Raman microspectroscopy for skin cancer detection in vitro
Raman microspectroscopy for skin cancer detection in vitro
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DOI：
10.1117/1.2899155
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发表时间：
2008-03-01
影响因子：
3.5
通讯作者：
Mahadevan-Jansen, Anita
中科院分区：
文献类型：
--
作者：
Lieber, Chad A.;Majumder, Shovan K.;Mahadevan-Jansen, Anita
我们研究了近红外拉曼显微光谱的潜力，以区分正常和恶性皮肤病变。研究了39例患者的39个皮肤组织样本，包括正常、基底细胞癌（BCC）、鳞状细胞癌（SCC）和黑色素瘤。记录每个样品的表面和表面下20 μ m间隔处的拉曼光谱，直至至少100 μ m的深度。基于非线性最大表示和判别特征（MRDF）的数据简化算法和基于稀疏多项式逻辑回归（SMLR）的判别算法被开发用于与组织病理学相关的拉曼光谱的分类。组织拉曼光谱被分类为病理状态，对疾病的最大总体灵敏度和特异性为100%。这些结果表明，使用拉曼显微光谱检测皮肤癌的潜力，并为未来的临床研究提供了一个明确的理由。(C)2008年，由光学仪器工程师协会（Society of Photo-Optical Instrumentation Engineers）主办。
We investigate the potential of near-infrared Raman microspectroscopy to differentiate between normal and malignant skin lesions. Thirty-nine skin tissue samples consisting of normal, basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma from 39 patients were investigated. Raman spectra were recorded at the surface and at 20-mu m intervals below the surface for each sample, down to a depth of at least 100 mu m. Data reduction algorithms based on the nonlinear maximum representation and discrimination feature (MRDF) and discriminant algorithms using sparse multinomial logistic regression (SMLR) were developed for classification of the Raman spectra relative to histopathology. The tissue Raman spectra were classified into pathological states with a maximal overall sensitivity and specificity for disease of 100%. These results indicate the potential of using Raman microspectroscopy for skin cancer detection and provide a clear rationale for future clinical studies. (C) 2008 Society of Photo-Optical Instrumentation Engineers.