Quantitative analysis of optical coherence tomography for neovascular age-related macular degeneration using deep learning
Abstract
Purpose: To apply a deep learning algorithm for automated, objective, and comprehensive quantification of optical coherence tomography (OCT) scans to a large real-world dataset of eyes with neovascular age-related macular degeneration (AMD), and make the raw data openly available for further research.
Design: Retrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database.
Participants: 2473 first-treated eyes and 493 second-treated eyes that commenced therapy for neovascular AMD between June 2012 and June 2017.
Methods: A deep learning algorithm was used to segment all baseline OCT scans. Volumes were calculated for segmented features such as neurosensory retina (NSR), drusen, intraretinal fluid (IRF), subretinal fluid (SRF), subretinal hyperreflective material (SHRM), retinal pigment epithelium (RPE), hyperreflective foci (HRF), fibrovascular pigment epithelium detachment (fvPED), and serous PED (sPED). Analyses included comparisons between first and second eyes, by visual acuity (VA) and by ethnicity, and correlations between volumes.
Main outcome measures: Volumes of segmented features (mm3), central subfield thickness (CST) (μm).
Results: In first-treated eyes, the majority had both IRF and SRF (54.7%). First-treated eyes had greater volumes for all segmented tissues, with the exception of drusen, which was greater in second-treated eyes. In first-treated eyes, older age was associated with lower volumes for RPE, SRF, NSR and sPED; in second-treated eyes, older age was associated with lower volumes of NSR, RPE, sPED, fvPED and SRF. Eyes from black individuals had higher SRF, RPE and serous PED volumes, compared with other ethnic groups. For almost all features, greater volumes of each feature were associated with worse VA.
Conclusion: We report the results of large scale, novel, automated quantification of baseline features in neovascular AMD. Major differences between first and second-treated eyes, with increasing age, and between ethnicities are highlighted. In the coming years, enhanced, automated OCT segmentation may be of benefit for personalization of real-world care, as well as for the detection of novel structure-function correlations. This data will be made publicly available for replication and future investigation by the AMD research community.
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