Hogg, Henry David Jeffry;
Talks, S James;
Engelmann, Justin;
Teare, Marion Dawn;
Pogose, Michael;
Patel, Praveen J;
Balaskas, K;
... Keane, PA; + view all
(2025)
Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England.
Eye
10.1038/s41433-025-04025-4.
(In press).
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Abstract
BACKGROUND: Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England. METHODS: Using a published non-inferiority design protocol, 521 pairs of ipsilateral retinal OCTs from consecutive visits for nAMD treatment were collected from two NHS ophthalmology services. Real-world binary assessments of nAMD disease activity or stability were compared to an independent ophthalmic reading centre reference standard. An AI system capable of retinal OCT segmentation analysed the OCTs, applying thresholds for intraretinal and subretinal fluid to generate binary assessments. The relative negative predictive value (rNPV) of AI versus real-world assessments was calculated. RESULTS: Real-world assessments of nAMD activity showed a NPV of 81.6% (57.3–81.6%) and a positive predictive value (PPV) of 41.5% (17.8–62.3%). Optimised thresholds for intraretinal fluid increase (>1,000,000 µm³) and subretinal fluid increase (>2,000,000 µm³) for the AI system assessments produced an NPV of 95.3% (85.5–97.9%) and PPV of 57.8% (29.4–76.0%). The rNPV of 1.17 (1.11–1.23) met predefined criteria for clinical and statistical superiority and accompanied an rPPV of 1.39 (1.10–1.76). CONCLUSIONS: This study suggests that the same thresholds for interpreting OCT-based AI analysis could reduce undertreatment and overtreatment in nAMD monitoring at different centres. Interventional research is needed to test the potential of supportive or autonomous AI assessments of nAMD disease activity to improve the quality and efficiency of services.
| Type: | Article |
|---|---|
| Title: | Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41433-025-04025-4 |
| Publisher version: | https://doi.org/10.1038/s41433-025-04025-4 |
| Language: | English |
| Additional information: | © 2025 Springer Nature Limited. This article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10214589 |
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