Modelling normal age-related changes in individual retinal layers using location-specific OCT analysis

Author:

Trinh Matt,Khou Vincent,Zangerl Barbara,Kalloniatis Michael,Nivison-Smith Lisa

Abstract

AbstractCurrent descriptions of retinal thickness across normal age cohorts are mostly limited to global analyses, thus overlooking spatial variation across the retina and limiting spatial analyses of retinal and optic nerve disease. This retrospective cross-sectional study uses location-specific cluster analysis of 8 × 8 macular average grid-wise thicknesses to quantify topographical patterns and rates of normal, age-related changes in all individual retinal layers of 253 eyes of 253 participants across various age cohorts (n = 23–69 eyes per decade). Most retinal layers had concentric spatial cluster patterns except the retinal nerve fibre layer (RNFL) which displayed a nasal, asymmetric radial pattern. Age-related thickness decline mostly occurred after the late 4th decade, described by quadratic regression models. The ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), and outer nuclear layer + Henle’s fibre layer (ONL+HFL) were significantly associated with age (p < 0.0001 to < 0.05), demonstrating similar rates of thickness decline (mean pooled slope =  − 0.07 µm/year), while the IS/OS had lesser mean pooled thickness slopes for all clusters (− 0.04 µm/year). The RNFL, OPL, and RPE exhibited no significant age-related thickness change, and the RNFL were significantly associated with sex. Analysis using spatial clusters compared to the ETDRS sectors revealed more extensive spatial definition and less variability in the former method. These spatially defined, clustered normative data and age-correction functions provide an accessible method of retinal thickness analysis with more spatial detail and less variability than the ETDRS sectors, potentially aiding the diagnosis and monitoring of retinal and optic nerve disease.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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