Quantifying changes on optical coherence tomography in eyes receiving treatment for neovascular age-related macular degeneration

Purpose

Application of artificial intelligence (AI) to macular optical coherence tomography (OCT) scans to segment and quantify volumetric change of anatomical and pathological features during intravitreal treatment for neovascular age-related macular degeneration (AMD).

Design

Retrospective analysis of OCT images from the Eye Hospital AMD Database.

Participants

2115 eyes from 1883 patients that started anti-vascular endothelial growth factor (anti-VEGF) treatment between 1st June 2012 and 30th June 2017.

Methods

The Eye Hospital neovascular AMD database was queried for first and second eyes that received anti-VEGF treatment and had an OCT scan at baseline and at 12 months. Follow-up scans were input into the AI system to derive volumetric outputs for the following variables: intraretinal fluid (IRF), subretinal fluid (SRF), pigment epithelial detachment (PED), subretinal hyperreflective material (SHRM), hyperreflective foci (HRF), neurosensory retina (NSR) and retinal pigment epithelium (RPE). Volumes were studied at different time points and comparisons made with respect to baseline volume groups. Cross-sectional comparisons between time points were conducted using Mann-Whitney U test.

Results

Mean volumes of analysed features decreased significantly from baseline to both four and 12 months, in both first and second-treated eyes. Pathological features that reflect exudation, including pure fluid components (IRF and SRF) and those with a mixture of fluid and fibrovascular tissue (PED and SHRM), displayed similar response to treatment over 12 months. Mean PED and SHRM volumes showed less pronounced but also substantial decreases over the first two months, reaching a plateau post loading phase, and minimal change to 12 months. Both NSR and RPE volumes showed gradual reductions over time, and not as substantial as exudative features.

Conclusion

We report the results of a quantitative analysis of change in retinal segmented features over time, enabled by an AI segmentation system. Cross-sectional analysis at multiple time points demonstrated significant associations between baseline OCT-derived segmented features and the volume of biomarkers at follow-up. Demonstrating how certain OCT biomarkers progress with treatment and the impact of pre-treatment retinal morphology on different structural volumes may provide novel insights into disease mechanisms and aid personalization of care. Data will be made public for future studies.

Methods

The dataset comprises anonymised metadata and OCT segmentation data of patients undergoing treatment for wet AMD.