The Study Of X-ray Phase Contrast Imaging And Its Application On Microstructure Visualization Of Hepatocellular Carcinoma

X-ray phase-contrast imaging (PCI) is a new emerging imaging technique which generates high spatial resolution and super contrast of biological soft tissues compared to conventional radiography, and can clearly display the inner details and micro-structures of biological soft tissues. In recent years, PCI technique has also been introduced into X-ray computed tomography (CT). PCI-CT can provide substantially enhanced contrast in combination with the PCI advantage, promising to provide high-resolution micro-CT images, especially for soft tissues. In addition, combining the three dimensional (3D) visualization technique, PCI-CT can acquire3D morphology of inner microstructures in biomedical samples without contrast agents. In this subject, high-quality images and clear3D microstructures of the samples are presented by means of the information extraction and CT reconstruction based on the PCI technique. The subject aims to enrich and deepen the theory and method of PCI, and explore a new way for PCI and its image processing in the biomedical application.As main PCI techniques, diffraction enhanced imaging (DEI) and in-line phase-contrast imaging (ILPCI) have been widely studied and applied by scientists in many fields. The DEI and ILPCI experiments are performed at the4W1A beamline of the Beijing synchrotron radiation facility (BSRF) and X-ray imaging and biomedical application beamline (BL13W1) of Shanghai Synchrotron Radiation Facility (SSRF), respectively. In this study, the quantitative information extraction method in DEI is first studied. Then, high-resolution micro-CT images of the human hepatocellular carcinoma (HCC) tissues are obtained using ILPCI-CT, and the corresponding3D microstructures of the HCC tissues are reconstructed. Finally, the anatomical and pathological features of the HCC tissues are further studied by combining the histological sections. The main research contents are as follows:1. DEI derives contrast from an object’s X-ray absorption, refraction and ultra-small angle X-ray scattering (USAXS) properties. The separation of different contrast contributions from images is an important issue for potential application of DEI. In this paper, an improved DEI (IDEI) method is proposed based on the Gaussian curve fitting of the rocking curve (RC). Utilizing only three images in input, IDEI method can accurately separate the contrasts from absorption, refraction and USAXS produced by the object. IDEI method can be viewed as an improvement on the extended DEI (EDEI) method. In contrast, The IDEI method can well circumvent the limitations of the EDEI method since it does not impose a Taylor approximation to the RC. Moreover, compared with the multiple image radiography (MIR) method, the IDEI method needs only three images, which is definitely an advantage in the reduction of acquisition time and the dose delivered to the sample. Additionally, the analysis of IDEI model errors is performed to further investigate the factors that lead to the image artifacts. Finally, the validation studies are conducted by use of computer simulated and synchrotron experiment data.2. ILPCI-CT technique is utilized to obtain the CT image and3D microvasculature morphology of the HCC tissues, and the corresponding analysis is performed by combining the histological sections. In addition, for biological soft tissues, the expression between the density and refractive index decrement is inferred by combining the ILPCI-CT technique with phase retrieval algorithm, which provides the density distribution of soft tissues. The CT image and3D structure of the microvasculature in the HCC tissues are used to differentiate between the cancer embolus and thrombus based on the difference of their density distributions.3.3D trabecular microstructures from differently differentiated HCC tissues are presented and analyzed. Firstly, ILPCI-CT is utilized to obtain the CT images of the HCC tissues, and the correspondence between CT image and histopathological sections is confirmed, which highlights the high degree of sensitivity of ILPCI-CT technique. Secondly, for the trabecular spacing with no blood in the HCC tissues, the microstructures of hepatic sinusoids are presented using ILPCI-CT. According to the spatial relation between the hepatic sinusoid and trabecular spacing, some valuable quantitative assessments in differently differentiated HCC tissues, including the trabecular spacing distance and specific surface area, are performed, and they characterize anatomical properties and pathological features of differently differentiated HCC tissues. Finally,3D texture analysis is used to study the trabecular microstructures of the HCC tissues when the trabecular spacing in the HCC tissue is full of bloods. The research demonstrates that the texture measurements of the energy, inertia, sum average, and sum entropy can clearly distinguish3D texture features of trabecular microstructures from differently differentiated HCC tissues.