Normative Cone Photoreceptor Distribution and the Relationship with Retinal Layer Thickness

Purpose: To establish a normative database of cone photoreceptor density across the macula in healthy eyes at a range of ages using adaptive optics scanning laser ophthalmoscopy (AOSLO). This dataset, composed of paired confocal and split-detection imaging, further investigates relationships between cone density and retinal layer thicknesses measured by optical coherence tomography (OCT), extending structural insights beyond those provided by recently published automated cone montage repositories. Methods: Forty-five healthy adults (21–64 years) were enrolled in this prospective cross-sectional study. One eye per subject was imaged with a custom dual-modality AOSLO. Cone mosaics were acquired across the central 10°, excluding the innermost ±0.5° of the fovea due to resolution limitations, and assembled into montage density maps. Cone identification was performed using a combination of automated algorithms and expert review. Cone densities were analyzed in relation to eccentricity, demographic and biometric factors, as well as co-localized OCT-derived retinal layer thicknesses. Results: Density profiles were symmetric across meridians, with substantial interindividual variability near the fovea. Age, sex, and refractive error showed no significant associations. Cone density correlated positively with the thicknesses of the outer nuclear layer and the photoreceptor–RPE complex layer, and negatively with the retinal nerve fiber layer thickness, while no association was found with the choroidal thickness. Conclusions: This work provides a normative reference of macular cone density that complements the recently published fully automated montage-based database by including direct structural correlations with OCT-derived retinal layers. Together, these resources broaden the foundation for early detection of photoreceptor abnormalities and evaluation of treatment effects in retinal disease. Translational Relevance: Parallel normative databases—one emphasizing large-scale automated montage availability and the other highlighting structure–function correlations—offer complementary benchmarks to support translation of adaptive optics imaging into clinical practice.