Eur. Phys. J. Appl. Phys. 47, 12707 (2009)
https://doi.org/10.1051/epjap/2009032

Bimodal spectroscopic evaluation of ultra violet-irradiated mouse skin inflammatory and precancerous stages: instrumentation, spectral feature extraction/selection and classification (k-NN, LDA and SVM)

¹ Centre de Recherche en Automatique de Nancy, CRAN UMR 7039 CNRS, Nancy University, 2 av. de la Forêt de Haye, 54516 Vandœuvre-lès-Nancy, France
² Laboratoire de Biophysique Moléculaire, Cellulaire et Tissulaire, BioMoCeTi UMR 7033 CNRS, Université Pierre et Marie Curie Paris 6, Génopôle Campus 1, 5 rue Henri Desbruères, 91030 Évry Cedex, France
³ Centre Alexis Vautrin, 6 av. de Bourgogne, 54511 Vandœuvre-lès-Nancy Cedex, France

Corresponding author: walter.blondel@ensem.inpl-nancy.fr

Received: 1 June 2008
Revised: 8 October 2008
Accepted: 10 December 2008
Published online: 15 April 2009

Abstract

This paper deals with the development and application of in vivo spatially-resolved bimodal spectroscopy (AutoFluorescence AF and Diffuse Reflectance DR), to discriminate various stages of skin precancer in a preclinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A programmable instrumentation was developed for acquiring AF emission spectra using 7 excitation wavelengths: 360, 368, 390, 400, 410, 420 and 430 nm, and DR spectra in the 390–720 nm wavelength range. After various steps of intensity spectra preprocessing (filtering, spectral correction and intensity normalization), several sets of spectral characteristics were extracted and selected based on their discrimination power statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of sensitivity (Se) and specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibers distances and of the numbers of principal components, such that: Se and Sp ≈ 100% when discriminating CH vs. others; Sp ≈ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ≈ 74% and Se ≈ 63% for AH vs. D.