Murphy Bruce W, Webster Rebecca J, Turlach Berwin A, Quirk Christopher J, Clay Christopher D, Heenan Peter J, Sampson David D
The University of Western Australia, School of Electrical, Electronic, and Computer Engineering, Optical+Biomedical Engineering Laboratory, M018, 35 Stirling Highway, Crawley, Western Australia 6009, Australia.
J Biomed Opt. 2005 Nov-Dec;10(6):064020. doi: 10.1117/1.2135799.
We describe a study of the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy. Diffuse reflectance spectra in the wavelength range 550 to 1000 nm are obtained using 400-microm core multimode fibers arranged in a six-illumination-around-one-collection geometry with a single fiber-fiber spacing of 470 microm. Spectra are collected at specific locations on 120 pigmented lesions selected by clinicians as possible melanoma, including 64 histopathologically diagnosed as melanoma. These locations are carried through to the histopathological diagnosis, permitting a spatially localized comparison with the corresponding spectrum. The variations in spectra between groups of lesions with different diagnoses are examined and reduced to features suitable for discriminant analysis. A classifier distinguishing between benign and malignant lesions performs with sensitivity/specificity of between 6469% and 7278%. Classifiers between pairs of the group common nevus, dysplastic nevus, in situ melanoma, and invasive melanoma show better or similar performance than the benign/malignant classifier, and analysis provides evidence that different spectral features are needed for each pair of groups. This indicates that multiple discriminant systems are likely to be required to distinguish between melanoma and similar lesions.
我们描述了一项使用光纤漫反射光谱法鉴别早期黑色素瘤与普通痣和发育异常痣的研究。使用400微米芯多模光纤,以六环绕一采集的几何结构、单根光纤间距为470微米,在550至1000纳米波长范围内获取漫反射光谱。在临床医生选定的120个可能为黑色素瘤的色素沉着病变的特定位置采集光谱,其中64个经组织病理学诊断为黑色素瘤。这些位置与组织病理学诊断相对应,从而能够对相应光谱进行空间定位比较。检查不同诊断的病变组之间光谱的变化,并将其简化为适合判别分析的特征。区分良性和恶性病变的分类器的灵敏度/特异性在64%至69%和72%至78%之间。普通痣、发育异常痣、原位黑色素瘤和侵袭性黑色素瘤组之间的分类器表现优于或类似于良性/恶性分类器,分析表明每组之间需要不同的光谱特征。这表明可能需要多个判别系统来区分黑色素瘤和类似病变。