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Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy
Hirschsprung disease (HD) is a congenital disorder in the distal colon that is characterized by the absence of nerve ganglion cells in the diseased tissue. The primary treatment for HD is surgical intervention with resection of the aganglionic bowel. The accurate identification of the aganglionic se...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809197/ https://www.ncbi.nlm.nih.gov/pubmed/33446868 http://dx.doi.org/10.1038/s41598-021-80981-7 |
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author | Soares de Oliveira, Marcos A. Galganski, Laura Stokes, Sarah Chang, Che -Wei Pivetti, Christopher D. Zhang, Bo Matsukuma, Karen E. Saadai, Payam Chan, James W. |
author_facet | Soares de Oliveira, Marcos A. Galganski, Laura Stokes, Sarah Chang, Che -Wei Pivetti, Christopher D. Zhang, Bo Matsukuma, Karen E. Saadai, Payam Chan, James W. |
author_sort | Soares de Oliveira, Marcos A. |
collection | PubMed |
description | Hirschsprung disease (HD) is a congenital disorder in the distal colon that is characterized by the absence of nerve ganglion cells in the diseased tissue. The primary treatment for HD is surgical intervention with resection of the aganglionic bowel. The accurate identification of the aganglionic segment depends on the histologic evaluation of multiple biopsies to determine the absence of ganglion cells in the tissue, which can be a time-consuming procedure. We investigate the feasibility of using a combination of label-free optical modalities, second harmonic generation (SHG); two-photon excitation autofluorescence (2PAF); and Raman spectroscopy (RS), to accurately locate and identify ganglion cells in murine intestinal tissue without the use of exogenous labels or dyes. We show that the image contrast provided by SHG and 2PAF signals allows for the visualization of the overall tissue morphology and localization of regions that may contain ganglion cells, while RS provides detailed multiplexed molecular information that can be used to accurately identify specific ganglion cells. Support vector machine, principal component analysis and linear discriminant analysis classification models were applied to the hyperspectral Raman data and showed that ganglion cells can be identified with a classification accuracy higher than 95%. Our findings suggest that a near real-time intraoperative histology method can be developed using these three optical modalities together that can aid pathologists and surgeons in rapid, accurate identification of ganglion cells to guide surgical decisions with minimal human intervention. |
format | Online Article Text |
id | pubmed-7809197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78091972021-01-15 Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy Soares de Oliveira, Marcos A. Galganski, Laura Stokes, Sarah Chang, Che -Wei Pivetti, Christopher D. Zhang, Bo Matsukuma, Karen E. Saadai, Payam Chan, James W. Sci Rep Article Hirschsprung disease (HD) is a congenital disorder in the distal colon that is characterized by the absence of nerve ganglion cells in the diseased tissue. The primary treatment for HD is surgical intervention with resection of the aganglionic bowel. The accurate identification of the aganglionic segment depends on the histologic evaluation of multiple biopsies to determine the absence of ganglion cells in the tissue, which can be a time-consuming procedure. We investigate the feasibility of using a combination of label-free optical modalities, second harmonic generation (SHG); two-photon excitation autofluorescence (2PAF); and Raman spectroscopy (RS), to accurately locate and identify ganglion cells in murine intestinal tissue without the use of exogenous labels or dyes. We show that the image contrast provided by SHG and 2PAF signals allows for the visualization of the overall tissue morphology and localization of regions that may contain ganglion cells, while RS provides detailed multiplexed molecular information that can be used to accurately identify specific ganglion cells. Support vector machine, principal component analysis and linear discriminant analysis classification models were applied to the hyperspectral Raman data and showed that ganglion cells can be identified with a classification accuracy higher than 95%. Our findings suggest that a near real-time intraoperative histology method can be developed using these three optical modalities together that can aid pathologists and surgeons in rapid, accurate identification of ganglion cells to guide surgical decisions with minimal human intervention. Nature Publishing Group UK 2021-01-14 /pmc/articles/PMC7809197/ /pubmed/33446868 http://dx.doi.org/10.1038/s41598-021-80981-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Soares de Oliveira, Marcos A. Galganski, Laura Stokes, Sarah Chang, Che -Wei Pivetti, Christopher D. Zhang, Bo Matsukuma, Karen E. Saadai, Payam Chan, James W. Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
title | Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
title_full | Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
title_fullStr | Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
title_full_unstemmed | Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
title_short | Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
title_sort | diagnosing hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809197/ https://www.ncbi.nlm.nih.gov/pubmed/33446868 http://dx.doi.org/10.1038/s41598-021-80981-7 |
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