen considered the excellent denoising capability of nonlocal algorithm and proposed an adaptive-weighting nonlocal prior statistical reconstruction approach [43]. The proposed prior imposes an effective resolution-preserving and noise-removing regularization for reconstructions, and specially has a good recovery ability for region of gradated density. Zhang explored an adaptive Markov random field (MRF) based penalty term which utilizes previous normal-dose scan to obtain the MRF coefficients and incorporated it into the PWLS image reconstruction framework [44]. Li proposed a hybrid nonlocal means regularization model for iterative reconstruction of low-dose CT perfusion to

overcome the limitation of the conventional prior-image-induced penalty [45].

**2.3. Post-processing method**

78 State of the Art in Nano-bioimaging

However, IR techniques such as algebraic reconstruction technique (ART) always have high computation loads (e.g., up to several hours per data set), which have prevented fast clinical applications. It is urgent to improve the reconstruction speed and researchers have proposed a variety of methods to speed up the convergence rate of IR algorithms, for example, orderedsubsets image reconstructions [46–48]. However, the practical application of IR is still limited by hardware level. Fortunately, the development of parallel computing technology has played an important role in the application of IR. The computation time of IR can be greatly reduced by using the graphics processing units (GPUs) [49–51]. It is worth noting that IR techniques require access to the raw projection data (projection restoration also has this problem) and are highly dependent on special scanner model, that is, requiring more detailed information such as scanning geometry, photon statistics, data-acquisition, correction physics, thus highly dependent on specific scanner models. Its limitation appeals a more broadly used denoising method that can perform on different systems, and leads us to think more about denoising after reconstruction.

Image post-processing techniques, working on the image space alone, are retrospectively applied and relatively simple to implement without access to the raw projection data. Since post-processing methods directly enhance the existing CT images, they do not need to improve or replace the existing equipment, thus easy to be used and promoted. The main difficulty comes from the non-stationary mottle noise and streak-like artifacts, which often distribute over the whole CT image. These mottle noise and streak artifacts are caused by the back-projection process within the FBP algorithms, and are difficult to remove because they do not obey to specific distribution models. Various sophisticated techniques, considering the strong structural and statistical properties of objects in image space, have been proposed for improving the quality of low-dose CT images. In [52, 53], the low-dose CT reconstruction images are filtered by nonlinear or anisotropic filters, which can smooth the image effectively meanwhile preserve edges to some extent. But this kind of algorithms is easy to reduce the

In addition to X-ray intensity, to shorten scanning time can also reduce the radiation dose dramatically, which can be achieved by reducing projection angles (sparse angles or incomplete angles) in acquisition process. Due to the projection, data of CT systems usually have high redundancy, under the condition of less sampling angles, the missing data can be repaired to get a complete projection data set, and the reconstruction quality can be improved using the repaired data. In the decade, dictionary learning and TV (total variance) constraint are two effective techniques to estimate the missing projection data [70–76]. Recently, the convolutional neural network was also performed in sparse-view reconstruction (down to 50 views) on parallel-beam X-ray CT [77].

#### **2.4. ATCM technology**

In addition to adjusting scanning parameters, GE, Philips, Siemens and Toshiba introduced automatic tube current modulation (ATCM) to realize low-dose CT scanning. ATCM is based on differences of attenuation characteristics of human anatomy structure, and adjusts the tube current automatically according to the X-ray attenuation change. ATCM controls the tube current by using a certain algorithm and an optimized mode in the X-Y plane or along the scanning direction (Z-axis), thereby radiation doses are reduced in unnecessary projection direction. Another way, ATCM can achieve imaging with the minimum radiation dose by setting the image quality that meets certain criteria in advance. For example, the anteroposterior diameter of the chest and pelvis is significantly smaller than its right-and-left diameter. The anteroposterior tissue is thinner and the X-ray attenuation is lower, while the side is thicker and the X-ray attenuation is higher. Studies have shown that the total radiation dose can be reduced by 29.4% by using the ATCM technique for full-body scan, and the abdominal radiation dose can be reduced by 29.7% [78]. At the annual conference on radiology in North America in 2008, some manufacturers introduced selective shielding techniques that would allow the closure of X-ray when it rotates to the direct irradiation position of sensitive organs, such as eyes, thyroid and breast, thereby to avoid direct exposure to sensitive organs [79]. In addition, an asymmetric shielding acquisition system, called adaptive dose shield (ADS), can shield the invalid X-ray at the beginning and end of the Z-axis scan. Furthermore, it reasonably distributes the irradiation area with a cardiac bowtie. The radiation doses of cardiac scan are therefore reduced without increasing noise.

increase the SNR of acquired data and sequentially reduced the noise in CT images. They also designed wide-detector CT to improve time resolution and improved the detector material. One study reported that the wide-detector revolution CTA with 70 Kv tube voltage and prospective ECG-gated technique can provide high accuracy for assessment of congenital heart disease (CHD) in infants and children, which can keep good image quality, with the low radiation dose [85]. More significantly, it is the appearance of spectral CT, which can achieve high

Research Status and Prospect for CT Imaging http://dx.doi.org/10.5772/intechopen.73032 81

Advances in multi-detector technology, photon counting energy dispersive detectors and computer-processing technology have made spectral CT imaging possible [86–94]. Spectral CT can convert the X-ray absorption coefficient of any material to absorption coefficient of any two base material and achieve the same attenuation effect. On the basis of the improvement of X-ray tubes and X-ray detectors, spectral CT can obtain two images at different levels of energy at the same time and at the same phase to reconstruct high-definition and monochromatic images from 40 to 140 keV and even generate three materials decomposition images, virtual non-contrast images and specific spectrum curve. Thanks to innovations on the tube ball and detectors, spectral CT not only achieves high resolution, high-definition images in the case of low radiation dose, but also uses the spectral imaging technology for the first time. Spectral CT uses different X-ray spectra and certain chemical elements to detect changes in the shape and function of the whole body, and can realize single photon imaging and physical separation, thus fundamentally changes the traditional way of CT imaging based on a single CT value and provides reliable information to diagnose disease earlier and more accurately, showing a great advantage in imaging. As a new method of clinical application, spectral CT can be developed rapidly in the qualitative, quantitative diagnosis and prognosis evaluation of systemic diseases. Nowadays, it is a promising technique with clinical application potential and has become another direction of CT technology. At present, there are two clinical kinds of spectral CT equipment. One takes the

rapid kVp switching as the core technique and another is the dual-source CT (DSCT).

reduction in radiation dose is achieved compare to routine dose.

The rapid kVp switching technology is first launched by GE, that is, Discovery CT750 HD [95], it has a double energy system but only with a single source, as shown in **Figure 3**. This system is composed of a special X-ray source which can switch kVp in a very short time (0.5 ms) and detectors can detect the high-energy and low-energy photons, thus obtaining two projection data sets. Discovery CT750 HD adopt gemstone as the detector materials (that has more stability than traditional materials), rapid kVp switching and adaptive statistical iterative reconstruction (ASIR) technology, spectral grating imaging technology and so on, makes it has high resolution imaging with low radiation dose. Detectors made of gemstone ensure each image in a whole body scan reconstructed in a low-dose case from hardware. More importantly, ASIR is the key technology to achieve high resolution and low radiation dose at the same time. It can achieve the limit of 0.23 mm spatial resolution around the body, and find small lesions that cannot be found using a conventional CT scan, greatly improve the detection rate of the lesions and the identification of tumorous diseases [96]. Besides an approximate 50%

DSCT is first launched by Siemens, at the moment, there are two clinical, commercially available DSCT scanners: the SOMATOM Definition (the first generation DSCT, launched in 2005) and the SOMATOM Definition Flash (the second generation DSCT, launched in 2019). Each of them contains two X-ray tubes and two detectors which are mounted so that the X-ray

time resolution and high intensity resolution.

#### **3. Ultra low-dose CT**

In the decades, ultra low-dose CT, defined as a radiation dose ≤1.9 mSv, was studied and used [80, 81]. Accordingly, researchers pay attention to the reconstruction algorithms for high-quality ultra low-dose CT. Yu proposed a previous scan-regularized reconstruction (PSRR) method for ultra low-dose CT of lung perfusion [82]. His study demonstrated that approximately 90% reduction in radiation dose is achievable using PSRR without compromising quantitative computed tomographic measurements of regional lung function. Xu compared the effect of different reconstruction algorithm applications for ultra low-dose CT on image quality improvement using a phantom study [83]. Rob investigated whether ultra low-dose CT and low-dose CT KUB (kidney, ureters and bladder) for acute renal colic impacted upon the specificity, sensitivity and detection of urolithiasis, and found that both ultra low-dose CT and low-dose CT yield comparable results against standard-dose CT KUB in detecting alternative diagnoses (they may not be as effective in detecting stones <3 mm in size or in patients with a body mass index of >30 kg/m<sup>2</sup> ) [84]. For the foreseeable future, ultra low-dose CT with the tendency of CT development and more commonly used in clinical, especially for several months baby, and pregnant female. In a word, CT technologies have entered into low-dose imaging times.

#### **4. Spectral CT**

CT manufacturers have tried their best to improve the hardware for the improvement of reconstructed image quality for low-dose CT. For example, they improved the detection efficiency to increase the SNR of acquired data and sequentially reduced the noise in CT images. They also designed wide-detector CT to improve time resolution and improved the detector material. One study reported that the wide-detector revolution CTA with 70 Kv tube voltage and prospective ECG-gated technique can provide high accuracy for assessment of congenital heart disease (CHD) in infants and children, which can keep good image quality, with the low radiation dose [85]. More significantly, it is the appearance of spectral CT, which can achieve high time resolution and high intensity resolution.

**2.4. ATCM technology**

80 State of the Art in Nano-bioimaging

**3. Ultra low-dose CT**

of >30 kg/m<sup>2</sup>

**4. Spectral CT**

In addition to adjusting scanning parameters, GE, Philips, Siemens and Toshiba introduced automatic tube current modulation (ATCM) to realize low-dose CT scanning. ATCM is based on differences of attenuation characteristics of human anatomy structure, and adjusts the tube current automatically according to the X-ray attenuation change. ATCM controls the tube current by using a certain algorithm and an optimized mode in the X-Y plane or along the scanning direction (Z-axis), thereby radiation doses are reduced in unnecessary projection direction. Another way, ATCM can achieve imaging with the minimum radiation dose by setting the image quality that meets certain criteria in advance. For example, the anteroposterior diameter of the chest and pelvis is significantly smaller than its right-and-left diameter. The anteroposterior tissue is thinner and the X-ray attenuation is lower, while the side is thicker and the X-ray attenuation is higher. Studies have shown that the total radiation dose can be reduced by 29.4% by using the ATCM technique for full-body scan, and the abdominal radiation dose can be reduced by 29.7% [78]. At the annual conference on radiology in North America in 2008, some manufacturers introduced selective shielding techniques that would allow the closure of X-ray when it rotates to the direct irradiation position of sensitive organs, such as eyes, thyroid and breast, thereby to avoid direct exposure to sensitive organs [79]. In addition, an asymmetric shielding acquisition system, called adaptive dose shield (ADS), can shield the invalid X-ray at the beginning and end of the Z-axis scan. Furthermore, it reasonably distributes the irradiation area with a cardiac bowtie.

The radiation doses of cardiac scan are therefore reduced without increasing noise.

In the decades, ultra low-dose CT, defined as a radiation dose ≤1.9 mSv, was studied and used [80, 81]. Accordingly, researchers pay attention to the reconstruction algorithms for high-quality ultra low-dose CT. Yu proposed a previous scan-regularized reconstruction (PSRR) method for ultra low-dose CT of lung perfusion [82]. His study demonstrated that approximately 90% reduction in radiation dose is achievable using PSRR without compromising quantitative computed tomographic measurements of regional lung function. Xu compared the effect of different reconstruction algorithm applications for ultra low-dose CT on image quality improvement using a phantom study [83]. Rob investigated whether ultra low-dose CT and low-dose CT KUB (kidney, ureters and bladder) for acute renal colic impacted upon the specificity, sensitivity and detection of urolithiasis, and found that both ultra low-dose CT and low-dose CT yield comparable results against standard-dose CT KUB in detecting alternative diagnoses (they may not be as effective in detecting stones <3 mm in size or in patients with a body mass index

) [84]. For the foreseeable future, ultra low-dose CT with the tendency of CT devel-

opment and more commonly used in clinical, especially for several months baby, and pregnant

CT manufacturers have tried their best to improve the hardware for the improvement of reconstructed image quality for low-dose CT. For example, they improved the detection efficiency to

female. In a word, CT technologies have entered into low-dose imaging times.

Advances in multi-detector technology, photon counting energy dispersive detectors and computer-processing technology have made spectral CT imaging possible [86–94]. Spectral CT can convert the X-ray absorption coefficient of any material to absorption coefficient of any two base material and achieve the same attenuation effect. On the basis of the improvement of X-ray tubes and X-ray detectors, spectral CT can obtain two images at different levels of energy at the same time and at the same phase to reconstruct high-definition and monochromatic images from 40 to 140 keV and even generate three materials decomposition images, virtual non-contrast images and specific spectrum curve. Thanks to innovations on the tube ball and detectors, spectral CT not only achieves high resolution, high-definition images in the case of low radiation dose, but also uses the spectral imaging technology for the first time. Spectral CT uses different X-ray spectra and certain chemical elements to detect changes in the shape and function of the whole body, and can realize single photon imaging and physical separation, thus fundamentally changes the traditional way of CT imaging based on a single CT value and provides reliable information to diagnose disease earlier and more accurately, showing a great advantage in imaging. As a new method of clinical application, spectral CT can be developed rapidly in the qualitative, quantitative diagnosis and prognosis evaluation of systemic diseases. Nowadays, it is a promising technique with clinical application potential and has become another direction of CT technology. At present, there are two clinical kinds of spectral CT equipment. One takes the rapid kVp switching as the core technique and another is the dual-source CT (DSCT).

The rapid kVp switching technology is first launched by GE, that is, Discovery CT750 HD [95], it has a double energy system but only with a single source, as shown in **Figure 3**. This system is composed of a special X-ray source which can switch kVp in a very short time (0.5 ms) and detectors can detect the high-energy and low-energy photons, thus obtaining two projection data sets. Discovery CT750 HD adopt gemstone as the detector materials (that has more stability than traditional materials), rapid kVp switching and adaptive statistical iterative reconstruction (ASIR) technology, spectral grating imaging technology and so on, makes it has high resolution imaging with low radiation dose. Detectors made of gemstone ensure each image in a whole body scan reconstructed in a low-dose case from hardware. More importantly, ASIR is the key technology to achieve high resolution and low radiation dose at the same time. It can achieve the limit of 0.23 mm spatial resolution around the body, and find small lesions that cannot be found using a conventional CT scan, greatly improve the detection rate of the lesions and the identification of tumorous diseases [96]. Besides an approximate 50% reduction in radiation dose is achieved compare to routine dose.

DSCT is first launched by Siemens, at the moment, there are two clinical, commercially available DSCT scanners: the SOMATOM Definition (the first generation DSCT, launched in 2005) and the SOMATOM Definition Flash (the second generation DSCT, launched in 2019). Each of them contains two X-ray tubes and two detectors which are mounted so that the X-ray

etc., or one set of fusion image reconstruction, mainly used for high time resolution requirements such as the cardiac workup. DSCT has advantages on time resolution, only 83 ms in SOMATOM Definition and 75 ms in SOMATOM Definition Flash, thus lead to a low radiation dose. In a word, DSCT provides faster scanning speed and lower radiation dose, and completely broke the traditional idea of CT technology, leading to a new revolution in CT history.

Research Status and Prospect for CT Imaging http://dx.doi.org/10.5772/intechopen.73032 83

In addition to technologies mentioned above, CT contrast agents that often used for distinguishing subtle changes of soft tissues with similar densities, also makes, or rather, requires a low kVp, that is, low-dose radiation. Studies have shown that a lower kVp can improve the enhancement degree of contrast agent and thus improve the contrast between different tissues [97]. Especially in turn, using this low-dose CT, one can obtain good images with a low contrast agent dose, because contrast agent is harmful to human health. For example, often used contrast agent in angiography imaging, iodinated compounds, have relatively short circulation times in vivo and its rapid renal clearance may lead to serious adverse effects.

A long-sought-after CT contrast agent is the nanoparticle, which has tunable composition, shape and size, and can be readily attached to bioconjugates with interesting biofunctionalities on their surface [98, 99]. Nano-sized iodinated CT contrast agents have been developed that can increase the circulation time and decrease the adverse effects [100]. The classical nanoparticulate iodine-containing contrast agents include liposomal contrast agents, nanosuspensions, nanoemulsions, nanocapsules and polymeric nanoparticles [101]. Despite prolonged in vivo circulation time as compared to iodinated molecules, iodine-conjugated nanoparticles are still limited by iodine loading through surface covalent conjugation [102]. Moreover, iodinated agents cannot be used for those patients who are iodine hypersensitive. These appeals to new CT contrast agents using nanoparticles composed of other elements with higher X-ray attenuation. In 2006, Hainfeld first introduced gold nanoparticles (AuNPs) as CT contrast agent [103], and caused a lot of attention since gold has a higher atomic number than iodine, and thus, has a larger X-ray attenuation. Moreover, the size and shape of gold nanostructures can be easily controlled, and their surface can be modified with various functional groups [102]. Besides, it has good biotolerability and nontoxicity. All of these make AuNPs attract intense interest as CT contrast agents. Over the past few years, many studies on Au nanoparticle design techniques are reported and show good significant CT image enhancement [104–108]. In addition to iodine and gold, other nanoparticles based on heavy atoms such as lanthanides, Bismuth and tantalum Bismuth-based contrast agents, have been

With the progress of micro-nano processing technology, nano-ray source, micron grade CCD with nanoscale resolution, precise optical focusing imaging device, synchronous radiation source with high brightness, CT is being extended to the nanoscale, that is, nano-CT, bringing us startlingly accurate pictures of objects [111]. Nano-CT is derived from micro-CT but with higher resolution. At present, it has been widely used in many fields such as biology imaging,

Therefore, a variety of CT contrast agents are required to be developed.

used as more efficient CT contrast agents [109, 110].

**5. Nano-CT**

**Figure 3.** Diagram of discovery CT750 HD system.

beams are approximately perpendicular to each other, as shown in **Figure 4**. DSCT has two working model, that is, single source model and double source model. It works like an ordinary CT when using the single source model, while two acquisition systems work simultaneously when using the double source model. Thus one can obtain two independent sets of images, mainly used for separation of bones and calcification, tissue and collagen component,

**Figure 4.** Diagram of DSCT system.

etc., or one set of fusion image reconstruction, mainly used for high time resolution requirements such as the cardiac workup. DSCT has advantages on time resolution, only 83 ms in SOMATOM Definition and 75 ms in SOMATOM Definition Flash, thus lead to a low radiation dose. In a word, DSCT provides faster scanning speed and lower radiation dose, and completely broke the traditional idea of CT technology, leading to a new revolution in CT history.

### **5. Nano-CT**

**Figure 4.** Diagram of DSCT system.

**Figure 3.** Diagram of discovery CT750 HD system.

82 State of the Art in Nano-bioimaging

beams are approximately perpendicular to each other, as shown in **Figure 4**. DSCT has two working model, that is, single source model and double source model. It works like an ordinary CT when using the single source model, while two acquisition systems work simultaneously when using the double source model. Thus one can obtain two independent sets of images, mainly used for separation of bones and calcification, tissue and collagen component, In addition to technologies mentioned above, CT contrast agents that often used for distinguishing subtle changes of soft tissues with similar densities, also makes, or rather, requires a low kVp, that is, low-dose radiation. Studies have shown that a lower kVp can improve the enhancement degree of contrast agent and thus improve the contrast between different tissues [97]. Especially in turn, using this low-dose CT, one can obtain good images with a low contrast agent dose, because contrast agent is harmful to human health. For example, often used contrast agent in angiography imaging, iodinated compounds, have relatively short circulation times in vivo and its rapid renal clearance may lead to serious adverse effects. Therefore, a variety of CT contrast agents are required to be developed.

A long-sought-after CT contrast agent is the nanoparticle, which has tunable composition, shape and size, and can be readily attached to bioconjugates with interesting biofunctionalities on their surface [98, 99]. Nano-sized iodinated CT contrast agents have been developed that can increase the circulation time and decrease the adverse effects [100]. The classical nanoparticulate iodine-containing contrast agents include liposomal contrast agents, nanosuspensions, nanoemulsions, nanocapsules and polymeric nanoparticles [101]. Despite prolonged in vivo circulation time as compared to iodinated molecules, iodine-conjugated nanoparticles are still limited by iodine loading through surface covalent conjugation [102]. Moreover, iodinated agents cannot be used for those patients who are iodine hypersensitive. These appeals to new CT contrast agents using nanoparticles composed of other elements with higher X-ray attenuation. In 2006, Hainfeld first introduced gold nanoparticles (AuNPs) as CT contrast agent [103], and caused a lot of attention since gold has a higher atomic number than iodine, and thus, has a larger X-ray attenuation. Moreover, the size and shape of gold nanostructures can be easily controlled, and their surface can be modified with various functional groups [102]. Besides, it has good biotolerability and nontoxicity. All of these make AuNPs attract intense interest as CT contrast agents. Over the past few years, many studies on Au nanoparticle design techniques are reported and show good significant CT image enhancement [104–108]. In addition to iodine and gold, other nanoparticles based on heavy atoms such as lanthanides, Bismuth and tantalum Bismuth-based contrast agents, have been used as more efficient CT contrast agents [109, 110].

With the progress of micro-nano processing technology, nano-ray source, micron grade CCD with nanoscale resolution, precise optical focusing imaging device, synchronous radiation source with high brightness, CT is being extended to the nanoscale, that is, nano-CT, bringing us startlingly accurate pictures of objects [111]. Nano-CT is derived from micro-CT but with higher resolution. At present, it has been widely used in many fields such as biology imaging, pathological examination, integrated circuit testing and so on, and it is believed to have broad application prospects. For example, the phoenix nanotom® m, which is a nanoCT® system, has been used in industry and realized a unique spatial and contrast resolution on a wide sample and application range. Nano-CT also has been developed at the European synchrotron radiation facility (ESRF) to image bone tissue at the nanoscale [112].

[2] Brenner DJ, Hall EJ. Computed tomography–An increasing source of radiation exposure. New England Journal of Medicine. 2007;**357**(22):2277-2284. DOI: 10.1056/NEJMra072149

Research Status and Prospect for CT Imaging http://dx.doi.org/10.5772/intechopen.73032 85

[3] Brenner D, Elliston C, Hall E, Berdon W. Estimated risks of radiation-induced fatal cancer from pediatric CT. AJR American Journal of Roentgenology. 2001;**176**(2):289-296.

[4] Shrimpton PC, Hillier MC, Lewis MA, Dunn M. National survey of doses from CT in the UK: 2003. British Journal of Radiology. 2006;**79**(948):968-980. DOI: 10.1259/bjr/93277434 [5] Naidich DP, Marshall CH, Gribbin C, et al. Low-dose CT of the lungs: Preliminary observations. Radiology. 1990;**175**(3):729-731. DOI: 10.1148/radiology.175.3.2343122

[6] Bach PB, Jett JR, Pastorino U, et al. Computed tomography screening and lung cancer

[7] Hausleiter J, Meyer T, Hermann F, et al. Estimated radiation dose associated with cardiac CT angiography. JAMA. 2009;**301**(5):500-507. DOI: 10.1001/jama.2009.54

[8] Stephen AE, Segev DL, Ryan DP, et al. The diagnosis of acute appendicitis in a pediatric population: To CT or not to CT. Journal of Pediatric Surgery. 2003;**38**(3):367-371. DOI:

[9] Wang Y, Shao Y, Gui Z, etal. A novel fractional-order differentiation model for low-dose CT image processing. IEEE Access. 2016;**4**(2):8487-8499. DOI: 10.1109/ACCESS.2016.2633272

[10] Nyman U, Ahl TL, Kristiansson M, et al. Patient-circumference-adapted dose regulation in body computed tomography. A practical and flexible formula. Acta Radiologica.

[11] Heneghan JP, Mcguire KA, Leder RA, et al. Helical CT for nephrolithiasis and ureterolithiasis: Comparison of conventional and reduced radiation-dose techniques. Radiology.

[12] Liu Y, Castro M, Lederlin M, et al. Edge-preserving denoising for intra-operative cone beam CT in endovascular aneurysm repair. Computerized Medical Imaging and

[13] Hsieh J.Adaptive streak artifact reduction in computed tomography resulting from excessive x-ray photon noise. Medical Physics. 1998;**25**(11):2139-2147. DOI: 10.1118/1.598410

[14] Elbakri IA, Fessler JA. Statistical image reconstruction for polyenergetic X-ray computed tomography. IEEE Transactions on Medical Imaging. 2002;**21**(2):89-99. DOI:

[15] Elbakri IA, Fessler JA. Efficient and accurate likelihood for iterative image reconstruction in x-ray computed tomography. SPIE Medical Imaging. 2003;**5032**:1839-1850. DOI:

[16] Li T, Li X, Wang J, et al. Nonlinear sinogram smoothing for low-dose X-ray CT. IEEE Transactions on Nuclear Science. 2004;**51**(5):2505-2513. DOI: 10.1109/TNS.2004.834824 [17] Wang J, Li T, Lu H, et al. Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography. IEEE Transactions on Medical Imaging. 2006;**25**(10):1272-1283. DOI: 10.1109/TMI.2006.882141

outcomes. JAMA. 2007;**297**(9):953-961. DOI: 10.1001/jama.297.9.953

2005;**46**(4):396-406. DOI: 10.1080/02841850510021193

2003;**229**(2):575-580. DOI: 10.1148/radiol.2292021261

Graphics. 2017;**56**:49-59. DOI: 10.1016/j.compmedimag.2017.01.004

DOI: 10.2214/ajr.176.2.1760289

10.1053/jpsu.2003.50110

10.1109/42.993128

10.1117/12.480302

#### **6. Summary**

In recent years, CT has been developing steadily and the scope of clinical application has been continuously expanded. Now we pay more attention on utility-driven CT instead of algorithm-driven CT. Low-dose CT, ultra low-dose CT and spectral CT are representative directions of CT application, and the rapid development of the hardware provides substantial support. The future development of CT equipment is spectral CT, low-dose CT and even harmless CT. It is believed that with the progress of the ball tube and detector technology, the X-ray dose problem will be completely solved 1 day. The promotion of low-dose CT, combining the enhancement of time resolution, spatial resolution and density resolution, will make CT under the condition of safety and low-dose radiation, achieve more quickly in a clearer image display, making the disease more early and more clearly diagnosed. CT themselves will play an effective role clinical diagnosis and evaluation for more disease in such a high level of display. CT vendors shall stand to win in the fierce market competition if they step up such developments and win praise from the medical community and the whole people.

#### **Acknowledgements**

This work has been partially supported by the Shanxi Province Science Foundation for Youths (201601D021080), Research Project Supported by Shanxi Scholarship Council of China (2016- 085), National Key Research and Development Program of China (2016YFC0101602) and Science Foundation of North University of China (XJJ2016019).

#### **Author details**

Yi Liu

Address all correspondence to: liuyi@nuc.edu.cn

Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan, China

#### **References**

[1] Cierniak R. X-Ray Computed Tomography in Biomedical Engineering. London: Springer; 2011

[2] Brenner DJ, Hall EJ. Computed tomography–An increasing source of radiation exposure. New England Journal of Medicine. 2007;**357**(22):2277-2284. DOI: 10.1056/NEJMra072149

pathological examination, integrated circuit testing and so on, and it is believed to have broad application prospects. For example, the phoenix nanotom® m, which is a nanoCT® system, has been used in industry and realized a unique spatial and contrast resolution on a wide sample and application range. Nano-CT also has been developed at the European synchro-

In recent years, CT has been developing steadily and the scope of clinical application has been continuously expanded. Now we pay more attention on utility-driven CT instead of algorithm-driven CT. Low-dose CT, ultra low-dose CT and spectral CT are representative directions of CT application, and the rapid development of the hardware provides substantial support. The future development of CT equipment is spectral CT, low-dose CT and even harmless CT. It is believed that with the progress of the ball tube and detector technology, the X-ray dose problem will be completely solved 1 day. The promotion of low-dose CT, combining the enhancement of time resolution, spatial resolution and density resolution, will make CT under the condition of safety and low-dose radiation, achieve more quickly in a clearer image display, making the disease more early and more clearly diagnosed. CT themselves will play an effective role clinical diagnosis and evaluation for more disease in such a high level of display. CT vendors shall stand to win in the fierce market competition if they step up such developments and win praise from the medical community and the whole people.

This work has been partially supported by the Shanxi Province Science Foundation for Youths (201601D021080), Research Project Supported by Shanxi Scholarship Council of China (2016- 085), National Key Research and Development Program of China (2016YFC0101602) and

Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of

[1] Cierniak R. X-Ray Computed Tomography in Biomedical Engineering. London: Springer;

Science Foundation of North University of China (XJJ2016019).

Address all correspondence to: liuyi@nuc.edu.cn

tron radiation facility (ESRF) to image bone tissue at the nanoscale [112].

**6. Summary**

84 State of the Art in Nano-bioimaging

**Acknowledgements**

**Author details**

China, Taiyuan, China

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Yi Liu


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**Chapter 6**

**Provisional chapter**

**Biocompatible Magic Sized Quantum Dots:**

**Biocompatible Magic Sized Quantum Dots:** 

DOI: 10.5772/intechopen.72841

**Luminescent Markers and Probes**

**Luminescent Markers and Probes**

Fernanda Van Petten Vasconcelos Azevedo, Jéssica Peixoto Rodrigues, Luiz Ricardo Goulart, Veridiana de Melo Ávila and Noelio Oliveira Dantas

Fernanda Van Petten Vasconcelos Azevedo, Jéssica Peixoto Rodrigues, Luiz Ricardo Goulart, Veridiana de Melo Ávila and Noelio Oliveira Dantas

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

Nanotechnology in life sciences has as one of its objectives to diagnose diseases in a precise, fast and effective way, offering improvements to the existing diagnostic methods. In this sense, several nanomaterials have been studied and developed to benefit the biomedical

Nanoscience and nanobiotechnology have aroused great academic and technological interest. Works relating biomaterials at the nanoscale can reach new biotechnologies and help in the development and use of tools for bioimage and diagnosis applications. In this work we demonstrated the advantages of magic sized quantum dots as luminescent markers and probes to bioimage applications. The visualization of MSQDs bioconjugated with biological probes in cells were performed at periods greater than 2 h, and visualization with no commercial dye would not be possible. Therefore, we demonstrated that theses biocompatible nanocrystals are luminescent markers and probes

**Keywords:** nanocrystals, biocompatibility, luminescence, bioconjugation, probes

http://dx.doi.org/10.5772/intechopen.72841

**Abstract**

to diagnosis.

**1. Introduction**

technologies.

Anielle Christine Almeida Silva,

Anielle Christine Almeida Silva,

Lucas Ian Veloso Correia, Marcelo José Barbosa Silva, Mariana Alves Pereira Zóia,

Lucas Ian Veloso Correia, Marcelo José Barbosa Silva, Mariana Alves Pereira Zóia,

#### **Chapter 6**

**Provisional chapter**

#### **Biocompatible Magic Sized Quantum Dots: Luminescent Markers and Probes Luminescent Markers and Probes**

**Biocompatible Magic Sized Quantum Dots:** 

DOI: 10.5772/intechopen.72841

Anielle Christine Almeida Silva, Lucas Ian Veloso Correia, Marcelo José Barbosa Silva, Mariana Alves Pereira Zóia, Fernanda Van Petten Vasconcelos Azevedo, Jéssica Peixoto Rodrigues, Luiz Ricardo Goulart, Veridiana de Melo Ávila and Noelio Oliveira Dantas Lucas Ian Veloso Correia, Marcelo José Barbosa Silva, Mariana Alves Pereira Zóia, Fernanda Van Petten Vasconcelos Azevedo, Jéssica Peixoto Rodrigues, Luiz Ricardo Goulart, Veridiana de Melo Ávila and Noelio Oliveira Dantas Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.72841

Anielle Christine Almeida Silva,

#### **Abstract**

Nanoscience and nanobiotechnology have aroused great academic and technological interest. Works relating biomaterials at the nanoscale can reach new biotechnologies and help in the development and use of tools for bioimage and diagnosis applications. In this work we demonstrated the advantages of magic sized quantum dots as luminescent markers and probes to bioimage applications. The visualization of MSQDs bioconjugated with biological probes in cells were performed at periods greater than 2 h, and visualization with no commercial dye would not be possible. Therefore, we demonstrated that theses biocompatible nanocrystals are luminescent markers and probes to diagnosis.

**Keywords:** nanocrystals, biocompatibility, luminescence, bioconjugation, probes

#### **1. Introduction**

Nanotechnology in life sciences has as one of its objectives to diagnose diseases in a precise, fast and effective way, offering improvements to the existing diagnostic methods. In this sense, several nanomaterials have been studied and developed to benefit the biomedical technologies.

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

One of the nanomaterials with high potential for application in nanomedicine is the quantum dot, which is a semiconductor nanoparticle. This nanoparticle is a promising material for the diagnosis and understanding of cell biology, being used both for image generation and for detection of signals through [1–3].

the quantum dots, they can be injected into cells by the micro injection technique. Once inside

Biocompatible Magic Sized Quantum Dots: Luminescent Markers and Probes

http://dx.doi.org/10.5772/intechopen.72841

97

Recently, it has been shown that the magic-sized quantum dots (MSQDs) present great advantages in the medical and biological area. These MSQDs are quantum dots with extremely small sizes (<2 nm) and physical properties that are completely different from those presented by QDs [34, 35]. These MSQDs present thermodynamically stable structures, wide luminescence range, great size stability over time, relatively narrow absorption spectra, and heterogenic growth [36, 37]. The term magic size is related to a (magic) number of atoms in the structure that makes MSQDs extremely stable. The wide luminescence spectrum occurs

The MSQDs can be important tools in the investigation of metastases and have been proposed as vehicles for administering drugs that can initiate certain photoactivated chemical reactions due to highly stable luminescence over time [39]. The cultures of cells marked with MSQDs continue to maintain their functions, remaining viable for analysis for prolonged periods of time [39–42].

In this chapter we highlight the advantages of MSQDs as a biocompatible luminescent marker and its use as a specific probe. In the biological labeling assays, we use CdSe/CdS MSQDs bioconjugated with Pepstatin A, BnSP-6, BthTx-II and a specific BC Fab antibody to allow its tracking within the cell and, in addition, to verify the specificity of this treatment for breast cancer cells.

**Figure 1a** shows the absorption and emission spectra of CdSe/CdSe MSQDs that observed a narrow band around 428 nm and a broad emission spectrum, respectively [41]. This broad emission is characteristics of the MSQDs and that is of great applicability in biological processes, enabling their visualization in different detection channels, varying from blue to red (**Figure 1a**) [43]. Using the three detection filters, the fluorescence images of the MSQDs in the

One of the major problems of organic fluorophores besides cytotoxicity is the duration of luminescence, making it impossible to trace and observe biological assays as a function of time. Quantum dots present high intensity of luminescence compared to dyes and a monitoring time greater than 2 h, but after this time is observed a drastic decrease of luminescence intensity, that difficult of monitoring. This occurs because QDs interact with cellular proteins and decrease the luminescence intensity over time [17]. However, the high stability of MSQDS

The fluorescence images of the CdSe MSQDs in HeLa cells after (a) 24 h and (b) 36 h are shown in **Figure 2**. It is verified that even after 36 h it is possible to visualize the luminescence of MSQDs. In **Figure 2(c)** it is shown that the observed luminescence is due to a set of MSQDs and that they were constructed with the CdSe core, a thin layer of CdS and functionalized with hydroxyl groups. These results show that the MSQDs can be used as biocompatible

**2. Magic quantum dots luminescent markers and probes**

allows the highly stable luminescence, even after 36 h, (**Figure 2**) [39].

the cells, the QDs biochemical reaction [27, 31–33].

because MSQDs have internal atomic defects [38].

cells were recorded (**Figure 1b**–**d**) [39–41].

luminescent markers [39].

Measures based on fluorescence have biochemical specificity and high sensitivity. There is considerable interest in the use of quantum dots as inorganic fluorophores because they have significant advantages over conventionally used fluorescent markers. For this, it is necessary that these nanoparticles are biocompatible so that they are conjugated properly to biological molecules, by means of bioconjugation techniques [4–7].

In cell biology it has been a practice to use fluorescent labels such as organic dyes, coordinating compounds of lanthanide ions and recombinant fluorescent proteins [8–12]. Organic fluorophores are used as molecular markers to identify structural compartments, molecules, or organelles. These fluorophores can be linked (conjugated) to the target directly or indirectly through conjugation with antibodies and other molecules that bind secondarily to the target. The fluorophore DAPI (4′6-diamidino-2-phenylindole), for example, has affinity for DNA molecules, and is commonly employed for labeling in cell nuclei.

Although they are widely used in the labeling of cellular structures, tissues and organisms, some limitations of these fluorophores should be considered. An irreversible photochemical reaction common to fluorophores is the photobleaching or photodegradation caused by the photochemical destruction of the fluorophore, causing them to irreversibly lose their fluorescence, either after being excited or after a few minutes, depending on the intensity of the source of excitation [13–15].

In this way, samples stained with such dyes need to be kept in dark environments and the microscopy section needs to be performed quickly, making it difficult to monitor a whole cellular process. In addition to photodegradation, other disadvantages involved in these types of labeling are: high toxicity and cell death using ultraviolet (UV) [16–18]. Fluorescent proteins such as GFP (Green Fluorescent Protein) are apparently non-toxic, but may induce undesired cellular processes, and it is a laborious technique.

Due to the disadvantages in the use of conventional fluorophores, several researches have been directed towards the development and reproducibility in the synthesis of nanocrystals for use in bio detection and bioimaging [19–21]. In particular, quantum dots (QDs) have been extensively studied because they exhibit high absorption and the absorption and emission spectra are easily controlled as a function of size, shape and crystalline phase [15, 19, 22], this enables tuning of the emission length as well as high efficiency. Like this, multicolored images can be obtained with the same material when it has different diameters [19, 21, 23, 24].

Unlike most conventional dyes which have a narrow absorption spectrum, the QDs have the additional advantage that a single laser can excite luminescence at different wavelengths while each organic dye must be excited over a long length of single wave and well defined [25–29].

The studies and applications of QDs reveal their efficacy as new luminescent probes for diagnostic purposes, enabling real-time acquisition of a single cell surface receptor, as well as the development of non-invasive models for the detection of small tumors [30]. Another highlight is the application of the QDs in living cells and tissues. Depending on the binder attached to the quantum dots, they can be injected into cells by the micro injection technique. Once inside the cells, the QDs biochemical reaction [27, 31–33].

One of the nanomaterials with high potential for application in nanomedicine is the quantum dot, which is a semiconductor nanoparticle. This nanoparticle is a promising material for the diagnosis and understanding of cell biology, being used both for image generation and for

Measures based on fluorescence have biochemical specificity and high sensitivity. There is considerable interest in the use of quantum dots as inorganic fluorophores because they have significant advantages over conventionally used fluorescent markers. For this, it is necessary that these nanoparticles are biocompatible so that they are conjugated properly to biological

In cell biology it has been a practice to use fluorescent labels such as organic dyes, coordinating compounds of lanthanide ions and recombinant fluorescent proteins [8–12]. Organic fluorophores are used as molecular markers to identify structural compartments, molecules, or organelles. These fluorophores can be linked (conjugated) to the target directly or indirectly through conjugation with antibodies and other molecules that bind secondarily to the target. The fluorophore DAPI (4′6-diamidino-2-phenylindole), for example, has affinity for DNA

Although they are widely used in the labeling of cellular structures, tissues and organisms, some limitations of these fluorophores should be considered. An irreversible photochemical reaction common to fluorophores is the photobleaching or photodegradation caused by the photochemical destruction of the fluorophore, causing them to irreversibly lose their fluorescence, either after being excited or after a few minutes, depending on the intensity of the source of excitation [13–15]. In this way, samples stained with such dyes need to be kept in dark environments and the microscopy section needs to be performed quickly, making it difficult to monitor a whole cellular process. In addition to photodegradation, other disadvantages involved in these types of labeling are: high toxicity and cell death using ultraviolet (UV) [16–18]. Fluorescent proteins such as GFP (Green Fluorescent Protein) are apparently non-toxic, but may induce undesired

Due to the disadvantages in the use of conventional fluorophores, several researches have been directed towards the development and reproducibility in the synthesis of nanocrystals for use in bio detection and bioimaging [19–21]. In particular, quantum dots (QDs) have been extensively studied because they exhibit high absorption and the absorption and emission spectra are easily controlled as a function of size, shape and crystalline phase [15, 19, 22], this enables tuning of the emission length as well as high efficiency. Like this, multicolored images can be obtained with the same material when it has different diameters [19, 21, 23, 24].

Unlike most conventional dyes which have a narrow absorption spectrum, the QDs have the additional advantage that a single laser can excite luminescence at different wavelengths while each organic dye must be excited over a long length of single wave and well defined [25–29]. The studies and applications of QDs reveal their efficacy as new luminescent probes for diagnostic purposes, enabling real-time acquisition of a single cell surface receptor, as well as the development of non-invasive models for the detection of small tumors [30]. Another highlight is the application of the QDs in living cells and tissues. Depending on the binder attached to

detection of signals through [1–3].

96 State of the Art in Nano-bioimaging

molecules, by means of bioconjugation techniques [4–7].

molecules, and is commonly employed for labeling in cell nuclei.

cellular processes, and it is a laborious technique.

Recently, it has been shown that the magic-sized quantum dots (MSQDs) present great advantages in the medical and biological area. These MSQDs are quantum dots with extremely small sizes (<2 nm) and physical properties that are completely different from those presented by QDs [34, 35]. These MSQDs present thermodynamically stable structures, wide luminescence range, great size stability over time, relatively narrow absorption spectra, and heterogenic growth [36, 37]. The term magic size is related to a (magic) number of atoms in the structure that makes MSQDs extremely stable. The wide luminescence spectrum occurs because MSQDs have internal atomic defects [38].

The MSQDs can be important tools in the investigation of metastases and have been proposed as vehicles for administering drugs that can initiate certain photoactivated chemical reactions due to highly stable luminescence over time [39]. The cultures of cells marked with MSQDs continue to maintain their functions, remaining viable for analysis for prolonged periods of time [39–42].

In this chapter we highlight the advantages of MSQDs as a biocompatible luminescent marker and its use as a specific probe. In the biological labeling assays, we use CdSe/CdS MSQDs bioconjugated with Pepstatin A, BnSP-6, BthTx-II and a specific BC Fab antibody to allow its tracking within the cell and, in addition, to verify the specificity of this treatment for breast cancer cells.

#### **2. Magic quantum dots luminescent markers and probes**

**Figure 1a** shows the absorption and emission spectra of CdSe/CdSe MSQDs that observed a narrow band around 428 nm and a broad emission spectrum, respectively [41]. This broad emission is characteristics of the MSQDs and that is of great applicability in biological processes, enabling their visualization in different detection channels, varying from blue to red (**Figure 1a**) [43]. Using the three detection filters, the fluorescence images of the MSQDs in the cells were recorded (**Figure 1b**–**d**) [39–41].

One of the major problems of organic fluorophores besides cytotoxicity is the duration of luminescence, making it impossible to trace and observe biological assays as a function of time. Quantum dots present high intensity of luminescence compared to dyes and a monitoring time greater than 2 h, but after this time is observed a drastic decrease of luminescence intensity, that difficult of monitoring. This occurs because QDs interact with cellular proteins and decrease the luminescence intensity over time [17]. However, the high stability of MSQDS allows the highly stable luminescence, even after 36 h, (**Figure 2**) [39].

The fluorescence images of the CdSe MSQDs in HeLa cells after (a) 24 h and (b) 36 h are shown in **Figure 2**. It is verified that even after 36 h it is possible to visualize the luminescence of MSQDs. In **Figure 2(c)** it is shown that the observed luminescence is due to a set of MSQDs and that they were constructed with the CdSe core, a thin layer of CdS and functionalized with hydroxyl groups. These results show that the MSQDs can be used as biocompatible luminescent markers [39].

**Figure 1.** (a) Absorption and fluorescence spectra of CdSe/CdS MSQDs, (b)–(d) fluorescence images of MSQDS in cells using the blue, green and red detection filters, respectively [39–41].

Therefore, the photostable MSQDs allow researchers to investigate the distinct cellular process, in the form of experiments with phagocytosis and vesicles intracellular traffic [44]. Regarding in vivo experiments, stable luminescence MSQDs could be used for tumor cells migration since the monitoring could be done for days.

**Figure 2.** Fluorescent image of incubation with 0.05 M of MSQDs (a) after 24 h and (b) after 36 h. White arrow indicates MSQDs interacted to cellular membrane. Arrows head indicates MSQDs inside the cells. Scale bar = 200 μm.

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99

and (c) B-action mRNA fold/control in function of diminution of Cd2+

adsorbed on their surface, (b) Viability in

(increase of Se).

(c) Representation of a set of MSQDs [39].

function of diminution of Cd2+

**Figure 3.** (a) Representation of CdSe MSQDs with different amounts of Cd2+

It is crucial the high biocompatibility of MSQDs, in other words, they cannot be harmful to the cells. It is well known that MSQDs have cadmium ions (Cd2+) adsorbed in their superficies. The manipulation of the composition and diameter of core and shell of MSQDs reduce the cellular contact with Cd2+. In this scenario, Cd2+ could stimulate various noxious effects as apoptosis, necrosis and DNA damage by the induction of reactive oxygen species production. Such effects extremely change the biology of the cells. For example, in an experiment with phagocytosis and intracellular traffic, apoptotic cells present a deficient phagocytose process which can infer misunderstand able results [39].

To investigate the true cause of the cytotoxic effect of cadmium chalcogenides QDs, we synthesized CdSe MSQDs with different amounts of Cd2+ adsorbed on their surface and have shown that this quantity is directly related to cytotoxicity (**Figure 3 a,b**). The biocompatibility is increased with decrease of Cd2+ adsorbed on MSQDs surface (**Figure 3b**). In addition, the decrease of Cd2+ is confirmed by the lower expression of the protein (**Figure 3c**). Thus, based on this, we developed new synthesis methodologies to develop a CdS shell using the Cd2+ adsorbed [45, 46]. Thus, we have shown in our recent studies that this shell increases biocompatibility and has no immunological effects [41].

**Figure 4** shows fluorescence images of CdSe/CdSe MSQDs alone and bioconjugated Pepstatin A, BnSP-6, BthTx-II and a specific BC Fab antibody in the MDA-MB-23.1 [40, 41]. The fluorescence from MSQDs bioconjugated was detected inside the cells' nuclei compartment of MDA-MB-231. Notably, we verified that the MSQDs alone were not internalized in MDA-MB-231 (**Figure 4a**) [40].

Biocompatible Magic Sized Quantum Dots: Luminescent Markers and Probes http://dx.doi.org/10.5772/intechopen.72841 99

**Figure 2.** Fluorescent image of incubation with 0.05 M of MSQDs (a) after 24 h and (b) after 36 h. White arrow indicates MSQDs interacted to cellular membrane. Arrows head indicates MSQDs inside the cells. Scale bar = 200 μm. (c) Representation of a set of MSQDs [39].

Therefore, the photostable MSQDs allow researchers to investigate the distinct cellular process, in the form of experiments with phagocytosis and vesicles intracellular traffic [44]. Regarding in vivo experiments, stable luminescence MSQDs could be used for tumor cells

**Figure 1.** (a) Absorption and fluorescence spectra of CdSe/CdS MSQDs, (b)–(d) fluorescence images of MSQDS in cells

It is crucial the high biocompatibility of MSQDs, in other words, they cannot be harmful to the cells. It is well known that MSQDs have cadmium ions (Cd2+) adsorbed in their superficies. The manipulation of the composition and diameter of core and shell of MSQDs reduce the cellular contact with Cd2+. In this scenario, Cd2+ could stimulate various noxious effects as apoptosis, necrosis and DNA damage by the induction of reactive oxygen species production. Such effects extremely change the biology of the cells. For example, in an experiment with phagocytosis and intracellular traffic, apoptotic cells present a deficient phagocytose process which can infer misunderstand able results [39].

To investigate the true cause of the cytotoxic effect of cadmium chalcogenides QDs, we synthesized CdSe MSQDs with different amounts of Cd2+ adsorbed on their surface and have shown that this quantity is directly related to cytotoxicity (**Figure 3 a,b**). The biocompatibility is increased with decrease of Cd2+ adsorbed on MSQDs surface (**Figure 3b**). In addition, the decrease of Cd2+ is confirmed by the lower expression of the protein (**Figure 3c**). Thus, based on this, we developed new synthesis methodologies to develop a CdS shell using the Cd2+ adsorbed [45, 46]. Thus, we have shown in our recent studies that this shell increases biocom-

**Figure 4** shows fluorescence images of CdSe/CdSe MSQDs alone and bioconjugated Pepstatin A, BnSP-6, BthTx-II and a specific BC Fab antibody in the MDA-MB-23.1 [40, 41]. The fluorescence from MSQDs bioconjugated was detected inside the cells' nuclei compartment of MDA-MB-231. Notably, we verified that the MSQDs alone were not internalized in MDA-MB-231 (**Figure 4a**) [40].

migration since the monitoring could be done for days.

using the blue, green and red detection filters, respectively [39–41].

98 State of the Art in Nano-bioimaging

patibility and has no immunological effects [41].

**Figure 3.** (a) Representation of CdSe MSQDs with different amounts of Cd2+ adsorbed on their surface, (b) Viability in function of diminution of Cd2+ and (c) B-action mRNA fold/control in function of diminution of Cd2+ (increase of Se).

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and

101

S quantum dots for

**Figure 4.** Fluorescence images of (a) CdSe/CdSe MSQDs, bioconjugated (b) Pepstatin in 6 h after treatment, (c) BnSP-6 in 3 h after treatment, (d) BthTx-II in 3 h after treatment and (e) a specific BC Fab antibody in the MDA-MB-23.1 [40, 41].

This result confirms the bioconjugation of the MSQDs with biological probes and in addition, all the assays were performed at periods greater than 2 h, and visualization with no commercial dye would not be possible. Therefore, the group presents experience in the development of new biocompatible luminescent markers specific to each type of treatment.

#### **Author details**

Anielle Christine Almeida Silva<sup>1</sup> \*, Lucas Ian Veloso Correia<sup>2</sup> , Marcelo José Barbosa Silva<sup>3</sup> , Mariana Alves Pereira Zóia<sup>4</sup> , Fernanda Van Petten Vasconcelos Azevedo<sup>2</sup> , Jéssica Peixoto Rodrigues<sup>4</sup> , Luiz Ricardo Goulart<sup>4</sup> , Veridiana de Melo Ávila<sup>2</sup> and Noelio Oliveira Dantas1

\*Address all correspondence to: aniellechristineas@gmail.com

1 Laboratory of New Insulation and Semiconductor Materials, Institute of Physics, Federal University of Uberlândia, Brazil

2 Laboratory of Biochemistry and Animal Toxins, Institute of Genetics and Biochemistry, Federal University of Uberlândia, Brazil

3 Laboratory of Immunoparasitology, Institute of Biomedical Sciences, Federal University of Uberlândia, Brazil

4 Laboratory of Nanobiotechnology, Institute of Genetics and Biochemistry, Federal University of Uberlândia, Brazil

#### **References**

This result confirms the bioconjugation of the MSQDs with biological probes and in addition, all the assays were performed at periods greater than 2 h, and visualization with no commercial dye would not be possible. Therefore, the group presents experience in the development

**Figure 4.** Fluorescence images of (a) CdSe/CdSe MSQDs, bioconjugated (b) Pepstatin in 6 h after treatment, (c) BnSP-6 in 3 h after treatment, (d) BthTx-II in 3 h after treatment and (e) a specific BC Fab antibody in the MDA-MB-23.1 [40, 41].

\*, Lucas Ian Veloso Correia<sup>2</sup>

1 Laboratory of New Insulation and Semiconductor Materials, Institute of Physics, Federal

2 Laboratory of Biochemistry and Animal Toxins, Institute of Genetics and Biochemistry,

4 Laboratory of Nanobiotechnology, Institute of Genetics and Biochemistry, Federal

3 Laboratory of Immunoparasitology, Institute of Biomedical Sciences, Federal University of

, Fernanda Van Petten Vasconcelos Azevedo<sup>2</sup>

, Marcelo José Barbosa Silva<sup>3</sup>

and

,

, Veridiana de Melo Ávila<sup>2</sup>

,

of new biocompatible luminescent markers specific to each type of treatment.

, Luiz Ricardo Goulart<sup>4</sup>

\*Address all correspondence to: aniellechristineas@gmail.com

**Author details**

100 State of the Art in Nano-bioimaging

Anielle Christine Almeida Silva<sup>1</sup>

University of Uberlândia, Brazil

University of Uberlândia, Brazil

Federal University of Uberlândia, Brazil

Mariana Alves Pereira Zóia<sup>4</sup>

Jéssica Peixoto Rodrigues<sup>4</sup>

Noelio Oliveira Dantas1

Uberlândia, Brazil


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2014;**8**(2):1913-1922

## *Edited by Morteza Sasani Ghamsari*

*Nano-bioimaging* is a real-time observation method for the study of biological processes in subcellular structures and entire cells. This technique aims to interfere as little as possible with life processes using nanoscale materials and probes. In this method, nanoscale photon source is often used for imaging, and 3D structure of the observed specimen is studied in detail without physical interference. Over the last decade, further boost in bioimaging has led to increase the nano-bioimaging impact that includes many improvements in the data analysis method, image processing, and molecular imaging technology. However, to increase the usage of nano-bioimaging, several developments in the field of diagnosis accuracy, photobleaching prevention, and controlling of the fluorescence resonance energy transfer (FRET) must be achieved. The purpose of this book is to provide a perspective on the current status of nano-bioimaging technologies.

Published in London, UK © 2018 IntechOpen © sakkmesterke / iStock

State of the Art in Nano-bioimaging

State of the Art in

Nano-bioimaging