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)

Issue		Eur. Phys. J. Appl. Phys. Volume 47, Number 1, July 2009 4th Colloquium Interdisciplinary in Instrumentation (C2I)


Article Number		12707
Number of page(s)		12
Section		4th Colloquium Interdisciplinary in Instrumentation (C2I 2007)
DOI		10.1051/epjap/2009032
Published online		15 April 2009

Eur. Phys. J. Appl. Phys. 47, 12707 (2009)
DOI: 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)

G. Díaz-Ayil¹, M. Amouroux¹, W.C.P.M. Blondel¹, G. Bourg-Heckly², A. Leroux³, F. Guillemin^{1, 3} and Y. Granjon¹

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

walter.blondel@ensem.inpl-nancy.fr

Received: 1st June 2008 / Received in final form: 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 $\approx$ 100% when discriminating CH vs. others; Sp $\approx$ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp $\approx$ 74% and Se $\approx$ 63%for AH vs. D.

PACS
87.64.-t - Spectroscopic and microscopic techniques in biophysics and medical physics.
87.80.-y - Biophysical techniques (research methods).
07.60.-j - Optical instruments and equipment.

© EDP Sciences 2009

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