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Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue

This study aims to determine if light scatter parameters measured with spatial frequency domain imaging (SFDI) can accurately predict stromal, epithelial, and adipose fractions in freshly resected, unstained human breast specimens. An explicit model was developed to predict stromal, epithelial, and...

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Autores principales: McClatchy, David M., Rizzo, Elizabeth J., Wells, Wendy A., Black, Candice C., Paulsen, Keith D., Kanick, Stephen C., Pogue, Brian W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676039/
https://www.ncbi.nlm.nih.gov/pubmed/30264552
http://dx.doi.org/10.1117/1.JBO.24.7.071605
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author McClatchy, David M.
Rizzo, Elizabeth J.
Wells, Wendy A.
Black, Candice C.
Paulsen, Keith D.
Kanick, Stephen C.
Pogue, Brian W.
author_facet McClatchy, David M.
Rizzo, Elizabeth J.
Wells, Wendy A.
Black, Candice C.
Paulsen, Keith D.
Kanick, Stephen C.
Pogue, Brian W.
author_sort McClatchy, David M.
collection PubMed
description This study aims to determine if light scatter parameters measured with spatial frequency domain imaging (SFDI) can accurately predict stromal, epithelial, and adipose fractions in freshly resected, unstained human breast specimens. An explicit model was developed to predict stromal, epithelial, and adipose fractions as a function of light scattering parameters, which was validated against a quantitative analysis of digitized histology slides for [Formula: see text] specimens using leave-one-out cross-fold validation. Specimen mean stromal, epithelial, and adipose volume fractions predicted from light scattering parameters strongly correlated with those calculated from digitized histology slides ([Formula: see text] , 0.77, and 0.91, respectively, [Formula: see text]-value [Formula: see text]). Additionally, the ratio of predicted epithelium to stroma classified malignant specimens with a sensitivity and specificity of 90% and 81%, respectively, and also classified all pixels in malignant lesions with 63% and 79%, at a threshold of 1. All specimens and pixels were classified as malignant, benign, or fat with 84% and 75% accuracy, respectively. These findings demonstrate how light scattering parameters acquired with SFDI can be used to accurately predict and spatially map stromal, epithelial, and adipose proportions in fresh unstained, human breast tissue, and suggest that these estimations could provide diagnostic value.
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spelling pubmed-66760392019-09-27 Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue McClatchy, David M. Rizzo, Elizabeth J. Wells, Wendy A. Black, Candice C. Paulsen, Keith D. Kanick, Stephen C. Pogue, Brian W. J Biomed Opt Special Section on Spatial Frequency Domain Imaging This study aims to determine if light scatter parameters measured with spatial frequency domain imaging (SFDI) can accurately predict stromal, epithelial, and adipose fractions in freshly resected, unstained human breast specimens. An explicit model was developed to predict stromal, epithelial, and adipose fractions as a function of light scattering parameters, which was validated against a quantitative analysis of digitized histology slides for [Formula: see text] specimens using leave-one-out cross-fold validation. Specimen mean stromal, epithelial, and adipose volume fractions predicted from light scattering parameters strongly correlated with those calculated from digitized histology slides ([Formula: see text] , 0.77, and 0.91, respectively, [Formula: see text]-value [Formula: see text]). Additionally, the ratio of predicted epithelium to stroma classified malignant specimens with a sensitivity and specificity of 90% and 81%, respectively, and also classified all pixels in malignant lesions with 63% and 79%, at a threshold of 1. All specimens and pixels were classified as malignant, benign, or fat with 84% and 75% accuracy, respectively. These findings demonstrate how light scattering parameters acquired with SFDI can be used to accurately predict and spatially map stromal, epithelial, and adipose proportions in fresh unstained, human breast tissue, and suggest that these estimations could provide diagnostic value. Society of Photo-Optical Instrumentation Engineers 2018-09-27 2019-07 /pmc/articles/PMC6676039/ /pubmed/30264552 http://dx.doi.org/10.1117/1.JBO.24.7.071605 Text en © The Authors. https://creativecommons.org/licenses/by/3.0/ Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
spellingShingle Special Section on Spatial Frequency Domain Imaging
McClatchy, David M.
Rizzo, Elizabeth J.
Wells, Wendy A.
Black, Candice C.
Paulsen, Keith D.
Kanick, Stephen C.
Pogue, Brian W.
Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
title Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
title_full Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
title_fullStr Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
title_full_unstemmed Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
title_short Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
title_sort light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue
topic Special Section on Spatial Frequency Domain Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676039/
https://www.ncbi.nlm.nih.gov/pubmed/30264552
http://dx.doi.org/10.1117/1.JBO.24.7.071605
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