Deep Learning in the Management of Intracranial Aneurysms and Cerebrovascular Diseases: A Review of the Current Literature.

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Abstract

Intracranial aneurysms are a common asymptomatic vascular pathology, rupture of which is a devastating event with significant risk of morbidity and mortality. Aneurysm detection and risk stratification before rupture events are therefore imperative to guide prophylactic measures. Artificial intelligence has shown great promise in the management pathway of aneurysms, through automated detection, prediction of rupture risk, and outcome prediction following treatment. The complementary use of these programmes alongside clinical practice has demonstrated high diagnostic and prognostic accuracies, with the potential to improve patient outcomes. This review explores the role and limitations of deep learning, a subfield of artificial intelligence, in the aneurysm patient journey. We also briefly summarise the application of deep learning models in automated detection and prediction in cerebral arteriovenous malformations and Moyamoya disease.Copyright © 2022 Elsevier Inc. All rights reserved.