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人工智能在脑动静脉畸形中的应用:血管构筑、临床症状及预后预测

Application of artificial intelligence in brain arteriovenous malformations: Angioarchitectures, clinical symptoms and prognosis prediction.

作者信息

Li Xiangyu, Xiang Sishi, Li Guilin

机构信息

Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.

出版信息

Interv Neuroradiol. 2024 Mar 22:15910199241238798. doi: 10.1177/15910199241238798.


DOI:10.1177/15910199241238798
PMID:38515371
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11571152/
Abstract

BACKGROUND: Artificial intelligence (AI) has rapidly advanced in the medical field, leveraging its intelligence and automation for the management of various diseases. Brain arteriovenous malformations (AVM) are particularly noteworthy, experiencing rapid development in recent years and yielding remarkable results. This paper aims to summarize the applications of AI in the management of AVMs management. METHODS: Literatures published in PubMed during 1999-2022, discussing AI application in AVMs management were reviewed. RESULTS: AI algorithms have been applied in various aspects of AVM management, particularly in machine learning and deep learning models. Automatic lesion segmentation or delineation is a promising application that can be further developed and verified. Prognosis prediction using machine learning algorithms with radiomic-based analysis is another meaningful application. CONCLUSIONS: AI has been widely used in AVMs management. This article summarizes the current research progress, limitations and future research directions.

摘要

背景:人工智能(AI)在医学领域迅速发展,利用其智能和自动化来管理各种疾病。脑动静脉畸形(AVM)尤其值得关注,近年来发展迅速并取得了显著成果。本文旨在总结人工智能在AVM管理中的应用。 方法:回顾了1999年至2022年期间发表在PubMed上讨论人工智能在AVM管理中应用的文献。 结果:人工智能算法已应用于AVM管理的各个方面,特别是在机器学习和深度学习模型中。自动病变分割或勾勒是一个有前景的应用,可以进一步开发和验证。使用基于放射组学分析的机器学习算法进行预后预测是另一个有意义的应用。 结论:人工智能已广泛应用于AVM管理。本文总结了当前的研究进展、局限性和未来的研究方向。

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引用本文的文献

[1]
Impact of embolization on stereotactic radiosurgery outcomes for intracranial arteriovenous malformations Spetzler-Martin grades III-V: a systematic review and meta-analysis.

Front Surg. 2025-4-3

[2]
Comprehensive Management of a Giant Left Frontal AVM Coexisting with a Bilobed PComA Aneurysm: A Case Report Highlighting Multidisciplinary Strategies and Advanced Neurosurgical Techniques.

J Clin Med. 2025-2-13

本文引用的文献

[1]
Validation of the commercial coronary computed tomographic angiography artificial intelligence for coronary artery stenosis: a cross-sectional study.

Quant Imaging Med Surg. 2023-6-1

[2]
Ruptured arteriovenous malformation mortality: Incidence, risk factors, and inpatient outcome score.

Interv Neuroradiol. 2025-8

[3]
Microsurgery versus Microsurgery With Preoperative Embolization for Brain Arteriovenous Malformation Treatment: A Systematic Review and Meta-analysis.

Neurosurgery. 2023-1-1

[4]
Vessel wall imaging and quantitative flow assessment in arteriovenous malformations: A feasibility study.

Interv Neuroradiol. 2024-10

[5]
Brain arteriovenous malformation flow after stereotactic radiosurgery: Role of quantitative MRA.

Interv Neuroradiol. 2024-4

[6]
Segmentation techniques of brain arteriovenous malformations for 3D visualization: a systematic review.

Radiol Med. 2022-12

[7]
Predictive mutation signature of immunotherapy benefits in NSCLC based on machine learning algorithms.

Front Immunol. 2022

[8]
Machine learning for predicting hemorrhage in pediatric patients with brain arteriovenous malformation.

J Neurosurg Pediatr. 2022-8-1

[9]
Assessment of gamma knife radiosurgery for unruptured cerebral arterioveneus malformations based on multi-parameter radiomics of MRI.

Magn Reson Imaging. 2022-10

[10]
Compactness index: a radiosurgery outcome predictor for patients with unruptured brain arteriovenous malformations.

J Neurosurg. 2022-5-20

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