• Jihao Xue, Haowen Zheng, Rui Lai, Zhengjun Zhou, Jie Zhou, Ligang Chen, and Ming Wang.
• Department of Neurosurgery, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
• World Neurosurg. 2024 Nov 25; 193: 209221209-221.

AbstractIntracranial aneurysms (IAs), an asymptomatic vascular lesion, are becoming increasingly common as imaging technology progresses. Subarachnoid hemorrhage from IAs rupture entails a substantial risk of mortality or severe disability. The early detection and prompt intervention of IAs posing a high risk of rupture are paramount for optimizing clinical management and safeguarding patients' lives. Artificial intelligence (AI), with its exceptional capabilities in image-based tasks, has garnered significant scholarly interest worldwide. Its application in the management of IAs holds promise for advancing medical research and patient care. Utilizing deep learning algorithms, AI exhibits remarkable capabilities in precisely identifying and segmenting aneurysms, significantly enhancing diagnostic sensitivity and accuracy. Furthermore, AI can meticulously analyze extensive aneurysm datasets to forecast aneurysm growth, rupture hazards, and prognostic scenarios, offering clinician's invaluable assistance in decision-making. This article comprehensively examines the latest advancements in the utilization of AI in aneurysm treatment, encompassing detection and segmentation, rupture risk assessment, prediction of therapeutic outcomes, and facilitation of microcatheter shaping. A brief discussion is held on the challenges and future paths for clinical AI deployments.Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

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