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Quantitative analysis of histopathological findings using image processing software

In evaluating pathological changes in drug efficacy and toxicity studies, morphometric analysis can be quite robust. In this experiment, we examined whether morphometric changes of major pathological findings in various tissue specimens stained with hematoxylin and eosin could be recognized and quan...

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Autores principales: Horai, Yasushi, Kakimoto, Tetsuhiro, Takemoto, Kana, Tanaka, Masaharu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society of Toxicologic Pathology 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5660959/
https://www.ncbi.nlm.nih.gov/pubmed/29097847
http://dx.doi.org/10.1293/tox.2017-0031
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author Horai, Yasushi
Kakimoto, Tetsuhiro
Takemoto, Kana
Tanaka, Masaharu
author_facet Horai, Yasushi
Kakimoto, Tetsuhiro
Takemoto, Kana
Tanaka, Masaharu
author_sort Horai, Yasushi
collection PubMed
description In evaluating pathological changes in drug efficacy and toxicity studies, morphometric analysis can be quite robust. In this experiment, we examined whether morphometric changes of major pathological findings in various tissue specimens stained with hematoxylin and eosin could be recognized and quantified using image processing software. Using Tissue Studio, hypertrophy of hepatocytes and adrenocortical cells could be quantified based on the method of a previous report, but the regions of red pulp, white pulp, and marginal zones in the spleen could not be recognized when using one setting condition. Using Image-Pro Plus, lipid-derived vacuoles in the liver and mucin-derived vacuoles in the intestinal mucosa could be quantified using two criteria (area and/or roundness). Vacuoles derived from phospholipid could not be quantified when small lipid deposition coexisted in the liver and adrenal cortex. Mononuclear inflammatory cell infiltration in the liver could be quantified to some extent, except for specimens with many clustered infiltrating cells. Adipocyte size and the mean linear intercept could be quantified easily and efficiently using morphological processing and the macro tool equipped in Image-Pro Plus. These methodologies are expected to form a base system that can recognize morphometric features and analyze quantitatively pathological findings through the use of information technology.
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spelling pubmed-56609592017-11-02 Quantitative analysis of histopathological findings using image processing software Horai, Yasushi Kakimoto, Tetsuhiro Takemoto, Kana Tanaka, Masaharu J Toxicol Pathol Technical Report In evaluating pathological changes in drug efficacy and toxicity studies, morphometric analysis can be quite robust. In this experiment, we examined whether morphometric changes of major pathological findings in various tissue specimens stained with hematoxylin and eosin could be recognized and quantified using image processing software. Using Tissue Studio, hypertrophy of hepatocytes and adrenocortical cells could be quantified based on the method of a previous report, but the regions of red pulp, white pulp, and marginal zones in the spleen could not be recognized when using one setting condition. Using Image-Pro Plus, lipid-derived vacuoles in the liver and mucin-derived vacuoles in the intestinal mucosa could be quantified using two criteria (area and/or roundness). Vacuoles derived from phospholipid could not be quantified when small lipid deposition coexisted in the liver and adrenal cortex. Mononuclear inflammatory cell infiltration in the liver could be quantified to some extent, except for specimens with many clustered infiltrating cells. Adipocyte size and the mean linear intercept could be quantified easily and efficiently using morphological processing and the macro tool equipped in Image-Pro Plus. These methodologies are expected to form a base system that can recognize morphometric features and analyze quantitatively pathological findings through the use of information technology. Japanese Society of Toxicologic Pathology 2017-08-20 2017-10 /pmc/articles/PMC5660959/ /pubmed/29097847 http://dx.doi.org/10.1293/tox.2017-0031 Text en ©2017 The Japanese Society of Toxicologic Pathology This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License. (CC-BY-NC-ND 4.0: https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Technical Report
Horai, Yasushi
Kakimoto, Tetsuhiro
Takemoto, Kana
Tanaka, Masaharu
Quantitative analysis of histopathological findings using image processing software
title Quantitative analysis of histopathological findings using image processing software
title_full Quantitative analysis of histopathological findings using image processing software
title_fullStr Quantitative analysis of histopathological findings using image processing software
title_full_unstemmed Quantitative analysis of histopathological findings using image processing software
title_short Quantitative analysis of histopathological findings using image processing software
title_sort quantitative analysis of histopathological findings using image processing software
topic Technical Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5660959/
https://www.ncbi.nlm.nih.gov/pubmed/29097847
http://dx.doi.org/10.1293/tox.2017-0031
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