Deep learning-assisted analysis of biomarker changes after increase of dosing from aflibercept 2 mg to 8 mg in therapy-resistant neovascular age-related macular degeneration
Aflibercept 8 mg demonstrated significant efficacy and durability in reducing nAMD biomarkers and extending intervals in a real-world setting. The use of deep learning for biomarker quantification highlighted its potential for enhancing treatment monitoring and decision-making. Future studies with a larger patient cohort and prospective study setting should explore long-term outcomes and integration of artificial intelligence-driven analysis.
Authors
- Ben Asani (ORCID: https://orcid.org/0000-0003-4809-2859)
- Jakob Siedlecki (ORCID: https://orcid.org/0000-0002-0279-4823)
- Michael Hafner
- Benedikt Schworm (ORCID: https://orcid.org/0000-0003-0753-2408)
- Johannes Schiefelbein (ORCID: https://orcid.org/0000-0001-5357-7469)
- Franziska Eckardt (ORCID: https://orcid.org/0000-0001-5883-2529)
- Siegfried Priglinger (ORCID: https://orcid.org/0000-0002-5580-612X)
- Caspar Liesenhoff
- Alexander Kufner
Institutions
- LMU Klinikum (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- BMJ Open Ophthalmology
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1136/bmjophth-2025-002176
- Citations
- 5
- Primary Topic
- Retinal Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 8.54
Funders
- Bundesministerium für Bildung und Forschung
- Ludwig-Maximilians-Universität München
- Helmholtz Artificial Intelligence Cooperation Unit