Abstract
Purpose :
In this work, we have investigated the possibility to visualize retinal pigment epithelium (RPE) cells in healthy subjects with single-volume adaptive optics optical coherence tomography (AO-OCT) images recorded at an extended field of view (FoV).
Methods :
We used a spectral domain AO-OCT setup that supports an imaging beam diameter of 7 mm while maintaining a FoV of ~4°x4°. The instrument provides an axial resolution of 4.5 μm at 840 nm central wavelength and an A-scan rate of 250 kHz. For AO correction mainly backscattered light originating from the RPE layer is used in order to obtain the highest sharpness from this layer. Retinal images were recorded in the fovea of several healthy volunteers and segmentation of the photoreceptor and RPE layers allows for their en-face visualization. All results presented are extracted from single shot 3-D volumes and no averaging was applied.
Results :
Representative image data displayed in the figure show en-face images of the cone outer segment tips (COST) and the RPE layer. The cone mosaic is well visualized within the entire FoV apart from a small region of 0.5° eccentricity from the fovea centralis. The power spectra of regions of interest show the ability of the instrument to resolve the photoreceptors and RPE cells. From the RPE layer, a lower spatial frequency is obtained than from the equivalent section in the COST layer indicating a lower packing density of the RPE cells compared to the cones. The visualization of the RPE mosaic from single-shot data was achieved for all subjects. From the data cell densities could be retrieved that are consistent with previous studies.
Conclusions :
The photoreceptor and RPE layers can be visualized in single volume AO-OCT images at a large field of view. Through power spectra analysis the different row-to-row spacings could be identified for several subjects. The extended field of view facilitates the exact determination of the imaging location and enables the acquisition of large patches (>10°) of the retina with cellular resolution via image stitching.
This is a 2020 ARVO Annual Meeting abstract.