脑血管成像中的人工智能:对动脉瘤检测和断裂风险预测的有针对性的审查
1Department of Biomedical Engineering, University of Massachusetts Amherst, Amherst, MA, USA.
JMA journal
|February 12, 2026
概括
人工智能 (AI) 为检测脑动脉瘤和预测破裂风险提供了先进的工具,超过了传统方法. 虽然有希望,但人工智能应用需要进一步的临床验证,才能广泛采用个性化患者护理.
科学领域:
- 神经成像是一种神经成像.
- 血管神经学 血管神经学
- 人工智能在医学中的应用
背景情况:
- 大脑动脉瘤带来了重大风险,传统的成像技术在预测破裂方面有限.
- 需要先进的,个性化的诊断策略来改善患者的治疗结果.
- 人工智能 (AI) 在脑血管成像和动脉瘤管理方面具有变革性的潜力.
研究的目的:
- 审查和综合AI在脑血管成像中用于动脉瘤检测和破裂风险预测的应用.
- 为动脉瘤分析提供放射学,机器学习 (ML) 和深度学习 (DL) 的综合框架.
- 突出新兴的人工智能解决方案,并解决临床翻译的挑战.
主要方法:
- 关于人工智能在脑血管成像中的发表研究的叙述性综述.
- 对放射学进行量化特征提取的研究.
- 分析用于检测和风险预测的ML和深度学习 (DL) 模型.
主要成果:
- 放射学,ML和DL为动脉瘤检测和断裂风险评估提供了增强的能力.
- 人工智能方法显示出超越传统风险得分的潜力,如PHAZES和ELAPSS.
- 目前的人工智能方法是研究性的,需要严格的前性验证.
结论:
- 人工智能,包括放射学,ML和DL,对个性化动脉瘤护理具有重大前景.
- 临床验证和标准化对于成功将AI整合到实践中至关重要.
- 人工智能驱动的精准医学可能会降低动脉瘤破裂率并改善患者的治疗结果.
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