Unsupervised Classification of Wide-Field Swept-Source Optical Coherence Tomography Reveals Patterns Associated With Glaucoma Severity and Progression

Purpose: We investigated the structural patterns associated with visual field (VF) progression using a novel unsupervised hybrid clustering approach that combined archetypal analysis (AA) and fuzzy c-means (FCM). Methods: AA was used to identify the representative structural archetypes (ATs) from 1803 wide-field swept-source optical coherence tomography (SS-OCT) scans obtained from 1803 eyes of 1167 patients with glaucoma or suspected glaucoma, resulting in 10 distinct ATs. Subsequently, FCM was used to calculate the decomposition coefficients of each eye. A subset of 372 eyes with at least five reliable 24-2 VF tests was analyzed to evaluate the association between baseline structural patterns and subsequent VF progression. Progression was defined using three criteria: mean deviation slope, Visual Field Index slope, and pointwise linear regression. Results: We observed stage-dependent differences in archetypal expression. Greater baseline AT9 (bihemiretinal loss) was significantly associated with VF progression in glaucoma suspect eyes; greater baseline AT4 (early superior loss) and AT9 in early glaucoma; and lower baseline AT1 (normal) and greater baseline AT5 (superior hemiretinal loss) in moderate-to-advanced glaucoma. Only 4.3% of eyes met all three VF progression criteria, whereas 81.7% met none, highlighting substantial discordance among definitions. Conclusions: These findings suggest that the structural patterns associated with VF progression differ according to disease stage and progression criteria. Our hybrid unsupervised method offers a clinically interpretable framework that may facilitate real-time structural assessment and personalized glaucoma monitoring. Translational Relevance: Hybrid approach combining AA and FCM visualize wide-field SS-OCT images in characteristic patterns. It enables the identification of high-risk eyes in the early phase and allows for individualized patient monitoring.