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用于口腔正常组织和癌前组织分类的时间分辨自体荧光光谱学

Time-resolved autofluorescence spectroscopy for classifying normal and premalignant oral tissues.

作者信息

Chen Hsin-Ming, Chiang Chun-Pin, You Chun, Hsiao Tzu-Chien, Wang Chih-Yu

机构信息

Department of Dentistry, National Taiwan University Hospital, Taiwan.

出版信息

Lasers Surg Med. 2005 Jul;37(1):37-45. doi: 10.1002/lsm.20192.

Abstract

BACKGROUND AND OBJECTIVES

Time-resolved autofluorescence spectroscopy has been used for effectively distinguishing normal tissues from precancers and cancers in various organs. The aim of this study was to find out the possibility of using time-resolved autofluorescence spectroscopy to differentiate normal oral mucosa (NOM) from oral premalignant lesions including verrucous hyperplasia (VH), epithelial hyperplasia (EH), and epithelial dysplasia (ED).

STUDY DESIGN/MATERIALS AND METHODS: Time-resolved autofluorescence spectra at 633 nm under 410-nm excitation were recorded for 15 VH, 9 EH, 14 ED, and 38 NOM samples. The two-component lifetimes of the obtained curves were calculated, and a Fisher's discriminant analysis (FDA) was employed for distinguishing these tissue samples.

RESULTS

After two-component lifetimes for all samples being calculated, a two-dimensional scatter plot was developed, in which 76 oral tissue samples were separated into three groups by FDA. With a leave-one-out method, the FDA algorithm gave an accuracy rate of 93% for ED, of 75% for VH and EH, and of 100% for NOM samples. In addition, all oral premalignant lesions (including VH, EH, and ED) could be distinguished from NOM samples by this FDA algorithm.

CONCLUSIONS

We conclude that time-resolved autofluorescence spectroscopy at 633 nm under 410-nm excitation, based on two-component lifetime calculation and FDA, is a very sensitive technique for in vivo diagnosis of oral premalignant lesions. .

摘要

背景与目的

时间分辨自体荧光光谱已被用于有效区分各器官中的正常组织与癌前病变及癌症。本研究的目的是探究使用时间分辨自体荧光光谱区分正常口腔黏膜(NOM)与口腔癌前病变(包括疣状增生(VH)、上皮增生(EH)和上皮发育异常(ED))的可能性。

研究设计/材料与方法:记录了15个VH、9个EH、14个ED和38个NOM样本在410nm激发下633nm处的时间分辨自体荧光光谱。计算所得曲线的双组分寿命,并采用费舍尔判别分析(FDA)来区分这些组织样本。

结果

在计算所有样本的双组分寿命后,绘制了二维散点图,通过FDA将76个口腔组织样本分为三组。采用留一法,FDA算法对ED样本的准确率为93%,对VH和EH样本的准确率为75%,对NOM样本的准确率为100%。此外,通过该FDA算法可将所有口腔癌前病变(包括VH、EH和ED)与NOM样本区分开来。

结论

我们得出结论,基于双组分寿命计算和FDA的410nm激发下633nm处的时间分辨自体荧光光谱是一种用于口腔癌前病变活体诊断的非常灵敏的技术。

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