ArticleScientific reports2023
Clinical validation for automated geographic atrophy monitoring on OCT under complement inhibitory treatment.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Detection and Management of Geographic Atrophy Secondary to Age-Related Macular Degeneration Using Noninvasive Retinal Images and Artificial Intelligence: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.Investigative ophthalmology & visual science · 2026Trial
- Exploring Trial Endpoints in Geographic Atrophy Based on Localized Functional Changes in Microperimetry and AI-Quantified OCT Biomarkers.Investigative ophthalmology & visual science · 2026Trial
- Quantitative comparison of automated OCT and conventional FAF-based geographic atrophy measurements in the phase 3 OAKS/DERBY trials.Scientific reports · 2024Trial
- Geographic atrophy in age-related macular degeneration: phenotypic characterisation for clinical trial consideration.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Review
- Exploratory study on a novel automatic quantification software by artificial intelligence for geographic atrophy associated to age-related macular degeneration.International journal of retina and vitreous · 2026Article
- Histologic Photoreceptor and Retinal Pigment Epithelium Degeneration in an Eye With Clinically Documented Geographic Atrophy of AMD.Investigative ophthalmology & visual science · 2026Article
- Choriocapillaris Flow Deficits Are Spatially Linked to Retinal Pigment Epithelium and Photoreceptor Integrity in Geographic Atrophy.Investigative ophthalmology & visual science · 2026Article
- Automated OCT-tailored and same-visit biomarker-targeted microperimetry in geographic atrophy.Scientific reports · 2026Article
- Comparison of choroidal hypertransmission and retinal pigment epithelium loss for quantification of geographic atrophy across commonly used SD-OCT devices.Scientific reports · 2026Article
- Geographic Atrophy Progression in Clinical Practice Before and After Pegcetacoplan Treatment.Vision (Basel, Switzerland) · 2025Article
- Artificial intelligence in managing retinal disease-current concepts and relevant aspects for health care providers.Wiener medizinische Wochenschrift (1946) · 2025Review
- Artificial Intelligence Approaches for Geographic Atrophy Segmentation: A Systematic Review and Meta-Analysis.Bioengineering (Basel, Switzerland) · 2025Review
- Structure-Function Correlation of Deep-Learning Quantified Ellipsoid Zone and Retinal Pigment Epithelium Loss and Microperimetry in Geographic Atrophy.Investigative ophthalmology & visual science · 2025Article
- Rethinking Clinical Trials in Age-Related Macular Degeneration: How AI-Based OCT Analysis Can Support Successful Outcomes.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Photoreceptor assessment in age-related macular degeneration.Eye (London, England) · 2025Review
- Role of Artificial Intelligence in Retinal Diseases.Klinische Monatsblatter fur Augenheilkunde · 2024Review
- [Complement inhibition treatment for geographic atrophy (GA): functional and morphological efficacy and relevant biomarkers in clinical practice].Die Ophthalmologie · 2024Review
- AI-based support for optical coherence tomography in age-related macular degeneration.International journal of retina and vitreous · 2024Review
- Non-Neovascular Age-Related Macular Degeneration Assessment: Focus on Optical Coherence Tomography Biomarkers.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Geographic atrophy (GA) represents a late stage of age-related macular degeneration, which leads to irreversible vision loss. With the first successful therapeutic approach, namely complement inhibition, huge numbers of patients will have to be monitored regularly. Given these perspectives, a strong need for automated GA segmentation has evolved. The main purpose of this study was the clinical validation of an artificial intelligence (AI)-based algorithm to segment a topographic 2D GA area on a 3D optical coherence tomography (OCT) volume, and to evaluate its potential for AI-based monitoring of GA progression under complement-targeted treatment. 100 GA patients from routine clinical care at the Medical University of Vienna for internal validation and 113 patients from the FILLY phase 2 clinical trial for external validation were included. Mean Dice Similarity Coefficient (DSC) was 0.86 ± 0.12 and 0.91 ± 0.05 for total GA area on the internal and external validation, respectively. Mean DSC for the GA growth area at month 12 on the external test set was 0.46 ± 0.16. Importantly, the automated segmentation by the algorithm corresponded to the outcome of the original FILLY trial measured manually on fundus autofluorescence. The proposed AI approach can reliably segment GA area on OCT with high accuracy. The availability of such tools represents an important step towards AI-based monitoring of GA progression under treatment on OCT for clinical management as well as regulatory trials.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.