ArticleOphthalmology and therapy2025
Deep-Learning-Assisted Analysis of Early Biomarker Changes in Treatment-Naïve Patients with Neovascular AMD Under Intravitreal Faricimab.
Article in Ophthalmology and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Rapid Effects on Anatomical and Functional Outcomes following Upload with Faricimab in Treatment-Naïve nAMD: German Single-Center Study 45DRY.Ophthalmology and therapy · 2026Article
- Short-term outcomes of intravitreal faricimab on refractory neovascular age-related macular degeneration patients in China.Frontiers in medicine · 2026Article
- Visual Gains with Faricimab vs Aflibercept 8 mg in Naïve Retinovascular Disease: Global Real-World Cases and Literature Review.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
- Digital Physiotherapeutic Vision-Specific Training System for Patients with Diabetic Retinopathy: A Propensity Score-Matched Retrospective Cohort Study.Ophthalmology and therapy · 2026Article
- Efficacy and Safety of Intravitreal Faricimab in Age-Related Macular Degeneration-A Review.Journal of clinical medicine · 2025Review
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Authors and funding
7 authors.
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Abstract
introductionArtificial intelligence (AI)-driven biomarker segmentation offers an objective approach to assessing neovascular age-related macular degeneration (nAMD). In addition, faricimab, a bispecific VEGF and Ang-2 inhibitor, presents new potential in disease management. This study applies an AI-based segmentation algorithm to quantify key optical coherence tomography (OCT) biomarkers and assess the short-term efficacy of intravitreal faricimab in treatment-naïve patients.
methodsThis retrospective analysis includes 40 eyes from 38 treatment-naïve patients with nAMD treated with faricimab at LMU University Hospital Munich between January 2023 and September 2024. Patients received 4-monthly intravitreal injections. Biomarkers of disease activity, including central retinal thickness (CRT), intraretinal fluid (IRF), subretinal fluid (SRF), subretinal hyperreflective material (SHRM) and fibrovascular pigment epithelium detachment (fvPED), were quantified using a deep learning-based semantic segmentation algorithm. Best-corrected visual acuity (BCVA) and OCT imaging data were analyzed at baseline (mo0) and after 1 (mo1), 2 (mo2) and 3 months (mo3).
resultsAI-driven analysis revealed significant reductions in key biomarkers. CRT decreased from 433.6 (IQR: 306.6) µm at mo0 to 241.5 (IQR: 130.8) µm at mo3 (p < 0.0001). IRF and SRF volumes were reduced by > 99% from mo0 to mo3 (both p < 0.0001). BCVA improved from 0.60 (IQR: 0.30) logMAR at mo0 to 0.40 (IQR: 0.33) logMAR at mo3 (p < 0.0001). Correlation analysis identified IRF and SHRM reductions as the strongest predictors of visual improvement.
conclusionThis study demonstrates the potential of AI-assisted biomarker analysis for precise disease monitoring in nAMD. Faricimab significantly reduced disease activity biomarkers and improved visual acuity in treatment-naïve patients, reinforcing its efficacy in early disease control. Future studies should explore long-term outcomes and further integrate AI-driven biomarker evaluation in clinical practice.
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