A Hierarchical Cluster Analysis of Primary Angle Closure Classification Using Anterior Segment Optical Coherence Tomography Parameters

Abstract

To investigate the possibility of classifying angle closure eyes in terms of features provided by anterior segment optical coherence tomography (AS OCT). Angle closure (primary angle closure [PAC] or PAC glaucoma [PACG]) eyes diagnosed by gonioscopy were imaged using AS OCT under the same lighting conditions. Anterior chamber depth (ACD), anterior chamber width (ACW), iris cross-sectional area (IA), iris thickness at 750 μm from the scleral spur (IT750), iris curvature (IC), lens vault (LV), and anterior chamber area (ACA) were determined using Image J software (ver. 1.44). A hierarchical cluster analysis using Ward's method was performed using AS parameters obtained by AS OCT and axial length (AXL). A hierarchical cluster analysis was performed on 166 angle closure eyes and produced two clusters. The first cluster (84 eyes) was characterized by higher ACD (2.24 mm), higher ACA (12.5 mm(2)), higher IT750 (0.44 mm), higher ACW (11.2 mm), lower LV (0.85 mm), and higher AXL (23.5 mm) compared with the second cluster (82 eyes, 1.82 mm, 9.5 mm(2), 0.38 mm, 10.8 mm, 1.1 mm, and 22.8 mm, respectively). The second cluster had essentially higher LV and lower ACA than the first cluster. Most parameters were significantly different between two clusters except IC (P = 0.76). Our hierarchical cluster analysis indicated two clusters with quite different features existed in our total angle closure population. Our results suggest the possibility of subclassifying angle closure eyes according to AS OCT parameters.