Anterior Segment Imaging-based Subgrouping of Primary Angle Closure Glaucoma

Abstract

Purpose: We recently showed that it was possible to subgroup primary angle closure suspects (PACS) based on anterior segment optical coherence tomography (ASOCT) imaging. The purpose of this study was to identify whether this was also credible for primary angle-closure glaucoma (PACG); and to determine the characteristics of such subgroups.

Methods: We evaluated 210 PACG subjects. All subjects underwent gonioscopy and ASOCT imaging (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters. An agglomerative hierarchical clustering method was first used to determine the optimum number of parameters to be included in the determination of subgroups. Then the best number of subgroups was determined using Akaike Information Criterion (AIC) and Gaussian Mixture Model (GMM) methods.

Results: The mean age of the subjects was 68.3 years, and 60.2% were female. After hierarchical clustering, either 1 or 2 parameters from each cluster were chosen to be representative of related parameters. The parameters included were iris area, anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). The optimal number of subgroups using GMM analysis and AIC was 3. Subgroup 1 (N=89; 42.4%) was characterized by a large iris area, subgroup 2 (N=24; 11.4%) by a large LV and a shallow ACD, whereas subgroup 3 (N=97; 46.2%) displayed only intermediate values across iris area, LV and ACD.

Conclusions: Mirroring our findings for PACS, we also identified three distinct subgroups of PACG subjects based on ASOCT imaging.

Keywords: 421 anterior segment • 550 imaging/image analysis: clinical • 464 clinical (human) or epidemiologic studies: risk factor assessment