Abstract
Purpose: :
Primary angle closure glaucoma (PACG) is a leading cause of blindness worldwide, especially in Asian countries. PACG is not a single disease entity with single mechanism and thus can be classified into several subtypes according to main contributing pathogenic mechanism. We intended to search for the possibility of classifying the PACG using the parameters determined by anterior segment optical coherence tomography (AS OCT) and statistical modeling.
Methods: :
PAC or PACG eyes diagnosed by clinical examination were imaged using AS OCT at same lighting condition. Anterior chamber depth (ACD), iris cross-sectional area (IA), iris thickness at 750 microns from the scleral spur (IT), iris curvature (IC), anterior chamber width (ACW), lens vault (LV) and anterior chamber area (ACA), were determined using Image J software (version 1.44, National Institutes of Health). A cluster analysis (R 2.13.1. ) was run on 278 PAC or PACG eyes based on those parameters from AS OCT.
Results: :
A hierarchical cluster analysis using Ward's method produced three clusters, among which the variables were significantly different in the main. The first cluster was characterized by high ACW, low LV, and high IA (mean ± standard deviation, 11.4±0.36 mm, 0.88±0.22 mm, and 2.38±0.47mm2). The second cluster was characterized by low ACW, low LV, and low IA (10.6±0.35 mm, 0.89±0.28 mm, and 2.21±0.36mm2). The third cluster was characterized by high LV and low IA (1.35±0.23 mm and 2.29±0.46mm2).
Conclusions: :
A cluster analysis based on AS OCT parameter categorized three types of PAC/PACG. Three types were mainly characterized by increased IA, reduced ACW and increased LV, respectively. Those three characteristics might be related to pathogenic mechanism of PAC/PACG. AS OCT parameters might be applied to classify PAC/PACG into subtypes.
Keywords: imaging/image analysis: clinical • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound)