Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina.

This study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment-outer segment (ISOS) layer measurements were extracted using a customized high-density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age-related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann-Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity-dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age-related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high-resolution OCT data, and correction for demographics-related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.