Subgrouping of primary angle-closure suspects based on anterior segment optical coherence tomography parameters

Area of Science:

• Ophthalmology
• Medical Imaging
• Biometry

Background:

• Primary angle-closure suspects (PACS) represent a heterogeneous group.
• Understanding PACS heterogeneity is crucial for effective management and preventing vision loss.
• Anterior segment optical coherence tomography (AS-OCT) provides detailed anatomical measurements.

Purpose of the Study:

• To identify distinct subgroups within primary angle-closure suspects (PACS).
• To utilize anterior segment optical coherence tomography (AS-OCT) and biometric parameters for subgroup identification.
• To validate the identified subgroups in an independent cohort.

Main Methods:

• Cross-sectional study involving 243 PACS subjects (primary group) and 165 (validation group).
• AS-OCT and gonioscopy were performed; customized software measured anterior segment parameters.
• Agglomerative hierarchical clustering, Akaike Information Criterion (AIC), and Gaussian Mixture Model (GMM) were used for subgroup determination.

Main Results:

• Hierarchical clustering selected iris area, anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV) as key parameters.
• Gaussian Mixture Model analysis, guided by AIC, identified 3 optimal PACS subgroups.
• Subgroup 1: large iris area; Subgroup 2: large LV and shallow ACD; Subgroup 3: combination of both.
• Findings were successfully replicated in the independent validation group.

Conclusions:

• Clustering analysis successfully delineated 3 distinct subgroups of PACS based on AS-OCT and biometric data.
• These identified subgroups offer a refined classification of PACS.
• The findings have potential implications for understanding the pathogenesis and guiding the management of angle-closure glaucoma.