Purpose. We assessed the relationship between retinal structures measured by spectral-domain optical coherence tomography (SD-OCT) and visual acuity in open-angle glaucoma (OAG) patients. Methods. In this cross-sectional observational study, 186 eyes from 186 OAG patients were included. The participants underwent RTVue OCT for measurement of circumpapillary retinal nerve fiber layer (cpRNFL) thickness and macular ganglion cell complex (mGCC) thickness. The correlations between best-corrected visual acuity (BCVA) and optical coherence tomography (OCT) parameters were evaluated using Pearson's partial correlation test and regression analysis. Receiver operating characteristic (ROC) curve analysis was performed to obtain a cutoff value for OCT parameters in detecting decreased visual acuity (BCVA < 0.7). Results. Among RNFL parameters, average RNFL thickness (r = -0.447, P < 0.001) showed the highest correlation with BCVA, followed by superior hemisphere (r = -0.440, P <0.001), and TU1 (67.5°-90°, r = -0.427, P < 0.001), TU2 (45°-67.5°, r = -0.408, P < 0.001), and TL1 (90°-112.5°, r = -0.40, P < 0.001) sectors. When logMAR BCVA was plotted against average RNFL/ganglion cell complex (GCC) thickness, second-order polynomial models fit better than the linear model. The areas under the receiver operating characteristic curves (AUROCs) of the average RNFL/GCC thickness were 0.910 (95% confidence interval [CI], 0.856-0.965) and 0.874 (95% CI, 0.795-0.953), respectively. Conclusions. The relationship between BCVA and SD-OCT parameters were curvilinear, and significant correlations were noted only in eyes with severe glaucoma. The global average cpRNFL thickness showed the highest correlation with BCVA rather than TU1, TL1 sectors, or GCC parameters. Considering the wide variability of structure-visual acuity relationship in glaucoma patients, the clinicians should take other variables into account to predict the visual acuity in advanced glaucoma patients.
All Science Journal Classification (ASJC) codes
- Sensory Systems
- Cellular and Molecular Neuroscience