Anatomy-Based Algorithms for Detecting Oral Cancer Using Reflectance and Fluorescence Spectroscopy
Anatomy-Based Algorithms for Detecting Oral Cancer Using Reflectance and Fluorescence Spectroscopy
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DOI：
10.1177/000348941011901112
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发表时间：
2009-11-01
影响因子：
1.4
通讯作者：
Feld, Michael S.
中科院分区：
文献类型：
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作者：
McGee, Sasha;Mardirossian, Vartan;Feld, Michael S.
目的：我们使用反射和荧光光谱法，非侵入性和定量区分良性的口腔病变的发育不良/恶性。我们设计的诊断算法，以解释解剖部位（牙龈，颊粘膜等）之间的光谱特性的差异：在体内的反射和荧光光谱收集了71例口腔病变。然后对组织进行活检，并通过组织病理学对标本进行评价。从光谱中提取与组织形态学和生物化学相关的定量参数。特定的诊断算法的组合具有相似的光谱properties的网站developed.Results：良性发育不良/恶性病变的歧视是最成功的算法时，被设计为个别网站（面积下的接收器操作者特征曲线[ROC-AUC]，0.75的舌头的侧面），是最不准确的，当所有网站相结合（ROC-AUC，0.60）。具有相似光谱特性的部位（口底和扁桃体侧面）的组合产生的ROC AUC为0.71。结论：准确的口腔疾病光谱检测必须考虑解剖部位之间的光谱差异。单个部位或部位组合的基于解剖结构的算法在区分良性病变与异型增生/恶性病变方面表现出良好的诊断性能，并且始终优于为所有部位组合开发的算法。
Objectives: We used reflectance and fluorescence spectroscopy to noninvasively and quantitatively distinguish benign from dysplastic/malignant oral lesions. We designed diagnostic algorithms to account for differences in the spectral properties among anatomic sites (gingiva, buccal mucosa, etc).Methods: In vivo reflectance and fluorescence spectra were collected from 71 patients with oral lesions. The tissue was then biopsied and the specimen evaluated by histopathology. Quantitative parameters related to tissue morphology and biochemistry were extracted from the spectra. Diagnostic algorithms specific for combinations of sites with similar spectral properties were developed.Results: Discrimination of benign from dysplastic/malignant lesions was most successful when algorithms were designed for individual sites (area under the receiver operator characteristic curve [ROC-AUC], 0.75 for the lateral surface of the tongue) and was least accurate when all sites were combined (ROC-AUC, 0.60). The combination of sites with similar spectral properties (floor of mouth and lateral surface of the ton-Lie) yielded an ROC-AUC of 0.71.Conclusions: Accurate spectroscopic detection of oral disease must account for spectral variations among anatomic sites. Anatomy-based algorithms for single sites or combinations of sites demonstrated good diagnostic performance in distinguishing benign lesions from dysplastic/malignant lesions and consistently performed better than algorithms developed for all sites combined.