Phase-contrast CT Research Articles

Multiscale X-ray phase-contrast CT uncovers adaptive changes and compensatory mechanisms of circulatory pathways during acute liver injury

Intrahepatic circulation is essential for the repair of acute liver injury (ALI); however, very limited information is available concerning changes in the circulatory pathways during ALI. Therefore, multi-scale X-ray phase-contrast CT combined with three-dimensional (3D) visualization is used to quantitatively analyze the intrahepatic circulation pathway (including the hepatic vein, portal vein and hepatic sinusoid) in the mouse model via the intraperitoneal injection of carbon tetrachloride (CCl4) from acute injury to recovery. The results demonstrate that the liver still preserves some vessel-like channels accessed to the central vein when the injury causes the severe collapse of the hepatic sinusoids that cannot be observed in two-dimensional pathologic slices. Moreover, angiogenesis is observed in the terminal branches of the hepatic vein and portal vein. Additionally, we extend the two-dimensional primary lobule to a 3D model and find that the sinusoids in zone III have the most severe injury. The sinusoids in different zones also show changes in parameters such as density and mean diameter during the ALI. In conclusion, phase-contrast CT can reveal the intact vascular system within the liver lobes, thus providing critical information for studying the mechanisms involved in the evolution of circulatory structures from damage to repair.

Phase-contrast visualization of human tissues using superimposed wavefront imaging of diffraction-enhanced x-rays.

Phase-contrast computed tomography (CT) using high-brilliance, synchrotron-generated x-rays enable three-dimensional (3D) visualization of microanatomical structures within biological specimens, offering exceptionally high-contrast images of soft tissues. Traditional methods for phase-contrast CT; however, necessitate a gap between the subject and the x-ray camera, compromising spatial resolution due to penumbral blurring. Our newly developed technique, Superimposed Wavefront Imaging of Diffraction-enhanced x-rays (SWIDeX), leverages a Laue-case Si angle analyzer affixed to a scintillator to convert x-rays to visible light, capturing second-order differential phase contrast images and effectively eliminating the distance to the x-ray camera. This innovation achieves superior spatial resolution over conventional methods. In this paper, the imaging principle and CT reconstruction algorithm based on SWIDeX are presented in detail and compared with conventional analyzer-based imaging (ABI). It also shows the physical setup of SWIDeX that provides the resolution preserving second-order differential images for reconstruction. We compare the spatial resolution and the sensitivity of SWIDeX to conventional ABI. To demonstrate high-spatial resolution achievable by SWIDeX, the internal structures of four human tissues-ductal carcinoma in situ, normal stomach, normal pancreas, and intraductal papillary mucinous neoplasm of the pancreas-were visualized using an imaging system configured at the Photon Factory's BL14B beamline under the High Energy Accelerator Research Organization (KEK). Each tissue was thinly sliced after imaging, stained with hematoxylin and eosin (H&E) for conventional microscope-based pathology. A comparison of SWIDeX-CT and pathological images visually demonstrates the effectiveness of SWIDeX-CT for biological tissue imaging. SWIDeX could generate clearer 3D images than existing analyzer-based phase-contrast methods and accurately delineate tissue structures, as validated against histopathological images. SWIDeX can visualize important 3D structures in biological soft tissue with high spatial resolution and can be an important tool for providing information between the disparate scales of clinical and pathological imaging.

Automated segmentation of liver and hepatic vessels on portal venous phase computed tomography images using a deep learning algorithm.

CT-image segmentation for liver and hepatic vessels can facilitate liver surgical planning. However, time-consuming process and inter-observer variations of manual segmentation have limited wider application in clinical practice. Our study aimed to propose an automated deep learning (DL) segmentation algorithm for liver and hepatic vessels on portal venous phase CT images. This retrospective study was performed to develop a coarse-to-fine DL-based algorithm that was trained, validated, and tested using private 413, 52, and 50 portal venous phase CT images, respectively. Additionally, the performance of the DL algorithm was extensively evaluated and compared with manual segmentation using an independent clinical dataset of preoperative contrast-enhanced CT images from 44 patients with hepatic focal lesions. The accuracy of DL-based segmentation was quantitatively evaluated using the Dice Similarity Coefficient (DSC) and complementary metrics [Normalized Surface Dice (NSD) and Hausdorff distance_95 (HD95) for liver segmentation, Recall and Precision for hepatic vessel segmentation]. The processing time for DL and manual segmentation was also compared. Our DL algorithm achieved accurate liver segmentation with DSC of 0.98, NSD of 0.92, and HD95 of 1.52mm. DL-segmentation of hepatic veins, portal veins, and inferior vena cava attained DSC of 0.86, 0.89, and 0.94, respectively. Compared with the manual approach, the DL algorithm significantly outperformed with better segmentation results for both liver and hepatic vessels, with higher accuracy of liver and hepatic vessel segmentation (all p<0.001) in independent 44 clinical data. In addition, the DL method significantly reduced the manual processing time of clinical postprocessing (p<0.001). The proposed DL algorithm potentially enabled accurate and rapid segmentation for liver and hepatic vessels using portal venous phase contrast CT images.

Multiscale X-ray phase-contrast CT unveils the evolution of bile infarct in obstructive biliary disease

Bile infarct is a pivotal characteristic of obstructive biliary disease, but its evolution during the disease progression remains unclear. Our objective, therefore, is to explore morphological alterations of the bile infarct in the disease course by means of multiscale X-ray phase-contrast CT. Bile duct ligation is performed in mice to mimic the obstructive biliary disease. Intact liver lobes of the mice are scanned by phase-contrast CT at various resolution scales. Phase-contrast CT clearly presents three-dimensional (3D) images of the bile infarcts down to the submicron level with good correlation with histological images. The CT data illustrates that the infarct first appears on day 1 post-BDL, while a microchannel between the infarct and hepatic sinusoids is identified, the number of which increases with the disease progression. A 3D model of hepatic acinus is proposed, in which the infarct starts around the portal veins (zone I) and gradually progresses towards the central veins (zone III) during the disease process. Multiscale phase-contrast CT offers the comprehensive analysis of the evolutionary features of the bile infarct in obstructive biliary disease. During the course of the disease, the bile infarcts develop infarct-sinusoidal microchannels and gradually occupy the whole liver, promoting the disease progression.

Model-driven CT reconstruction algorithm for nano-resolution x-ray phase contrast imaging

Abstract The low-density imaging performance of a zone plate-based nano-resolution hard x-ray computed tomography (CT) system can be significantly improved by incorporating a grating-based Lau interferometer. Due to the diffraction, however, the acquired nano-resolution phase signal may suffer splitting problem, which impedes the direct reconstruction of phase contrast CT (nPCT) images. To overcome, a new model-driven nPCT image reconstruction algorithm is developed in this study. In it, the diffraction procedure is mathematically modeled into a matrix B , from which the projections without signal splitting can be generated invertedly. Furthermore, a penalized weighted least-square model with total variation (PWLS-TV) is employed to denoise these projections, from which nPCT images with high accuracy are directly reconstructed. Numerical experiments demonstrate that this new algorithm is able to work with phase projections having any splitting distances. Moreover, results also reveal that nPCT images of higher signal-to-noise-ratio (SNR) could be reconstructed from projections having larger splitting distances. In summary, a novel model-driven nPCT image reconstruction algorithm with high accuracy and robustness is verified for the Lau interferometer-based hard x-ray nano-resolution phase contrast imaging.

Detection of early pulmonary emphysema by multi-contrast x-ray Talbot-Lau interferometer.

Pulmonary emphysema is a part of chronic obstructive pulmonary disease, which is an irreversible chronic respiratory disease. In order to avoid further damage to lung tissue, early diagnosis and treatment of pulmonary emphysema is essential. Early pulmonary emphysema diagnosis is difficult with conventional radiographic imaging. Recently, x-ray phase contrast imaging has proved to be an effective and promising imaging strategy for soft tissue, due to its high sensitivity and multi-contrast. The aim of this study is to diagnose pulmonary emphysema early utilizing an x-ray Talbot-Lau interferometer (TLI). We successfully established the mouse model of emphysema by porcine pancreatic elastase treatment, and then used the established x-ray TLI to perform imaging experiments on the mice with different treatment time. The traditional absorption CT and phase contrast CT were obtained simultaneously through TLI. The CT results and histopathology of mice lung in different treatment time were quantitatively analyzed. By imaging mice lungs, it can be found that phase contrast has higher sensitivity than absorption contrast in early pulmonary emphysema. The results show that the phase contrast signal could distinguish the pulmonary emphysema earlier than the conventional attenuation signal, which can be consistent with histological images. Through the quantitative analysis of pathological section and phase contrast CT, it can be found that there is a strong linear correlation. In this study, we quantitatively analyze mean linear intercept of histological sections and CT values of mice. The results show that the phase contrast signal has higher imaging sensitivity than the attenuation signal. X-ray TLI multi-contrast imaging is proved as a potential diagnostic method for early pulmonary emphysema in mice.

Obliteration of portal venules contributes to portal hypertension in biliary cirrhosis.

The effects of the obliteration of portal venules (OPV) in cirrhotic portal hypertension are poorly understood. To investigate its contribution to portal hypertension in biliary cirrhosis and its underlying mechanism,we evaluated OPV using two-dimensional (2D) histopathology in liver explants from patients with biliary atresia (BA, n = 63), primary biliary cholangitis (PBC, n = 18), and hepatitis B-related cirrhosis (Hep-B-cirrhosis, n = 35). Then, three-dimensional (3D) OPV was measured by X-ray phase-contrast CT in two parallel models in rats following bile duct ligation (BDL) or carbon tetrachloride (CCl4) administration, representing biliary cirrhosis and post-necrotic cirrhosis, respectively. The portal pressure was also measured in the two models. Finally, the effects of proliferative bile ducts on OPV were investigated. We found that OPV was significantly more frequent in patients with biliary cirrhosis, including BA (78.57 ± 16.45%) and PBC (60.00 ± 17.15%), than that in Hep-B-cirrhotic patients (29.43 ± 14.94%, p < 0.001). OPV occurred earlier, evidenced by the paired liver biopsy at a Kasai procedure (KP), and was irreversible even after a successful KP in the patients with BA. OPV was also significantly more frequent in the BDL models than in the CCl4 models, as shown by 2D and 3D quantitative analysis. Portal pressure was significantly higher in the BDL model than that in the CCl4 model. With the proliferation of bile ducts, portal venules were compressed and irreversibly occluded, contributing to the earlier and higher portal pressure in biliary cirrhosis. OPV, as a pre-sinusoidal component, plays a key role in the pathogenesis of portal hypertension in biliary cirrhosis. The proliferated bile ducts and ductules gradually take up the 'territory' originally attributed to portal venules and compress the portal venules, which may lead to OPV in biliary cirrhosis. © 2024 The Pathological Society of Great Britain and Ireland.

Abstract 2585: First in human study with a novel peptide binder to glypican-3, demonstrates high specificity as a PET imaging agent in patients with hepatocellular carcinoma

Abstract Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. The American Association for the Study of Liver Disease recommends surveillance for high-risk individuals with abdominal ultrasound, triple phase contrast CT or MRI. However, these imaging techniques have limited sensitivity in classifying lesions smaller than 2 centimeters. The use of [18F]FDG Positron Emission Tomography (PET) is constrained due to insufficient uptake by HCC lesions over background liver uptake. Hence, there is an urgent need for more precise radiotracers for HCC. This study introduces the development of a novel radiotracer that binds to glypican-3 (GPC3), a cell membrane-anchored oncofetal protein overexpressed in HCC with minimal normal tissue expression. Methods: [68Ga]Ga-RYZ-GPC3 is composed of a small macrocyclic peptide binder with high affinity to GPC3 linked with a tetraxetan moiety capable of chelating a variety of radioisotopes including positron-emitting 68Ga and other radiometals. The unlabeled binder to GPC3 was synthesized by the sponsor and provided to three imaging centers in India as part of investigator-initiated trials reviewed and approved by each site’s institutional review board and ethics committee. Labeling with 68Ga and quality checks of the product was performed locally at each center. Patients with high clinical suspicion or with confirmed HCC who gave informed consent received injections of 1.5-5.5 mCi of [68Ga]Ga-RYZ-GPC3 and underwent PET-CT scanning at predetermined intervals. Some patients underwent companion [18F]FDG PET-CT scans in accordance with local guidelines. Results: A total of 64 patients underwent [68Ga]Ga-RYZ-GPC3 PET-CT scans. The median age within the cohort was 61 (41-83), 22% were female. Liver cirrhosis was present in 72% of patients, attributed to hepatitis B, hepatitis C or NASH in 17%, 13% and 20% of cases. Notably, 92% of patients exhibited at least one positive lesion on [68Ga]Ga-RYZ-GPC3 scans. The median SUVmax of GPC3-avid liver lesions was 15.5 (range 1.1 to 137.0) while the median liver SUVmean was 1.6 (0.3-7.9). Physiologic uptake was predominantly observed in the kidneys, the primary route of clearance, with a median SUVmean of 10.9 (2.2-20.7). Additionally, 20 patients underwent [18F]FDG PET-CT scan for comparison. The median SUVmax of lesions on 68Ga-RYZ-GPC3 vs [18F]FDG PET was 11.0 (1.1-137.0) vs 3.8 (1.2-12.2). Conclusion: Early human imaging results in patients with HCC indicate that [68Ga]Ga-RYZ-GPC3 has high tumor lesion specificity compared to normal liverand demonstrates the potential of [68Ga]Ga-RYZ-GPC3 to improve detection of HCC over conventional [18F]FDG PET-CT. In addition, the binder could be complexed with a therapeutic radioisotope as a novel targeted therapeutic option for HCC. Further investigation of this first-in-class binder to HCC is warranted. Citation Format: Chandresakhar Bal, Sanjana Ballal, Kumar Kallur, Anna Karmann, Ye Yuan, Jessica Rearden, Kathryn Shah, Charlotte Lorenz, Susan Moran, Ken Song, Ishita Sen. First in human study with a novel peptide binder to glypican-3, demonstrates high specificity as a PET imaging agent in patients with hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2585.

In vivo low-dose phase-contrast CT for quantification of functional and anatomical alterations in lungs of an experimental allergic airway disease mouse model.

Synchrotron-based propagation-based imaging (PBI) is ideally suited for lung imaging and has successfully been applied in a variety of in vivo small animal studies. Virtually all these experiments were tailored to achieve extremely high spatial resolution close to the alveolar level while delivering high x-ray doses that would not permit longitudinal studies. However, the main rationale for performing lung imaging studies in vivo in small animal models is the ability to follow disease progression or monitor treatment response in the same animal over time. Thus, an in vivo imaging strategy should ideally allow performing longitudinal studies. Here, we demonstrate our findings of using PBI-based planar and CT imaging with two different detectors-MÖNCH 0.3 direct conversion detector and a complementary metal-oxide-semiconductor (CMOS) detector (Photonics Science)-in an Ovalbumin induced experimental allergic airway disease mouse model in comparison with healthy controls. The mice were imaged free breathing under isoflurane anesthesia. At x-ray dose levels below those once used by commercial small animal CT devices at similar spatial resolutions, we were able to resolve structural changes at a pixel size down to 25 μm and demonstrate the reduction in elastic recoil in the asthmatic mice in cinematic planar x-ray imaging with a frame rate of up to 100 fps. Thus, we believe that our approach will permit longitudinal small animal lung disease studies, closely following the mice over longer time spans.

Analyzer-free hard x-ray interferometry

Objective. To enable practical interferometry-based phase contrast CT using standard incoherent x-ray sources, we propose an imaging system where the analyzer grating is replaced by a high-resolution detector. Since there is no need to perform multiple exposures (with the analyzer grating at different positions) at each scan angle, this scheme is compatible with continuous-rotation CT apparatus, and has the potential to reduce patient radiation dose and patient motion artifacts. Approach. Grating-based x-ray interferometry is a well-studied technique for imaging soft tissues and highly scattering objects embedded in such tissues. In addition to the traditional x-ray absorption-based image, this technique allows reconstruction of the object phase and small-angle scattering information. When using conventional incoherent, polychromatic, hard x-ray tubes as sources, three gratings are usually employed. To sufficiently resolve the pattern generated in these interferometers with contemporary x-ray detectors, an analyzer grating is used, and consequently multiple images need to be acquired for each view angle. This adds complexity to the imaging system, slows image acquisition and thus increases sensitivity to patient motion, and is not dose efficient. By simulating image formation based on wave propagation, and proposing a novel phase retrieval algorithm based on a virtual grating, we assess the potential of a analyzer-grating-free system to overcome these limitations. Main results. We demonstrate that the removal of the analyzer-grating can produce equal image contrast-to-noise ratio at reduced dose (by a factor of 5), without prolonging scan duration. Significance. By demonstrating that an analyzer-free CT system, in conjuction with an efficient phase retrieval algorithm, can overcome the prohibitive dose and workflow penalties associated grating-stepping, an alternative path towards realizing clinical inteferometric CT appears possible.

Experimental Approach for Clarifying Initiation and Growth Behaviors of Internal Fatigue Cracks Using Synchrotron Radiation Multiscale X-ray Computed Tomography

Abstract The very high cycle fatigue (VHCF) phenomenon has been recognized and extensively studied in the past quarter century. One of the most peculiar and noticeable characteristics of VHCF is the transition of the origin site from the surface to the interior of the material in long-life regimes over 107 cycles. In particular, in high-strength metals, a tiny site can become an origin of internal fatigue cracks, such as nonmetallic inclusions of several micrometers to several tens of micrometers in high-strength steels and crystal grains of several tens of micrometers in titanium alloys. However, such small cracks are difficult to detect using conventional nondestructive approaches, such as industrial X-ray computed tomography (CT) or ultrasonic CT. Given this background, we have attempted to use a synchrotron radiation multiscale X-ray CT provided by SPring-8 in Japan. This system comprises a projection CT (micro-CT) with a spatial resolution of approximately 1 μm and a phase-contrast imaging CT (nano-CT) with a spatial resolution of approximately 200 nm or higher. The present study introduces our experimental approach to clarify internal fatigue crack behaviors using the multiscale X-ray CT with in situ fatigue testing. First, the principle of material selection focusing on the VHCF study is explained with the details of the materials used: (α+β) type Ti-6Al-4V, β type Ti-22V-4Al, and 17-4 precipitation-hardened martensite stainless steel. Afterward, the outline and primary performance of the multiscale X-ray CT are described. Subsequently, important points in conducting accurate in situ fatigue tests are discussed from the viewpoints of the development policies of the testing system and preparation of the special thin specimen for CT imaging. Finally, the multiscale X-ray CT is conducted for the above materials, and the initiation and growth behaviors of the internal fatigue cracks are compared and discussed for an in-depth understanding of the VHCF phenomenon.

Sparse2Noise: Low-dose synchrotron X-ray tomography without high-quality reference data

BackgroundSynchrotron radiation computed tomography (SR-CT) holds promise for high-resolution in vivo imaging. Notably, the reconstruction of SR-CT images necessitates a large set of data to be captured with sufficient photons from multiple angles, resulting in high radiation dose received by the object. Reducing the number of projections and/or photon flux is a straightforward means to lessen the radiation dose, however, compromises data completeness, thus introducing noises and artifacts. Deep learning (DL)-based supervised methods effectively denoise and remove artifacts, but they heavily depend on high-quality paired data acquired at high doses. Although algorithms exist for training without high-quality references, they struggle to effectively eliminate persistent artifacts present in real-world data. MethodsThis work presents a novel low-dose imaging strategy namely Sparse2Noise, which combines the reconstruction data from paired sparse-view CT scan (normal-flux) and full-view CT scan (low-flux) using a convolutional neural network (CNN). Sparse2Noise does not require high-quality reconstructed data as references and allows for fresh training on data with very small size. Sparse2Noise was evaluated by both simulated and experimental data. ResultsSparse2Noise effectively reduces noise and ring artifacts while maintaining high image quality, outperforming state-of-the-art image denoising methods at same dose levels. Furthermore, Sparse2Noise produces impressive high image quality for ex vivo rat hindlimb imaging with the acceptable low radiation dose (i.e., 0.5 Gy with the isotropic voxel size of 26 μm). ConclusionsThis work represents a significant advance towards in vivo SR-CT imaging. It is noteworthy that Sparse2Noise can also be used for denoising in conventional CT and/or phase-contrast CT.

SIMPLE PHYSICAL PRINCIPLES AND MEDICAL USES OF COMPUTED TOMOGRAPHY (CT) SCAN A NEW ASSESSMENT

The development of X-ray computed tomography (CT) has been founded on the discovery of X-rays, the inception of the Radon transform, and the growth of X-ray digital data acquisition systems and computer knowledge. Dissimilar conventional X-ray imaging (general radiography), CT reconstructs cross-sectional anatomical images of the internal structures according to X-ray attenuation co-efficients (approximate tissue density) for almost every region in the body. This articleappraisals the essential physical principles and practical aspects of the CT scanner, including numerous notable evolutions in CT technology that resulted in the appearance of helical, multidetector, cone beam, portable, dual-energy, and phase-contrast CT, in integrated imaging modalities, such as positronemission- tomography一CT and single-photon-emission-computed-tomography-CT, and in clinical applications, including image acquisition parameters, CT angiography, image adjustment, versatile image visualizations, volumetric/surface rendering on a computer workstation, radiation treatment planning, and target localization in radiotherapy. The understanding of CT characteristics will provide more effective and accurate patient care in the fields of diagnostics and radiotherapy, and can lead to the improvement of image quality and the optimization of exposure doses.

Retracted: Study on the Cytotoxic Microstructure of Titanium Dioxide Nanoparticles by X-Ray Phase-Contrast CT Imaging.

[This retracts the article DOI: 10.1155/2022/2413922.].

A deep learning reconstruction framework for low dose phase contrast computed tomography via inter-contrast enhancement

Phase contrast computed tomography (PCCT) offers excellent imaging contrast on soft tissue while it generate absorption, phase and dark-field contrast tomographic images. It has shown a great potential in clinical diagnosis. However, existing PCCT methods require high radiation doses. Reducing tube current is a universal low dose approach while it will introduce quantum noise in projections. In this paper, we report a deep learning (DL) framework for low dose PCCT based on inter-contrast enhancement. It utilizes the multi-contrast feature of PCCT and the varying effects of noise on each contrast. The missing structure in the contrasts that are more affected by noise can be recovered by those that are less affected. Considering the grating-based PCCT as example, the proposed framework is validated with experiments and a dramatic quality improvement of multi-contrast tomographic images has been obtained. This study shows potential of DL techniques in the field of low dose PCCT.

Towards virtual histology with X-ray grating interferometry

Breast cancer is the most common type of cancer worldwide. Diagnosing breast cancer relies on clinical examination, imaging and biopsy. A core-needle biopsy enables a morphological and biochemical characterization of the cancer and is considered the gold standard for breast cancer diagnosis. A histopathological examination uses high-resolution microscopes with outstanding contrast in the 2D plane, but the spatial resolution in the third, Z-direction, is reduced. In the present paper, we propose two high-resolution table-top systems for phase-contrast X-ray tomography of soft-tissue samples. The first system implements a classical Talbot–Lau interferometer and allows to perform ex-vivo imaging of human breast samples with a voxel size of 5.57 μm. The second system with a comparable voxel size relies on a Sigray MAAST X-ray source with structured anode. For the first time, we demonstrate the applicability of the latter to perform X-ray imaging of human breast specimens with ductal carcinoma in-situ. We assessed image quality of both setups and compared it to histology. We showed that both setups made it possible to target internal features of breast specimens with better resolution and contrast than previously achieved, demonstrating that grating-based phase-contrast X-ray CT could be a complementary tool for clinical histopathology.

Learning from Projection to Reconstruction: A Deep Learning Reconstruction Framework for Sparse-View Phase Contrast Computed Tomography via Dual-Domain Enhancement

Phase contrast computed tomography (PCCT) provides an effective non-destructive testing tool for weak absorption objects. Limited by the phase stepping principle and radiation dose requirement, sparse-view sampling is usually performed in PCCT, introducing severe artifacts in reconstruction. In this paper, we report a dual-domain (i.e., the projection sinogram domain and image domain) enhancement framework based on deep learning (DL) for PCCT with sparse-view projections. It consists of two convolutional neural networks (CNN) in dual domains and the phase contrast Radon inversion layer (PCRIL) to connect them. PCRIL can achieve PCCT reconstruction, and it allows the gradients to backpropagate from the image domain to the projection sinogram domain while training. Therefore, parameters of CNNs in dual domains are updated simultaneously. It could overcome the limitations that the enhancement in the image domain causes blurred images and the enhancement in the projection sinogram domain introduces unpredictable artifacts. Considering the grating-based PCCT as an example, the proposed framework is validated and demonstrated with experiments of the simulated datasets and experimental datasets. This work can generate high-quality PCCT images with given incomplete projections and has the potential to push the applications of PCCT techniques in the field of composite imaging and biomedical imaging.

Phase Retrieval-Based Phase-Contrast Imaging and CT of Living Zebrafish.

Zebrafish are widely used as experimental animal models. They are small and move fast in the water. Real-time imaging of fast-moving zebrafish is a challenge, and it requires that the imaging technique has higher spatiotemporal resolution and penetration ability. The purpose of this study was to evaluate the feasibility of dynamic phase retrieval (PR)-based phase-contrast imaging (PCI) for real-time displaying of the breathing and swimming process in unanesthetized free-moving zebrafish, and to evaluate the feasibility of PR-based phase-contrast CT (PCCT) for visualizing the soft tissues in anesthetized living zebrafish. PR was performed using the phase-attenuation duality (PAD) method with the δ/β values (PAD property) of 100 and 1000 for dynamic PR-based PCI and PR-based PCCT, respectively. The contrast-to-noise ratio (CNR) was used for quantitatively assessing the visibility of the adipose tissue and muscle tissue. The skeleton and swim bladder chambers in fast-moving zebrafish were clearly shown. The dynamic processes of breathing and swimming were visibly recorded. The respiratory intensity and frequency and the movement flexibility of the zebrafish could be dynamically evaluated. By producing more obvious image contrast, PR-based PCCT clearly showed the adipose tissue and muscle tissue. The CNRs from PR-based PCCT were significantly higher than those from PR-free PCCT for both adipose tissue (9.256 ± 2.037 vs. 0.429 ± 0.426, p < 0.0001) and muscle tissue (7.095 ± 1.443 vs. 0.324 ± 0.267, p < 0.0001). Dynamic PR-based PCI holds the potential for investigating both morphological abnormalities and motor disorders. PR-based PCCT offers clear visualization and the potential for quantification of soft tissues in living zebrafish.

Novel setup for rapid phase contrast CT imaging of heavy and bulky specimens.

This work introduces a novel setup for computed tomography of heavy and bulky specimens at the SYRMEP beamline of the Italian synchrotron Elettra. All the key features of the setup are described and the first application to off-center computed tomography scanning of a human chest phantom (approximately 45 kg) as well as the first results for vertical helical acquisitions arediscussed.

Reduced volume of diabetic pancreatic islets in rodents detected by synchrotron X-ray phase-contrast microtomography and deep learning network

The pancreatic islet is a highly structured micro-organ that produces insulin in response to rising blood glucose. Here we develop a label-free and automatic imaging approach to visualize the islets in situ in diabetic rodents by the synchrotron radiation X-ray phase-contrast microtomography (SRμCT) at the ID17 station of the European Synchrotron Radiation Facility. The large-size images (3.2mm×15.97mm) were acquired in the pancreas in STZ-treated mice and diabetic GK rats. Each pancreas was dissected by 3000 reconstructed images. The image datasets were further analysed by a self-developed deep learning method, AA-Net. All islets in the pancreas were segmented and visualized by the three-dimension (3D) reconstruction. After quantifying the volumes of the islets, we found that the number of larger islets (=>1500 μm3) was reduced by 2-fold (wt 1004±94 vs GK 419±122, P<0.001) in chronically developed diabetic GK rat, while in STZ-treated diabetic mouse the large islets were decreased by half (189±33 vs 90±29, P<0.001) compared to the untreated mice. Our study provides a label-free tool for detecting and quantifying pancreatic islets in situ. It implies the possibility of monitoring the state of pancreatic islets in vivo diabetes without labelling.