LAUSR

Diffuse reflectance spectroscopy (DRS) is a non-invasive, fast, and low-cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for non-melanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation, and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify [basal cell carcinoma (BCC), squamous cell carcinoma (SCC)] versus actinic keratosis (AK), and [BCC, SCC, AK] versus normal. The area under the Receiver Operating Characteristic curve (AUROC) achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis (PCA). Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. This article is protected by copyright. All rights reserved.