Automated Quantification of Decreased Fundus Autofluorescence in Stargardt Disease Using Starguage: Validation...

To evaluate the repeatability and reproducibility of Starguage, 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.

A cross-sectional reproducibility and agreement study.

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.

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.

Repeatability (intragrader ICC, SEM, and MDC), reproducibility (intergrader ICC), and agreement (CCC and bias in regression analysis) between and within manual and automated methods.

The automated method achieved excellent intragrader repeatability for both DAF and DDAF (ICCs ≥0.988, SEM ≤0.71 mm², MDC ≤1.98 mm²), 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.

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.

The authors have no proprietary or commercial interest in any materials discussed in this article.