Peer-Reviewed Publication
Sci Rep2026;16(1)February 17, 2026Journal Article
Artificial Intelligence-based characterization of therapeutic response in fluid types and volumes influencing retinal function in neovascular age-related macular degeneration.
Sophie Frank-Publig1, Wolf Buehl1, Virginia Mares1,2, Philipp Fuchs1, Leonard M Coulibaly1, Anna Eidenberger1, Ulrike Scheschy3, Georg Faustmann4, Markus Gumpinger1, Emese Sükei1, Hrvoje Bogunovic4,5, Gregor S Reiter1, Stefan Sacu6, Ursula Schmidt-Erfurth1
1Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
2Department of Ophthalmology, Federal University of Minas Gerais, Belo Horizonte, Brazil.
3Department of Ophthalmology, Landesklinikum Horn, Horn, Austria.
4Christian Doppler Lab for Artificial Intelligence in Retina, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
5Institute of Artificial Intelligence, Center for Medical Data Science, Medical University of Vienna, Vienna, Austria.
6Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. stefan.sacu@meduniwien.ac.at.
Abstract
In the real world, there are variable treatment strategies and therapeutic effects of anti-VEGF therapy in neovascular age-related macular degeneration (nAMD). To investigate mechanisms of fluid resolution in pretreated and treatment-naïve eyes, we aimed to compare treatment response through assessment of fluid types, distribution and volumes. 289 eyes of 289 real-world patients with active nAMD w…
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