Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
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Quantitative analysis of myocardial tissue with digital autofluorescence microscopy. / Jensen, Thomas; Holten-Rossing, Henrik; Svendsen, Ida M H; Jacobsen, Christina; Vainer, Ben.
In: Journal of Pathology Informatics, Vol. 7, 15, 2016.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
AU - Jensen, Thomas
AU - Holten-Rossing, Henrik
AU - Svendsen, Ida M H
AU - Jacobsen, Christina
AU - Vainer, Ben
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Journal Article
U2 - 10.4103/2153-3539.179908
DO - 10.4103/2153-3539.179908
M3 - Journal article
C2 - 27141321
VL - 7
JO - Journal of Pathology Informatics
JF - Journal of Pathology Informatics
SN - 2229-5089
M1 - 15
ER -
ID: 172805626