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• W3209308983 abstract "Objective: To develop an artificial intelligence deep learning system (AI-DLS) capable of distinguishing “normal optic nerves”, “papilledema” (optic disc edema from proven intracranial hypertension), and “other optic nerve abnormalities” on standard digital fundus photographs from a large, multi-ethnic, worldwide, patient population (BONSAI Study Group). This classification was chosen to provide a low-cost, non-invasive test that facilitates identification of patients less (those with normal optic nerves) or more (those with papilledema) likely to have a neurologic disorder associated with high morbidity/mortality in an emergency setting. Background: The timely and accurate detection of optic disc abnormalities, in particular papilledema, is a key part of the clinical examination; however, few physicians confidently perform ophthalmoscopy. Design/Methods: We developed and validated an AI-DLS to automatically classify optic discs as “normal” or “abnormal”, and specifically detect “papilledema”, using 15,846 digital ocular fundus photographs (14,341 images for DLS training and validation, and 1,505 for external testing) from adult patients as part of an international consortium. The DLS performance to classify the optic disc appearance was evaluated by calculating the area under the receiver operating curve (AUC), sensitivity and specificity, with reference to expert neuro-ophthalmologists. Results: We included 9,156 images of “normal” discs, 2,148 images with “papilledema”, and 3,037 images with “other” optic disc abnormalities. In the primary validation dataset, the DLS successfully discriminated “normal” from “abnormal” optic discs (AUC 0.99 [0.99–0.99]), and “papilledema” from “other”(AUC 0.98 [0.98–0.98]. Similar performance was observed on external datasets, with AUC 0.98 (0.97–0.98), sensitivity 95.3 (93.8–96.6) and specificity 86.6 (83.8–89.3) for the detection of “normal”, and AUC 0.96 (0.95–0.97), sensitivity 96.4 (94.2–98.1) and specificity 84.7 (82.6–86.7) for the detection of “papilledema”. Conclusions: A fundus photograph-based DLS can automatically discriminate normal optic discs, papilledema and other optic disc abnormalities in a multi-country, multi-ethnic patient population, with potential applications for the management of headache and neurologic patients in various clinical settings. Disclosure: Dr. Biousse has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Gensight Biologics.Dr. Najjar has nothing to disclose. Dr. Zhubo has nothing to disclose. Dr. Vasseinex has nothing to disclose. Dr. Ting has nothing to disclose. Dr. Liu has nothing to disclose. Dr. Wong has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with consultant and advisory board member for Allergan, Bayer, Boehringer-Ingelheim, Genentech, Merck, Novartis, Oxurion (formerly ThromboGenics), Roche and Samsung; and is co-inventor and co-founder of start-up companies plano and EyRiS. Dr. Wong has received royalty, license fees, or contractual rights payments from Co-inventor and co-founder of start-up companies plano and EyRiS. Dr. Newman has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with GenSight, Santhera, and Quark. Dr. Newman has received research support from GenSight and Santhera. Dr. Milea has nothing to disclose." @default.
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• W3209308983 date "2020-04-14" @default.
• W3209308983 modified "2023-09-28" @default.
• W3209308983 title "The Brain and Optic Nerve Study with Artificial Intelligence (BONSAI): A Deep Learning System to Detect Papilledema on Ocular Fundus Photography (2743)" @default.
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