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Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas
We present the first detailed study using multispectral multiphoton fluorescence lifetime imaging to differentiate basal cell carcinoma cells (BCCs) from normal keratinocytes. Images were acquired from 19 freshly excised BCCs and 27 samples of normal skin (in & ex vivo). Features from fluorescen...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3439453/ https://www.ncbi.nlm.nih.gov/pubmed/22984428 http://dx.doi.org/10.1371/journal.pone.0043460 |
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author | Patalay, Rakesh Talbot, Clifford Alexandrov, Yuriy Lenz, Martin O. Kumar, Sunil Warren, Sean Munro, Ian Neil, Mark A. A. König, Karsten French, Paul M. W. Chu, Anthony Stamp, Gordon W. H. Dunsby, Chris |
author_facet | Patalay, Rakesh Talbot, Clifford Alexandrov, Yuriy Lenz, Martin O. Kumar, Sunil Warren, Sean Munro, Ian Neil, Mark A. A. König, Karsten French, Paul M. W. Chu, Anthony Stamp, Gordon W. H. Dunsby, Chris |
author_sort | Patalay, Rakesh |
collection | PubMed |
description | We present the first detailed study using multispectral multiphoton fluorescence lifetime imaging to differentiate basal cell carcinoma cells (BCCs) from normal keratinocytes. Images were acquired from 19 freshly excised BCCs and 27 samples of normal skin (in & ex vivo). Features from fluorescence lifetime images were used to discriminate BCCs with a sensitivity/specificity of 79%/93% respectively. A mosaic of BCC fluorescence lifetime images covering >1 mm(2) is also presented, demonstrating the potential for tumour margin delineation. Using 10,462 manually segmented cells from the image data, we quantify the cellular morphology and spectroscopic differences between BCCs and normal skin for the first time. Statistically significant increases were found in the fluorescence lifetimes of cells from BCCs in all spectral channels, ranging from 19.9% (425–515 nm spectral emission) to 39.8% (620–655 nm emission). A discriminant analysis based diagnostic algorithm allowed the fraction of cells classified as malignant to be calculated for each patient. This yielded a receiver operator characteristic area under the curve for the detection of BCC of 0.83. We have used both morphological and spectroscopic parameters to discriminate BCC from normal skin, and provide a comprehensive base for how this technique could be used for BCC assessment in clinical practice. |
format | Online Article Text |
id | pubmed-3439453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34394532012-09-14 Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas Patalay, Rakesh Talbot, Clifford Alexandrov, Yuriy Lenz, Martin O. Kumar, Sunil Warren, Sean Munro, Ian Neil, Mark A. A. König, Karsten French, Paul M. W. Chu, Anthony Stamp, Gordon W. H. Dunsby, Chris PLoS One Research Article We present the first detailed study using multispectral multiphoton fluorescence lifetime imaging to differentiate basal cell carcinoma cells (BCCs) from normal keratinocytes. Images were acquired from 19 freshly excised BCCs and 27 samples of normal skin (in & ex vivo). Features from fluorescence lifetime images were used to discriminate BCCs with a sensitivity/specificity of 79%/93% respectively. A mosaic of BCC fluorescence lifetime images covering >1 mm(2) is also presented, demonstrating the potential for tumour margin delineation. Using 10,462 manually segmented cells from the image data, we quantify the cellular morphology and spectroscopic differences between BCCs and normal skin for the first time. Statistically significant increases were found in the fluorescence lifetimes of cells from BCCs in all spectral channels, ranging from 19.9% (425–515 nm spectral emission) to 39.8% (620–655 nm emission). A discriminant analysis based diagnostic algorithm allowed the fraction of cells classified as malignant to be calculated for each patient. This yielded a receiver operator characteristic area under the curve for the detection of BCC of 0.83. We have used both morphological and spectroscopic parameters to discriminate BCC from normal skin, and provide a comprehensive base for how this technique could be used for BCC assessment in clinical practice. Public Library of Science 2012-09-11 /pmc/articles/PMC3439453/ /pubmed/22984428 http://dx.doi.org/10.1371/journal.pone.0043460 Text en © 2012 Patalay et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Patalay, Rakesh Talbot, Clifford Alexandrov, Yuriy Lenz, Martin O. Kumar, Sunil Warren, Sean Munro, Ian Neil, Mark A. A. König, Karsten French, Paul M. W. Chu, Anthony Stamp, Gordon W. H. Dunsby, Chris Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas |
title | Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas |
title_full | Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas |
title_fullStr | Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas |
title_full_unstemmed | Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas |
title_short | Multiphoton Multispectral Fluorescence Lifetime Tomography for the Evaluation of Basal Cell Carcinomas |
title_sort | multiphoton multispectral fluorescence lifetime tomography for the evaluation of basal cell carcinomas |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3439453/ https://www.ncbi.nlm.nih.gov/pubmed/22984428 http://dx.doi.org/10.1371/journal.pone.0043460 |
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