A Review of Artificial Intelligence in Cerebrovascular Disease Imaging: Applications and Challenges.
A Review of Artificial Intelligence in Cerebrovascular Disease Imaging: Applications and Challenges.
复制标题
人工智能在脑血管疾病影像领域的综述：应用与挑战
DOI：
10.2174/1570159x19666211108141446
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发表时间：
2022
影响因子：
5.3
通讯作者：
Mao, Ying
中科院分区：
文献类型：
--
作者：
Chen, Xi;Lei, Yu;Su, Jiabin;Yang, Heng;Ni, Wei;Yu, Jinhua;Gu, Yuxiang;Mao, Ying
关键词：
背景：各种基于人工智能的新兴医学影像技术已广泛应用于多种疾病，但尽管这些疾病可能导致灾难性后果，但在脑血管领域的应用仍然有限。目的：本文旨在通过回顾现有的计算机辅助检测、预测和治疗脑血管疾病应用相关文献，探讨人工智能技术在脑血管疾病领域当前面临的挑战和未来发展方向。方法：基于人工智能在颅内动脉瘤、动静脉畸形、动脉硬化和烟雾病等四种代表性脑血管疾病中的应用，系统回顾了2006年至2021年在美国国家生物技术信息中心、Elsevier Science Direct、IEEE Xplore Digital Library、Web of Science和Springer Link 5个数据库中发表的研究。从这些数据库中识别相关文献后，进一步进行了三个细化步骤。结果：对于热门研究主题，纳入的出版物大多涉及动脉瘤的计算机辅助检测和预测，而动静脉畸形、动脉硬化和烟雾病的研究近年来呈上升趋势。这些出版物中既有传统的机器学习算法，也有深度学习算法，但机器学习技术所占比例较大。结论：与人工智能相关的算法，特别是深度学习，是医学影像分析的有前景的工具，将提高计算机辅助检测、预测和治疗脑血管疾病的性能。
Background: A variety of emerging medical imaging technologies based on artificial intelligence have been widely applied in many diseases, but they are still limitedly used in the cerebrovascular field even though the diseases can lead to catastrophic consequences. Objective: This work aims to discuss the current challenges and future directions of artificial intelligence technology in cerebrovascular diseases through reviewing the existing literature related to applications in terms of computer-aided detection, prediction and treatment of cerebrovascular diseases. Methods: Based on artificial intelligence applications in four representative cerebrovascular diseases including intracranial aneurysm, arteriovenous malformation, arteriosclerosis and moyamoya disease, this paper systematically reviews studies published between 2006 and 2021 in five databases: National Center for Biotechnology Information, Elsevier Science Direct, IEEE Xplore Digital Library, Web of Science and Springer Link. And three refinement steps were further conducted after identifying relevant literature from these databases. Results: For the popular research topic, most of the included publications involved computer-aided detection and prediction of aneurysms, while studies about arteriovenous malformation, arteriosclerosis and moyamoya disease showed an upward trend in recent years. Both conventional machine learning and deep learning algorithms were utilized in these publications, but machine learning techniques accounted for a larger proportion. Conclusion: Algorithms related to artificial intelligence, especially deep learning, are promising tools for medical imaging analysis and will enhance the performance of computer-aided detection, prediction and treatment of cerebrovascular diseases.