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Quantitative analysis of myocardial tissue with digital autofluorescence microscopy

BACKGROUND: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of...

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Autores principales: Jensen, Thomas, Holten-Rossing, Henrik, Svendsen, Ida M H, Jacobsen, Christina, Vainer, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837794/
https://www.ncbi.nlm.nih.gov/pubmed/27141321
http://dx.doi.org/10.4103/2153-3539.179908
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author Jensen, Thomas
Holten-Rossing, Henrik
Svendsen, Ida M H
Jacobsen, Christina
Vainer, Ben
author_facet Jensen, Thomas
Holten-Rossing, Henrik
Svendsen, Ida M H
Jacobsen, Christina
Vainer, Ben
author_sort Jensen, Thomas
collection PubMed
description BACKGROUND: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit. METHODS: This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented. RESULTS: It is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining. CONCLUSION: The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.
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spelling pubmed-48377942016-05-02 Quantitative analysis of myocardial tissue with digital autofluorescence microscopy Jensen, Thomas Holten-Rossing, Henrik Svendsen, Ida M H Jacobsen, Christina Vainer, Ben J Pathol Inform Research Article BACKGROUND: The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit. METHODS: This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented. RESULTS: It is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining. CONCLUSION: The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework. Medknow Publications & Media Pvt Ltd 2016-04-11 /pmc/articles/PMC4837794/ /pubmed/27141321 http://dx.doi.org/10.4103/2153-3539.179908 Text en Copyright: © Journal of Pathology Informatics http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Research Article
Jensen, Thomas
Holten-Rossing, Henrik
Svendsen, Ida M H
Jacobsen, Christina
Vainer, Ben
Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
title Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
title_full Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
title_fullStr Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
title_full_unstemmed Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
title_short Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
title_sort quantitative analysis of myocardial tissue with digital autofluorescence microscopy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4837794/
https://www.ncbi.nlm.nih.gov/pubmed/27141321
http://dx.doi.org/10.4103/2153-3539.179908
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