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Automated Quantification of Decreased Fundus Autofluorescence in Stargardt Disease Using Starguage: Validation against Manual Grading Standards

Year: 2026

Type: article

Abstract: Purpose: , a novel automated method, compared with manual segmentation for measuring decreased autofluorescence (DAF) and definitely decreased autofluorescence (DDAF) in fundus autofluorescence (FAF) images of patients with Stargardt disease. Design: A cross-sectional reproducibility and agreement study. Participants: A total of 316 eyes from 158 genetically confirmed Stargardt patients were analyzed. For intragrader repeatability, 114 FAF images were reassessed in a masked, repeated-measures design. Methods: Decreased autofluorescence and DDAF lesion areas were independently quantified by five certified graders using either manual delineation with Heidelberg RegionFinder or a threshold-based automated algorithm, with automated quantification and cross-method agreement analyses restricted to a prespecified central 6-mm fovea-centered region. Agreement and repeatability were assessed using intraclass correlation coefficients (ICCs), standard error of measurement (SEM), minimal detectable change (MDC), Lin's concordance correlation coefficient (CCC), Bland-Altman plots, and Passing-Bablok regression. Both raw and square-root-transformed lesion areas were evaluated. Main Outcome Measures: Repeatability (intragrader ICC, SEM, and MDC), reproducibility (intergrader ICC), and agreement (CCC and bias in regression analysis) between and within manual and automated methods. Results: ), with minimal operator influence. Manual measurements showed variable repeatability (DAF ICCs 0.909-0.974; DDAF ICCs as low as 0.837), with square-root transformation reducing SEM and MDC. Intergrader reproducibility was highest for automated methods (ICC = 0.988-0.992), whereas manual methods ranged from 0.764-0.939 (raw) and 0.867-0.922 (transformed). Cross-method agreement was strong (CCC = 0.91-0.96), though minor proportional and constant bias was observed in raw DAF data. Conclusions: The automated approach provides near-perfect repeatability and high agreement with manual grading, offering a scalable, objective alternative for quantifying hypo-auto-fluorescent lesions in Stargardt disease. Manual methods are generally reliable but more variable, especially for DDAF, and benefit from square-root transformation. Findings reflect a pediatric/adolescent single-trial predominantly Asian cohort. Financial Disclosures: The authors have no proprietary or commercial interest in any materials discussed in this article.

Source: Ophthalmology Science

DOI: 10.1016/j.xops.2026.101080