Semiautomated segmentation and analysis of retinal layers in three-dimensional spectral-domain optical coherence tomography images of patients with atrophic age-related macular degeneration.

Historically, regular drusen and geographic atrophy (GA) have been recognized as the hallmarks of nonneovascular age-related macular degeneration (AMD). Recent imaging developments have revealed another distinct nonneovascular AMD phenotype, reticular pseudodrusen (RPD). We develop an approach to semiautomatically quantify retinal surfaces associated with various AMD lesions (i.e., regular drusen, RPD, and GA) in spectral domain (SD) optical coherence tomography (OCT) images. More specifically, a graph-based algorithm was used to segment multiple retinal layers in SD-OCT volumes. Varying surface feasibility constraints based on the presegmentation were applied on the double-surface graph search to refine the surface segmentation. The thicknesses of these layers and their correlation with retinal functional measurements, including microperimetry (MP) sensitivity and visual acuity (VA), were investigated. The photoreceptor outer segment layer demonstrated significant thinning with a reduction in MP sensitivity and VA score when atrophic AMD lesions were present. Regular drusen and RPD were separately segmented on SD-OCT images to allow their characteristics and distribution to be studied separately. The mean thickness of regular drusen was found to significantly correlate with the VA score. RPD appeared to be distributed evenly throughout the macula and regular drusen appeared to be more concentrated centrally.