USE OF MODERN TOOLS OF DIGITAL PATHOLOGY IN THE DIAGNOSIS OF HEPATITIS
DOI:
https://doi.org/10.11603/mie.1996-1960.2024.1-2.14893Keywords:
hepatitis , non-alcoholic steatohepatitis, metabolic fatty liver disease, liver fibrosis , mac- rophages, T-lymphocytes, METAVIR, image management system, computer modelAbstract
Background. In this work, the issues of using modern available tools of digital pathology (primarily open-source software) were considered, which can facilitate the work of the pathologist in the mor- phological diagnosis of hepatitis of various genesis and metabolic fatty liver disease. The purpose of the work was to adapt available software and develop separate modules for building an image man- agement system and analyzing them to establish morphological criteria for the development of liver fibrosis according to the METAVIR index based on the study of the role of different subpopulations of liver macrophages, sinusoidal endothelial cells and fibroblasts.
Materials and methods. Results. The main task was to analyze the available software, as well as to develop or refine its individual modules for building an image management system, viewing digital scans of micropreparations and simplifying the evaluation of the expression of immunohistochemical markers CD3, CD68, CD163, CD34 and α-SMA with the ultimate goal of simplifying the study of the role of different subpopulations of liver macrophages, sinusoidal endothelial cells and fibroblasts in progressive liver diseases and the development of fibrosis.
Conclusions. Based on the results of the work, it was established the possibility of developing software to study the number and ratio of different populations of macrophage cells, sinusoidal endo- thelial cells, fibroblasts and lymphocytes in liver tissue using open-source software. The software de- veloped and improved by us made it possible to create a convenient array of data from digital scans of micropreparations of liver tissues, with accelerated and convenient access to relevant data. The computer model created by us for recognizing and counting populations of liver cells with a positive and negative IGH reaction with monoclonal antibodies to CD3, CD34, CD68, CD163, α-SMA shows a certain difference with the reference assessment by a pathologist, but a statistically significant difference no differences were found between the results of the created model and the reference results. In the future, it is necessary to improve the developed model to increase its sensitivity in the sense of recognizing cells of a specific type.
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