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OCT-angiography based artificial intelligence-inferred fluorescein angiography for leakage detection in retina
Toshinori Murata1, Takao Hirano1, Hideaki Mizobe2
1Department of Ophthalmology, School of Medicine, Shinshu University, 3-1-1 Asahi Matsumoto, Nagano, 390-8621, Japan.
Abstract:
Optical coherence tomography angiography (OCTA) covers most functions of fluorescein angiography (FA) when imaging the retina but lacks the ability to depict vascular leakage. Based on OCTA, we developed artificial intelligence-inferred-FA (AI-FA) to delineate leakage in eyes with diabetic retinopathy (DR). Training data of 19,648 still FA images were prepared from FA-photo and videos of 43 DR eyes. AI-FA images were generated using a convolutional neural network. AI-FA images achieved a structural similarity index of 0.91 with corresponding real FA images in DR. The AI-FA generated from OCTA correctly depicted vascular occlusion and associated leakage with enough quality, enabling precise DR diagnosis and treatment planning. A combination of OCT, OCTA, and AI-FA yields more information than real FA with reduced acquisition time without risk of allergic reactions.
