Abstract
Purpose :
Optical coherence tomography angiography (OCTA) has enabled accurate visualization and quantification of the radial peripapillary capillaries (RPC), which provide valuable functional information in disease processes such as glaucoma. Using OCTA, we characterize the RPC density across the posterior pole in healthy eyes, and its relationship with retinal nerve fiber layer (NFL) thickness.
Methods :
Four 4.5 x 4.5 mm overlapping scans using a commercial OCTA system were obtained in the right eye and montaged to form a wide-field angiogram centered on the optic disc of 9 health participants. A semi-automated segmentation algorithm isolated the RPC based on structural OCT and produced en face angiograms. The proportion of flow pixels within each grid element (8×8-pixel) was used to create RPC density maps, which were then aligned to generate an averaged RPC density map. An average NFL thickness map was created using the same OCT data set. Averaged density and thickness maps were spatially divided into small, radially arranged sections to facilitate quantitative assessment of the relationship between RPC density and NFL thickness.
Results :
The RPC density was greatest in the superior temporal and inferior temporal perpapillary regions in a similar pattern as the NFL thickness (Fig. 1). RPC density decreased with distance from the optic disc, but more slowly than the NFL thickness. Dense RPC can be found along the arcuate bundles more than 6mm from the disc center. RPC density and NFL thickness were nonlinearly related, RPC density reaching a ceiling of 80% when NFL thickness was greater than 100 μm. A nonlinear fit of RPC density on NFL thickness provides a high correlation (R2 = 0.96).
Conclusions :
The RPC density follows a bi-arcuate distribution pattern similar to the NFL thickness but attenuates more slowly with distance from the disc. It could be measured by OCTA in a large peripapillary area. Wide-field RPC density maps may be useful for the evaluation of retinal nerve fiber metabolism and function.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.