Abstract
Purpose :
Gonioscopy is the clinical standard for evaluating the anterior chamber to detect individuals at risk for primary angle closure glaucoma (PACG), a common cause of blindness worldwide. However, gonioscopy appears poorly predictive of elevated intraocular pressure (IOP) and development of PACG. In this study, we use population-based anterior segment optical coherence tomography (AS-OCT) imaging data to identify biometric determinants of IOP in order to advance understanding about disease mechanisms and refine clinical management.
Methods :
Study data was obtained from the population-based Chinese American Eye Study (CHES). CHES participants underwent complete ocular exams, including Goldmann applanation tonometry, gonioscopy, and AS-OCT imaging, which was used to characterize the angle configuration. One eye per participant was included in the analysis. Biometric parameters, including trabecular iris space area (TISA750), iris area (IA), lens vault (LV), lens tilt (LT), anterior chamber depth (ACD), iris curvature (IC) were used to develop linear multivariable regression models to predict IOP. Different TISA750 cutoffs were used to determine a threshold at which models were more predictive of IOP. Models with cumulative gonioscopy score, calculated as the sum of gonioscopy measurements, were also developed.
Results :
Data from 2360 participants were analyzed (1518 female, 842 male). Mean age was 60.2 ± 7.8 years old. Multivariable linear regression models showed that below a TISA750 cutoff of 0.08 mm2, models grew increasingly predictive of IOP (R2 from 0.14 to 0.40, Figure 1). At TISA750 less than 0.10 mm and 0.05 mm, TISA750 (SRC = -0.219 and -0.085, respectively) and IA (SRC = -0.133 and -0.085, respectively) were the strongest determinants of IOP (p<0.05). Cumulative gonioscopy score was poorly predictive of IOP (R2 from 0.02 to 0.05) below any cutoff.
Conclusions :
Below particular angle width cutoffs, biometric factors, specifically TISA750 and IA, significantly predict IOP. Gonioscopy is poorly predictive of IOP below any cutoff. These findings suggest that biometric analysis of AS-OCT images could help identify patients at higher risk for elevated IOP and glaucoma.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.