Reliability and agreement testing of a new automated measurement method to determine facial vitiligo extent using standardized ultraviolet images and a dedicated algorithm

Abstract

Abstract Background Facial repigmentation is the primary outcome measure for most vitiligo trials. The Facial Vitiligo Area Scoring Index (F-VASI) score is often chosen as the primary outcome measure to assess the efficacy of treatments for facial vitiligo. Although useful, this scoring system remains subjective and has several limitations. Objectives To assess the agreement and reliability of an algorithmic method to measure the percentage depigmentation of vitiligo on the face. Methods We developed a dedicated algorithm called Vitil-IA® to assess depigmentation on standardized facial ultraviolet (UV) pictures. We then conducted a cross-sectional study using the framework of the ERASE trial (NCT04843059) in 22 consecutive patients attending a tertiary care centre for vitiligo. Depigmentation was analysed before any treatment and, for 7 of them, after 3 and 6 months of narrowband UVB treatment combined with 16 mg methylprednisolone, both used twice weekly. Interoperator and interacquisition repeatability measures were assessed for the algorithm. The results of the algorithmic measurement were then compared with the F-VASI and the percentage of depigmented skin scores assessed by 13 raters, including 7 experts in the grading of vitiligo lesions. Results Thirty-one sets of pictures were analysed with the algorithmic method. Internal validation showed excellent reproducibility, with a variation of < 3%. The percentage of depigmentation assessed by the system showed high agreement with the percentage of depigmentation assessed by raters [mean error (ME) –11.94 and mean absolute error (MAE) 12.71 for the nonexpert group; ME 0.43 and MAE 5.57 for the expert group]. The intraclass correlation coefficient (ICC) for F-VASI was 0.45 [95% confidence interval (CI) 0.29–0.62] and 0.52 (95% CI 0.37–0.68) for nonexperts and experts, respectively. When the results were analysed separately for homogeneous and heterogeneous depigmentation, the ICC for homogeneous depigmentation was 0.47 (95% CI 0.31–0.77) and 0.85 (95% CI 0.72–0.94) for nonexperts and experts, respectively. When grading heterogeneous depigmentation, the ICC was 0.19 (95% CI 0.05–0.43) and 0.38 (95% CI 0.20–0.62) for nonexperts and experts, respectively. Conclusions We demonstrated that the Vitil-IA algorithm provides a reliable assessment of facial involvement in vitiligo. The study underlines the limitations of the F-VASI score when performed by nonexperts for homogeneous vitiligo depigmentation, and in all raters when depigmentation is heterogeneous.