The Erythema Q-score, an Imaging Biomarker for Redness in Skin Inflammation.

BACKGROUND Physician rating of cutaneous erythema is central to clinical dermatological assessment as well as quantification of outcome measures in clinical trials in a number of dermatologic conditions. However, issues with interrater reliability and variability in the setting of higher Fitzpatrick skin types makes visual erythema assessment unreliable. AIM To develop and validate a computer-assisted image-processing algorithm (EQscore) to reliably quantify erythema (across a range of skin types) in the dermatology clinical setting. METHODS An image processing algorithm (EQscore) was developed to evaluate erythema based upon green-light suppression differentials between affected and unaffected skin. A group of 4 dermatologists used a 4-point Likert scale as a human evaluation of similar erythematous patch tests. Algorithm and dermatologist scores were compared across 164 positive patch test reactions. The intra-class correlation coefficient of groups and the correlation coefficient between groups were calculated. The EQscore was validated on and independent image set of psoriasis, minimal erythema dose testing, and steroid-induced blanching images. RESULTS The reliability of the erythema quantification method produced an intra-class correlation coefficient of 0.84 for the algorithm and 0.67 for dermatologists. The correlation coefficient between groups was 0.85. The EQscore was able to quantify erythema. CONCLUSION The EQscore demonstrated high agreement with clinical scoring and superior reliability compared with clinical scoring, avoiding the pitfalls of erythema underrating in the setting of pigmentation. The EQscore is easily accessible, user-friendly, and may allow dermatologists to more readily and accurately rate the severity of dermatological conditions and the response to therapeutic treatments.