口腔癌的荧光光谱检测及不同分期的多变量分析

Pavan Kumar
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引用次数: 0

摘要

本研究将荧光光谱作为口腔癌的诊断工具。对于荧光测量,激发波长为350 nm。两种诊断介质,即人体组织和唾液纳入本研究。测量完成对口腔鳞状细胞癌(OSCC),发育不良,和正常组织和唾液样本。从人口腔组织中获得的荧光光谱包括390和445 nm附近的胶原和NADH的主要波段。然而,唾液在440 nm附近只显示一个NADH主带。对人口腔组织和唾液的荧光数据进行多变量分析,对不同阶段的癌症进行分类。在多变量分析中,采用主成分分析(PCA)、马氏距离(MD)模型和受试者工作特征(ROC)分析。利用荧光光谱对人口腔组织和唾液进行鉴别,OSCC与正常、异常增生与正常、OSCC与异常增生的总体准确率分别为90%、83%、80%和100%、86%、85%。利用荧光光谱法对人唾液进行分析得到的结果与人体组织样品具有可比性。结果表明,我们可以利用唾液作为一种无创的诊断介质来检测口腔癌,多变量分析可以作为一种分类工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Oral Cancer Using the Fluorescence Spectroscopy and Classification of Different Stages of Cancer by Multivariate Analysis
Fluorescence spectroscopy is used as a diagnostic tool for the detection of oral cancer in the present study. For the fluorescence measurement, an excitation wavelength of 350 nm is used. Two diagnostic media, namely human tissue and saliva are incorporated in this study. Measurements are accomplished on oral squamous cell carcinoma (OSCC), dysplastic, and normal tissue and saliva samples. Fluorescence spectra obtained from human oral tissue consists of major bands of collagen and NADH near 390 and 445 nm. However, saliva shows only one major band of NADH near 440 nm. Multivariate analysis has been employed on the fluorescence data of human oral tissue and saliva for the classification of different stages of cancer. In the multivariate analysis, principal component analysis (PCA), Mahalanobis distance (MD) model, and receiver operating characteristic (ROC) analysis are utilized. Fluorescence spectroscopy on human oral tissue and saliva is competent to differentiate OSCC to normal, dysplasia to normal and OSCC to dysplasia with overall accuracies of 90%, 83%, 80% and 100%, 86%, 85% respectively. Obtained results using the fluorescence spectroscopy on human saliva are comparable to human tissue samples. Results imply that we may make use of saliva as a non-invasive diagnostic medium for the detection of oral cancer and multivariate analysis can be employed as a classification tool.
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