Abstract
Purpose :
To provide an understanding of the natural history in geographic atrophy (GA) secondary to age-related macular degeneration by investigating retinal morphology changes particularly within the photoreceptor (PR) and retinal pigment epithelium (RPE) layers using advanced automatic OCT segmentation in data from a real-world cohort
Methods :
A retrospectively collected dataset of 388 GA patients was evaluated for longitudinal changes in the macular structure. Automatic measurements of GA patients imaged with star pattern OCT scans centered on the fovea, with at least 2 visits over a period of up to 4 years, was conducted to determine the extent and loss of both the inner and outer retinal layers particularly focusing on the PR layer and myoid zone (MZ) and the RPE. Further measurements involved drusen, pigment epithelial detachment (PED) and amorphous material (AM) such as outer retina material that were no longer identified as intact retinal structures, including subretinal hyperreflective material (SHRM) and fibrosis. For each measured biomarker the mean and maximum horizontal loss, or the extent of change per year were calculated. Visits were aligned with the baseline visit
Results :
3317 OCT scans were analyzed over a mean of 887 (SD of 463) follow-up days. The mean (SD) change in mm per year demonstrated a depletion extent of RPE: 0.16 (0.51); PR: 0.20 (0.63); MZ: 0.22 (0.69); an extent of PED: 0.07 (0.57) and AM: 0.10 (0.86). The MZ layer appeared to attenuate first, followed by the photoreceptors, and finally RPE layer over time (Figure 1). The direction of atrophy progression finding was in line with the atrophy being considered complete when the RPE layer is attenuated. Automatic OCT segmentation facilitated an understanding of disease processes in a large longitudinal data set
Conclusions :
The natural history of disease progression within the MZ, PR and RPE layers is essential for disease and treatment success assessment in GA, and Automatic OCT segmentation a key support
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.