Psoriasis is a common chronic inflammatory skin disease. Disease severity is commonly assessed using the Psoriasis Area and Severity Index (PASI), in which erythema is graded subjectively on a 0-4 scale. This visual assessment is prone to significant inter- and intra-rater variability. Although objective tools such as colorimeters provide accurate erythema measurement, their high cost limits routine clinical use. Smartphone imaging combined with artificial intelligence (AI) offers a practical alternative for objective assessment. However, variability in lighting conditions can affect image consistency. Incorporating a color calibration card enables accurate color normalization. This study aims to develop and validate an AI-based system for measuring erythema in psoriatic lesions using smartphone images with a color card, compared against a standard colorimeter to assess validity and reliability.
Study Type
OBSERVATIONAL
Enrollment
50
This study is distinct from other clinical studies in that it does not involve any therapeutic intervention or modification of standard patient care. Instead, it evaluates a non-invasive, image-based measurement system that combines smartphone photography, a color calibration card, and artificial intelligence to quantify erythema in psoriasis lesions. Unlike conventional approaches that rely on subjective physician scoring or require specialized and costly equipment, this intervention is designed to be low-cost, accessible, and applicable in real-world settings, including patient self-monitoring at home.
Khon Kaen University
Khon Kaen, Changwat Khon Kaen, Thailand
To evaluate the accuracy of erythema measurements of psoriatic lesions obtained from an AI-based erythema model (smartphone imaging with a color calibration card) compared with a standard color calibration device (gold standard).
Time frame: From enrollment to 12 weeks
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