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Introduction: Visual assessment of endomyocardial biopsy (EMB) specimens may result in errors due to the human factor and inability to obtain quantitative data on the intensity of immunohistochemical (IHC) reactions and severity of pathological changes in the heart transplant. Detailed digital characterization of EMB specimens based on automated or semi-automated computer-assisted morphometry improves the diagnostic accuracy of EMB. Objective: To develop a method of and algorithms for digital computer-assisted analysis of EMB specimens to quantify pathomorphological and immunophenotypic changes in the myocardium of patients with various types and grades of heart transplant rejection. Materials and methods: We studied 257 EMB specimens from 56 heart transplant recipients at Scientific Research Institute – Ochapovsky Regional Clinical Hospital No. 1 (Krasnodar, Russian Federation). Sections were stained with hematoxylin and eosin. We used the streptavidin-biotin method to determine the CD68 expression and computer-assisted morphometry of digital images to measure the area of pathological changes and CD68 expression. Results: When developing a method for computer-assisted analysis of EMB specimens, we proposed a new evaluation criterion: staining area coefficient (%) that is a ratio of the total stained area to the total section area. We created and field-tested algorithms for digital morphometric analysis to assess the intensity of IHC reactions and to identify the relative area of pathological changes in the EBM specimens. Conclusions: New digital criteria for diagnosing heart transplant rejections are to improve the accuracy of EMB results interpretation, but can also be used for analyzing other biopsy specimens.
Introduction: Visual assessment of endomyocardial biopsy (EMB) specimens may result in errors due to the human factor and inability to obtain quantitative data on the intensity of immunohistochemical (IHC) reactions and severity of pathological changes in the heart transplant. Detailed digital characterization of EMB specimens based on automated or semi-automated computer-assisted morphometry improves the diagnostic accuracy of EMB. Objective: To develop a method of and algorithms for digital computer-assisted analysis of EMB specimens to quantify pathomorphological and immunophenotypic changes in the myocardium of patients with various types and grades of heart transplant rejection. Materials and methods: We studied 257 EMB specimens from 56 heart transplant recipients at Scientific Research Institute – Ochapovsky Regional Clinical Hospital No. 1 (Krasnodar, Russian Federation). Sections were stained with hematoxylin and eosin. We used the streptavidin-biotin method to determine the CD68 expression and computer-assisted morphometry of digital images to measure the area of pathological changes and CD68 expression. Results: When developing a method for computer-assisted analysis of EMB specimens, we proposed a new evaluation criterion: staining area coefficient (%) that is a ratio of the total stained area to the total section area. We created and field-tested algorithms for digital morphometric analysis to assess the intensity of IHC reactions and to identify the relative area of pathological changes in the EBM specimens. Conclusions: New digital criteria for diagnosing heart transplant rejections are to improve the accuracy of EMB results interpretation, but can also be used for analyzing other biopsy specimens.
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