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Visual assessment is the most common clinical investigation of skin reactions in radiotherapy. Due to the subjective nature of this method, additional noninvasive techniques are needed for more accurate evaluation. Our goal is to evaluate the effectiveness of hyperspectral image analysis for that purpose. In this pilot study, we focused on detection and grading of skin Erythema. This paper reports our proposed processing pipeline and experimental findings. Experiments have been performed to demonstrate the efficacy of the proposed approach for (1) reproducing clinical assessments, and (2) outperforming RGB imaging data.

Erythema is an inflammatory condition of the skin that is commonly used as a feature to monitor the progression of cutaneous diseases or treatment induced side effects. In radiation therapy, skin erythema is routinely assessed visually by an expert using standardized grading criteria. However, visual assessment (VA) is subjective and commonly used grading tools are too coarse to score the onset of erythema. Therefore, an objective method capable of quantitatively grading early erythema changes may help identify patients at higher risk for developing severe radiation induced skin toxicities. The purpose of this study is to investigate the feasibility of using hyperspectral imaging (HSI) for quantitative assessment of early erythema and to characterize its performance against VA documented on conventional digital photographic red-green-blue (RGB) images. Erythema was induced artificially on 3 volunteers in a controlled pilot study; and was subsequently measured using HSI and color imaging. HSI and color imaging data was analyzed using linear discriminant analysis (LDA) to perform classification. The classification results, including accuracy, and precision, demonstrated that HSI is superior to color imaging in skin erythema assessment.

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