Abstract Details

Title The Brain and Optic Nerve Study with Artificial Intelligence (BONSAI): A Deep Learning System to Detect Papilledema on Ocular Fundus Photography

Topic Neuro-ophthalmology/Neuro-otology

Presentation(s) S32 - Neuro-ophthalmology/Neuro-otology (3:30 PM-3:42 PM)

Poster/Presentation
Number 001

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.

Authors/Disclosures
Valerie Biousse, MD PRESENTER	Dr. Biousse has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Gensights Biologic. Dr. Biousse has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Topcon. Dr. Biousse has received publishing royalties from a publication relating to health care. Dr. Biousse has received publishing royalties from a publication relating to health care.
	No disclosure on file
	No disclosure on file
	No disclosure on file
	No disclosure on file
	No disclosure on file
	No disclosure on file
Nancy J. Newman, MD, FAAN (Emory University School of Medicine)	Dr. Newman has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for GenSight. Dr. Newman has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Chiesi. Dr. Newman has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Stoke. Dr. Newman has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Neurophth. Dr. Newman has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Lilly. The institution of Dr. Newman has received research support from GenSight. The institution of Dr. Newman has received research support from Santhera. The institution of Dr. Newman has received research support from NINDS/NIH. Dr. Newman has received publishing royalties from a publication relating to health care. Dr. Newman has received publishing royalties from a publication relating to health care. Dr. Newman has received publishing royalties from a publication relating to health care.
	No disclosure on file

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