Predictive Biomarker for Progression Into the Sunset Glow Fundus of Vogt-Koyanagi-Harada Disease, Using Adaptive Binarization of Fundus Photographs.

Purpose: The sunset glow fundus (SGF) appearance in Vogt-Koyanagi-Harada (VKH) disease was evaluated by means of adaptive binarization of patients' fundus photographs. Methods: Twenty-nine Japanese patients with acute VKH were enrolled in this study. We evaluated one eye of each patient, and thereby divided the patients into two groups; SGF+ and SGF- at 6 months after treatment. We compared patient age, gender, and spherical equivalent refractive error (SERE) and choroidal thickness measured using optical coherence tomography. We also compared the choroidal vascular appearance index (CVAI), derived by adaptive binarization image processing of fundus photographs, between the two groups. Measurements of choroidal thickness and CVAI were taken at the onset of disease, and 1, 3, and 6 months after treatment. The sunset glow index (SGI), as previously reported, was calculated using color fundus photographs, and compared to the CVAI. Results: Eight patients (27.6%) were categorized into the SGF+ group. At all time points, the mean CVAI in the SGF+ group was significantly greater than that in the SGF- group. No significant difference was observed in choroidal thicknesses at any time point. The SGI was significantly greater in the SGF+ group at 6 months. Conclusions: CVAI could be a new predictive biomarker for the development of SGF in patients with VKH disease. Translational Relevance: Detecting SGF is important for management of patients with VKH, and CVAI may indicate the possibility of developing into SGF, although the color fundus photographs do not yet show SGF at that time.