Surgical resection of skin cancer implies safety margins delineation: currently, surgeons have no diagnostic aid to narrow or widen such margins if necessary. A promising approach is the use of optical methods, which can be used non-invasively and offer real-time diagnostic assistance.
This study presents the results of classification of autofluorescence (AF) and diffuse reflectance (DR) spectra obtained in vivo on skin Basal Cell Carcinomas (BCC) and Squamous Cell Carcinomas (SCC), Actinic Keratoses (AK) and Healthy skin (H) of 140 patients. The bimodal spectroscopic instrument used in this study uses five LEDs for fluorescence excitation at wavelengths peaks between 365 and 415 nm, and a xenon lamp featuring 350-800 nm emission range to obtain AF and DR spectra for four source-detector distances (from 400 to 1000 μm).
The classification (C vs H, H vs AK) was done by support vector machine, discriminant analysis, and multilayer perceptron. Final accuracy of two-class classification tests for almost all pairs of classes was more than 80%. This study presents a comparison of the performance of these combination of methods with the standard clinical procedure.
Information on skin phototype and ages is of cosmetic and medical interest in some procedures like objective evaluation of cosmetic treatments effectiveness, laser wavelength choice, risk of skin cancer recurrence and skin evaluation before cosmetic surgeries. Phototype may be evaluated using the Fitzpatrick questionnaire whose results are impaired by patients’ subjective answers; melanometers may be used but are not always available in dermatology practice. Tewameter, corneometer or cutometer are used to evaluate skin features that may be related to skin age but they lack evaluation of skin internal structure directly related to skin age (fibrosis, elastosis, etc.). Optical spectroscopy combining autofluorescence (AF) and diffuse reflectance (DR) may be a promising and non-invasive alternative to these tests.
In the current study, a bimodal spectroscopic device was used to obtain in vivo spatially resolved AF and DR spectra of skin in the visible range. Five LEDs featuring wavelength peaks at 365, 385, 395, 400 and 415 nm and a xenon lamp featuring a 350-800 nm spectral emission were used as light sources. Four source-detector separation (SDS) were used: 400, 600, 800, and 1000 μm.
Spectra were taken in different anatomical sites on 131 patients of different age and gender during a clinical study. Spectra were analysed using classification (support vector machine and multilayer perceptron) and regression (multilayer perceptron, linear, kernel ridge and Lasso) methods. Results of skin phototype and age estimation from AF and DR spectra obtained in vivo using machine learning methods will be presented and discussed.
The aim of the current study is to evaluate the classification accuracy and provide corresponding biological interpretation of four classification methods used on autofluorescence (AF) and diffuse reflectance (DR) spectra acquired in vivo on healthy human skin of different phototypes, civil and apparent age groups. Spectroscopic data were acquired on 91 patients using the SpectroLive device. The latter spatially and spectrally-resolved device features four source-to-detector distances (D1-D4) and six excitation light sources: 5 peaks for AF and one broadband white light for DR. For all patients, spectra were acquired on two healthy skin sites i.e. hand palm and inner wrist chosen for their low sun exposure. Four classification methods were tested: Support Vector Machine, K-Nearest Neighbors, Linear Discriminant Analysis and Artificial Neural Network. All combinations of excitation wavelengths, distances and skin sites acquisition were tested to find out the best classification results following a training step on 67 % of the dataset and a validation step on 33 % of the dataset. Classification accuracies were compared using Principal Components Analysis and statistical features. For civil and biological skin age groups discrimination, best classification results (70 % and 76 % respectively) were obtained when combining autofluorescence spectral features from three excitation wavelengths (385, 395 and 405 nm) all acquired at the shortest distance (400 µm) on hand palm. The combination of AF, inner wrist and the longest distance (1 mm) gave the best classification results (76 %) for phototype groups discrimination.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.