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Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy

Until now, the classification system of oral epithelial dysplasia is still based on the architectural and cytological changes, which relies on the observation of pathologists and is relatively subjective. The purpose of present research was to discriminate the oral dysplasia by the near-infrared Ram...

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Autores principales: Li, Bo, Gu, Zhi-Yu, Yan, Kai-Xiao, Wen, Zhi-Ning, Zhao, Zhi-He, Li, Long-Jiang, Li, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5652703/
https://www.ncbi.nlm.nih.gov/pubmed/29100309
http://dx.doi.org/10.18632/oncotarget.19343
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author Li, Bo
Gu, Zhi-Yu
Yan, Kai-Xiao
Wen, Zhi-Ning
Zhao, Zhi-He
Li, Long-Jiang
Li, Yi
author_facet Li, Bo
Gu, Zhi-Yu
Yan, Kai-Xiao
Wen, Zhi-Ning
Zhao, Zhi-He
Li, Long-Jiang
Li, Yi
author_sort Li, Bo
collection PubMed
description Until now, the classification system of oral epithelial dysplasia is still based on the architectural and cytological changes, which relies on the observation of pathologists and is relatively subjective. The purpose of present research was to discriminate the oral dysplasia by the near-infrared Raman spectroscope, in order to evaluate the classification system. We collected Raman spectra of normal mucosa, oral squamous cell carcinoma (OSCC) and dysplasia by near-infrared Raman spectroscope. The biochemical variations between different stages were analyzed by the characteristic peaks in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to establish the diagnostic models. At the same time, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to verify the results of SVM. Raman spectral differences were observed in the range between 730~1913 cm(-1). Compared with normal mucosa, high contents of protein and DNA in oral dysplasia and OSCC were observed. There were no significant or gradual variation of Raman peaks among different dysplastic grades. The accuracies of comparison between mild, moderate, severe dysplasia with OSCC were 100%, 44.44%, 71.15%, which elucidated the low modeling ability of support vector machines, especially for the moderate dysplasia. The analysis by PCA-LDA could not discriminate the stages, either. Combined with support vector machines, near-infrared Raman spectroscopy could detect the biochemical variations in oral normal, OSCC and dysplastic tissues, but could not establish diagnostic model accurately. The classification system needs further improvements.
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spelling pubmed-56527032017-11-02 Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy Li, Bo Gu, Zhi-Yu Yan, Kai-Xiao Wen, Zhi-Ning Zhao, Zhi-He Li, Long-Jiang Li, Yi Oncotarget Research Paper Until now, the classification system of oral epithelial dysplasia is still based on the architectural and cytological changes, which relies on the observation of pathologists and is relatively subjective. The purpose of present research was to discriminate the oral dysplasia by the near-infrared Raman spectroscope, in order to evaluate the classification system. We collected Raman spectra of normal mucosa, oral squamous cell carcinoma (OSCC) and dysplasia by near-infrared Raman spectroscope. The biochemical variations between different stages were analyzed by the characteristic peaks in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to establish the diagnostic models. At the same time, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to verify the results of SVM. Raman spectral differences were observed in the range between 730~1913 cm(-1). Compared with normal mucosa, high contents of protein and DNA in oral dysplasia and OSCC were observed. There were no significant or gradual variation of Raman peaks among different dysplastic grades. The accuracies of comparison between mild, moderate, severe dysplasia with OSCC were 100%, 44.44%, 71.15%, which elucidated the low modeling ability of support vector machines, especially for the moderate dysplasia. The analysis by PCA-LDA could not discriminate the stages, either. Combined with support vector machines, near-infrared Raman spectroscopy could detect the biochemical variations in oral normal, OSCC and dysplastic tissues, but could not establish diagnostic model accurately. The classification system needs further improvements. Impact Journals LLC 2017-07-18 /pmc/articles/PMC5652703/ /pubmed/29100309 http://dx.doi.org/10.18632/oncotarget.19343 Text en Copyright: © 2017 Li et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (http://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Li, Bo
Gu, Zhi-Yu
Yan, Kai-Xiao
Wen, Zhi-Ning
Zhao, Zhi-He
Li, Long-Jiang
Li, Yi
Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy
title Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy
title_full Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy
title_fullStr Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy
title_full_unstemmed Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy
title_short Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy
title_sort evaluating oral epithelial dysplasia classification system by near-infrared raman spectroscopy
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5652703/
https://www.ncbi.nlm.nih.gov/pubmed/29100309
http://dx.doi.org/10.18632/oncotarget.19343
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