Journal of Peking University(Health Sciences) ›› 2018, Vol. 50 ›› Issue (5): 899-904. doi: 10.19723/j.issn.1671-167X.2018.05.023

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Investigation on diagnosing hepatic fibrosis with X-ray diffraction-enhanced imaging

WANG Ming, LI Hui△, WANG Jing, GAO Song   

  1. (Department of Medical Physics, Peking University Institute of Medical Humanities, Beijing 100191, China)
  • Online:2018-10-18 Published:2018-10-18
  • Contact: LI Hui E-mail:wllihui@bjmu.edu.cn
  • Supported by:
    Supported by the National Natural Science Foundation of China (61671026) and Beijing Natural Science Foundation (7142084)

Abstract: Objective: X-ray diffraction-enhanced imaging (DEI) method was used to image hepatic fibrous samples, and the texture measurements based on DEI images were calculated and analyzed for investigating the feasibility of diagnosing fibrosis quantitatively. Methods: Hepatic fibrosis of different severity in ICR mice was induced by injecting with carbon tetrachloride (CCl4) olive oil solution for 21 d, 42 d and 84 d, respectively. The excised liver tissues were then imaged at the 4W1A Topography & Imaging Station of Beijing Synchrotron Radiation Facility (BSRF). After imaging, the liver tissues were sectioned and stained for Masson trichrome using standard histological techniques. The imaging features of hepatic fibrosis of different severity were analyzed by comparing DEI images with histological examinations. The nine basic texture parameters on regions of interest (ROIs) of DEI images were extracted based on the gray level co-occurrence matrix (GLCM), and then evaluated for their feasibility to distinguish stages of fibrosis. Results: The results showed that great differences could be observed in the DEI images between the normal and diseased mice in different stages of liver fibrosis. It was demonstrated that there were six texture measurements (entropy, inertia, difference entropy, difference average increase, energy and inverse difference moment) that could distinguish between the normal and diseased mice in different stages of liver fibrosis (P<0.05). The texture parameters of entropy, inertia, difference entropy, difference average increased with the development of fibrosis, while the texture parameters of energy and inverse difference moment decreased with the development of fibrosis. The variation in entropy of different severity of fibrosis was most obvious among the six texture features. Conclusion: The degree of hepatic fibrosis can be discriminated by morphological features in DEI images. Moreover, the degree of hepatic fibrosis can be graded quantitatively by the texture features. These results suggest that DEI can be a promising noninvasive technique to diagnose and distinguish hepatic fibrosis of different degrees.

Key words: Liver cirrhosis, experimental, X-ray diffraction, Radiographic image enhancement, Early diagnosis, Pathology

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