Multimodal imaging and deep learning in geographic atrophy secondary to age-related macular degeneration.

Autor: Pfau M; Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland.; Department of Ophthalmology, University of Basel, Basel, Switzerland., Künzel SH; Department of Ophthalmology, University of Bonn, Bonn, Germany., Pfau K; Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland.; Department of Ophthalmology, University of Basel, Basel, Switzerland.; Department of Ophthalmology, University of Bonn, Bonn, Germany., Schmitz-Valckenberg S; Department of Ophthalmology, University of Bonn, Bonn, Germany.; Department of Ophthalmology & Visual Sciences, John A. Moran Eye Center, University of Utah, Salt Lake City, Utah, USA., Fleckenstein M; Department of Ophthalmology & Visual Sciences, John A. Moran Eye Center, University of Utah, Salt Lake City, Utah, USA., Holz FG; Department of Ophthalmology, University of Bonn, Bonn, Germany.
Jazyk: angličtina
Zdroj: Acta ophthalmologica [Acta Ophthalmol] 2023 Dec; Vol. 101 (8), pp. 881-890.
DOI: 10.1111/aos.15796
Abstrakt: Geographic atrophy (GA) secondary to age-related macular degeneration is among the most common causes of irreversible vision loss in industrialized countries. Recently, two therapies have been approved by the US FDA. However, given the nature of their treatment effect, which primarily involves a relative decrease in disease progression, discerning the individual treatment response at the individual level may not be readily apparent. Thus, clinical decision-making may have to rely on the quantification of the slope of GA progression before and during treatment. A panel of imaging modalities and artificial intelligence (AI)-based algorithms are available for such quantifications. This article aims to provide a comprehensive overview of the fundamentals of GA imaging, the procedures for diagnosis and classification using these images, and the cutting-edge role of AI algorithms in automatically deriving diagnostic and prognostic insights from imaging data.
(© 2023 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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