人工智能用于估计即时无波比:对技术的系统文献综述
Yacoub Aldroubi1, Tariq Alhusban2, Rama Abu Yosef1
1Faculty of Medicine, University of Jordan, Amman, Jordan.
The international journal of cardiovascular imaging
|February 4, 2026
概括
人工智能 (AI) 提高了使用冠状动脉血管学即时无波比 (iFR) 的非侵入性估计. 这种人工智能驱动的方法对冠状动脉疾病的评估具有前景,可以提高诊断准确度,而无需侵入性手术.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 分流储备 (FFR) 对于冠状动脉疾病 (CAD) 评估和皮肤冠状动脉干预 (PCI) 指导至关重要.
- 即时无波比 (iFR) 为FFR提供了一个非高血压的,不那么复杂的替代方案,但仍然具有侵入性.
- 在iFR侵入性的局限性阻碍了广泛的临床采用.
研究的目的:
- 系统地审查和评估基于人工智能 (AI) 的方法的诊断准确性,以进行iFR的非侵入性估计.
- 评估AI在使用医学成像模式改善冠状动脉疾病评估方面的潜力.
主要方法:
- 在主要的科学数据库 (Web of Science,PubMed,ScienceDirect,Scopus) 中进行了系统的文献搜索.
- 包括专注于基于AI的iFR估计冠状动脉计算机断层扫描血管造影 (CCTA) 和X射线冠状动脉血管造影 (XCA) 的研究.
- 通过QUADAS-2工具评估研究质量.
主要成果:
- 五项研究符合纳入标准,利用人工智能从CCTA和XCA估计iFR.
- 报告的诊断准确度在58%至90.2%之间,灵敏度在37%至87.2%之间,特异性在50%至97.8%之间.
- 积极的预测值 (PPV) 从34%到79%,负的预测值 (NPV) 从77%到97.5%,ROC曲线值从0.89到0.98.
结论:
- 人工智能模型通过准确的IFR估计,显示出改善非侵入性冠状动脉疾病评估的巨大潜力.
- 这些人工智能驱动的方法为侵入性评估提供了一个有希望的替代方案.
- 需要进一步的研究来规范实践,并确保这些AI工具的临床可访问性和适用性.
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