Fluorescence spectroscopy as a tool to in vivo discrimination of distinctive skin disorders

Background: Fast and non-invasive analytical methods, as in fluorescence spectroscopy, have potential applications to detect modifications of biochemical and morphologic properties of malignant tissues. In this study, we propose to analyze the fluorescence spectra using k-Nearest Neighbours algorithm (k-NN) and ratio of the fluorescence intensity (FI) to differentiate skin disorders of distinctive etiologies and morphologies. Materials and methods: Laser-induced autofluorescence spectra upon excitation at 408 nm were collected from basal cell carcinoma (BCC) subtypes (n = 45/212 spectra), psoriasis (PS) (n = 37/193 spectra) and Bowen's disease (BD) (n = 04/19 spectra) lesions and respective normal skin at sun-exposed (EXP) and non-exposed (NEXP) sites of the same patient. Results: The mean ratios of FI values at selected wavelengths of emission (FI600nm/FI500nm) were significantly lower in BCC and PS lesions compared to EXP [P = 0.0001; P = 0.0002, respectively]; but there were no significant differences between abnormal conditions. The analysis of fluorescence spectra using k-NN can discriminate normal or abnormal skin conditions (EXP, BCC, BD, PS) of distinctive etiology, neoplastic or inflammatory (BCC, BD and PS) and morphologies (nodular and superficial BCC, BD and PS) as high as 88% and 93% sensitivity and specificity means, respectively; also, similar erythematous-squamous features (superficial BCC, BD and PS) with 98% and 97% sensitivity and specificity means, respectively. The k-NN computational analysis appears to be a promising approach to distinguish skin disorders. (C) 2017 Elsevier B.V. All rights reserved.