ArticleOphthalmology2021
Quantitative Analysis of OCT for Neovascular Age-Related Macular Degeneration Using Deep Learning.
Article in Ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
63 citing papers in PubMed, 1 synthesis or guideline pooled it.
- In-depth analysis of research hotspots and emerging trends in AI for retinal diseases over the past decade.Frontiers in medicine · 2024Pooled it
- Fluid/function correlation using AI-based quantification versus central subfield thickness in treatment-naïve and pre-treated patients with neovascular AMD in a real-world setting.Acta ophthalmologica · 2026Trial
- Longitudinal Assessment of Ellipsoid Zone Integrity, Subretinal Hyperreflective Material, and Subretinal Pigment Epithelium Disease in Neovascular Age-Related Macular Degeneration.Ophthalmology. Retina · 2021Trial
- Fluid Volumes Longitudinal Modeling to Predict Atrophy and Fibrosis in Neovascular Age-Related Macular Degeneration.Ophthalmology science · 2026Article
- Review
- Integrating genetics, age and imaging to predict treatment outcomes in neovascular age-related macular degeneration: a proof-of-concept study.Scientific reports · 2026Article
- Automated measurement of macular neovascularization lesion size in nAMD using AI segmentation.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- AI-based fluid quantification in neovascular age-related macular degeneration and diabetic macular edema treated with faricimab - a real-life study.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Article
- Evaluation of deep learning-based retinal pigment epithelium segmentation for a widely used optical coherence tomography device.Scientific reports · 2025Article
- Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England.Eye (London, England) · 2025Article
- Ophthalmic drug discovery and development using artificial intelligence and digital health technologies.NPJ digital medicine · 2025Review
- Deep Learning-Based Retinal Layer Segmentation in Optical Coherence Tomography Scans of Patients with Inherited Retinal Diseases.Klinische Monatsblatter fur Augenheilkunde · 2025Article
- Imaging biomarkers and artificial intelligence for diagnosis, prediction, and therapy of macular fibrosis in age-related macular degeneration: Narrative review and future directions.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Review
- Updates on novel and traditional OCT and OCTA biomarkers in nAMD.Eye (London, England) · 2025Review
- Impact of residual retinal fluid on treatment outcomes in neovascular age-related macular degeneration.The British journal of ophthalmology · 2025Review
- Non-exudative OCT findings in neovascular AMD.Eye (London, England) · 2025Review
- Artificial intelligence in assessing progression of age-related macular degeneration.Eye (London, England) · 2025Review
- Faricimab efficacy in type 1 macular neovascularization: AI-assisted quantification of pigment epithelium detachment (PED) volume reduction over 12 months in Naïve and switch eyes.International journal of retina and vitreous · 2025Article
- Efficiency and safety of automated label cleaning on multimodal retinal images.NPJ digital medicine · 2025Article
- The British-Israeli Project for Algorithm-Based Management of Age-Related Macular Degeneration: Deep Learning Integration for Real-World Data Management and Analysis.Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde · 2025Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
purposeTo apply a deep learning algorithm for automated, objective, and comprehensive quantification of OCT scans to a large real-world dataset of eyes with neovascular age-related macular degeneration (AMD) and make the raw segmentation output data openly available for further research.
designRetrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database.
participantsA total of 2473 first-treated eyes and 493 second-treated eyes that commenced therapy for neovascular AMD between June 2012 and June 2017.
methodsA 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-treated eyes by visual acuity (VA) and race/ethnicity and correlations between volumes.
main outcome measuresVolumes of segmented features (mm
resultsIn 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. Greater volumes of the majority of features were associated with worse VA.
conclusionsWe report the results of large-scale automated quantification of a novel range 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 assist personalization of real-world care and the detection of novel structure-function correlations. These data will be made publicly available for replication and future investigation by the AMD research community.
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