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Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM)
Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789107/ https://www.ncbi.nlm.nih.gov/pubmed/31604963 http://dx.doi.org/10.1038/s41598-019-50143-x |
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author | Majeed, Hassaan Keikhosravi, Adib Kandel, Mikhail E. Nguyen, Tan H. Liu, Yuming Kajdacsy-Balla, Andre Tangella, Krishnarao Eliceiri, Kevin W. Popescu, Gabriel |
author_facet | Majeed, Hassaan Keikhosravi, Adib Kandel, Mikhail E. Nguyen, Tan H. Liu, Yuming Kajdacsy-Balla, Andre Tangella, Krishnarao Eliceiri, Kevin W. Popescu, Gabriel |
author_sort | Majeed, Hassaan |
collection | PubMed |
description | Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing. Here we present color spatial light interference microscopy (cSLIM) as a new whole-slide imaging modality that performs interferometric imaging on stained tissue, with a color detector array. As a result, cSLIM yields in a single scan both the intrinsic tissue phase map and the standard color bright-field image, familiar to the pathologist. Our results on 196 breast cancer patients indicate that cSLIM can provide stain-independent prognostic information from the alignment of collagen fibers in the tumor microenvironment. The effects of staining on the tissue phase maps were corrected by a mathematical normalization. These characteristics are likely to reduce barriers to clinical translation for the new cSLIM technology. |
format | Online Article Text |
id | pubmed-6789107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67891072019-10-17 Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) Majeed, Hassaan Keikhosravi, Adib Kandel, Mikhail E. Nguyen, Tan H. Liu, Yuming Kajdacsy-Balla, Andre Tangella, Krishnarao Eliceiri, Kevin W. Popescu, Gabriel Sci Rep Article Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing. Here we present color spatial light interference microscopy (cSLIM) as a new whole-slide imaging modality that performs interferometric imaging on stained tissue, with a color detector array. As a result, cSLIM yields in a single scan both the intrinsic tissue phase map and the standard color bright-field image, familiar to the pathologist. Our results on 196 breast cancer patients indicate that cSLIM can provide stain-independent prognostic information from the alignment of collagen fibers in the tumor microenvironment. The effects of staining on the tissue phase maps were corrected by a mathematical normalization. These characteristics are likely to reduce barriers to clinical translation for the new cSLIM technology. Nature Publishing Group UK 2019-10-11 /pmc/articles/PMC6789107/ /pubmed/31604963 http://dx.doi.org/10.1038/s41598-019-50143-x Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Majeed, Hassaan Keikhosravi, Adib Kandel, Mikhail E. Nguyen, Tan H. Liu, Yuming Kajdacsy-Balla, Andre Tangella, Krishnarao Eliceiri, Kevin W. Popescu, Gabriel Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
title | Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
title_full | Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
title_fullStr | Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
title_full_unstemmed | Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
title_short | Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM) |
title_sort | quantitative histopathology of stained tissues using color spatial light interference microscopy (cslim) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789107/ https://www.ncbi.nlm.nih.gov/pubmed/31604963 http://dx.doi.org/10.1038/s41598-019-50143-x |
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