Li Bin, Chen Huaigang, Wang Hong, Hong Lang, Yang Liu
Department of Cardiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, 330006 Nanchang, Jiangxi, China.
Jiangxi Medical College, Nanchang University, 330036 Nanchang, Jiangxi, China.
Rev Cardiovasc Med. 2024 Jun 13;25(6):211. doi: 10.31083/j.rcm2506211. eCollection 2024 Jun.
This article reviews four new technologies for assessment of coronary hemodynamics based on medical imaging and artificial intelligence, including quantitative flow ratio (QFR), optical flow ratio (OFR), computational fractional flow reserve (CT-FFR) and artificial intelligence (AI)-based instantaneous wave-free ratio (iFR). These technologies use medical imaging such as coronary angiography, computed tomography angiography (CTA), and optical coherence tomography (OCT), to reconstruct three-dimensional vascular models through artificial intelligence algorithms, simulate and calculate hemodynamic parameters in the coronary arteries, and achieve non-invasive and rapid assessment of the functional significance of coronary stenosis. This article details the working principles, advantages such as non-invasiveness, efficiency, accuracy, limitations such as image dependency, and assumption restrictions, of each technology. It also compares and analyzes the image dependency, calculation accuracy, calculation speed, and operation simplicity, of the four technologies. The results show that these technologies are highly consistent with the traditional invasive wire method, and shows distinct advantages in terms of accuracy, reliability, convenience and cost-effectiveness, but there are also factors that affect accuracy. The results of this review demonstrates that AI-based iFR technology is currently one of the most promising technologies. The main challenges and directions for future development are also discussed. These technologies bring new ideas for the non-invasive assessment of coronary artery disease, and are expected to promote the technological progress in this field.
本文综述了基于医学成像和人工智能的四种评估冠状动脉血流动力学的新技术，包括定量血流比（QFR）、光流比（OFR）、计算血流储备分数（CT-FFR）和基于人工智能（AI）的瞬时无波比值（iFR）。这些技术利用冠状动脉造影、计算机断层扫描血管造影（CTA）和光学相干断层扫描（OCT）等医学成像，通过人工智能算法重建三维血管模型，模拟并计算冠状动脉内的血流动力学参数，实现对冠状动脉狭窄功能意义的无创快速评估。本文详细阐述了每种技术的工作原理、无创性、高效性、准确性等优点，以及图像依赖性、假设限制等局限性。还对这四种技术的图像依赖性、计算准确性、计算速度和操作简便性进行了比较分析。结果表明，这些技术与传统的有创导丝法高度一致，在准确性、可靠性、便利性和成本效益方面具有明显优势，但也存在影响准确性的因素。本综述结果表明，基于人工智能的iFR技术是目前最有前景的技术之一。还讨论了未来发展的主要挑战和方向。这些技术为冠状动脉疾病的无创评估带来了新思路，有望推动该领域的技术进步。
