Lihachev Alexey, Lihacova Ilze, Plorina Emilija V, Lange Marta, Derjabo Alexander, Spigulis Janis
Institute of Atomic Physics and Spectroscopy, University of Latvia, Raina Blvd. 19, Riga LV-1586, Latvia.
Riga Eastern University Hospital, Oncology Centre of Latvia, Hipokrata Street 4, Riga LV-1079, Latvia.
Biomed Opt Express. 2018 Mar 23;9(4):1852-1858. doi: 10.1364/BOE.9.001852. eCollection 2018 Apr 1.
A clinical trial on the autofluorescence imaging of skin lesions comprising 16 dermatologically confirmed pigmented nevi, 15 seborrheic keratosis, 2 dysplastic nevi, histologically confirmed 17 basal cell carcinomas and 1 melanoma was performed. The autofluorescence spatial properties of the skin lesions were acquired by smartphone RGB camera under 405 nm LED excitation. The diagnostic criterion is based on the calculation of the mean autofluorescence intensity of the examined lesion in the spectral range of 515 nm-700 nm. The proposed methodology is able to differentiate seborrheic keratosis from basal cell carcinoma, pigmented nevi and melanoma. The sensitivity and specificity of the proposed method was estimated as being close to 100%. The proposed methodology and potential clinical applications are discussed in this article.
开展了一项关于皮肤病变自体荧光成像的临床试验，该试验纳入了16例经皮肤科确诊的色素痣、15例脂溢性角化病、2例发育异常痣、17例经组织学确诊的基底细胞癌和1例黑色素瘤。皮肤病变的自体荧光空间特性通过智能手机RGB相机在405 nm LED激发下获取。诊断标准基于计算被检查病变在515 nm - 700 nm光谱范围内的平均自体荧光强度。所提出的方法能够区分脂溢性角化病与基底细胞癌、色素痣和黑色素瘤。所提出方法的敏感性和特异性估计接近100%。本文讨论了所提出的方法及其潜在的临床应用。
