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

Authors

Hwayeong Kim, Sangwoo Moon, EunAh Kim, Jiwon Lee, Giltae Song, Jiwoong Lee

Published in

Translational vision science & technology. Volume 15. Issue 10. Pages 25. Oct 05, 2026.

Abstract

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).
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.
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.
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.
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.

PMID:
42885983
Bibliographic data and abstract were imported from PubMed on 16 Oct 2026.

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