2025 年第 1 期 第 20 卷

无创血流储备分数的历史和现状及发展趋势

History, current status and development trend of noninvasive fractional flow reserve

作者：王点  翟光耀

英文作者：Wang Dian Zhai Guangyao

单位：首都医科大学潞河临床医学院首都医科大学附属北京潞河医院心血管病中心，北京101149

英文单位：Cardiovascular Center Luhe Clinical Medical College Capital Medical University Beijing Luhe Hospital Capital Medical University Beijing 101149 China

关键词：冠状动脉狭窄；  冠状动脉CT血管造影；  血流储备分数；  CT血管造影血流储备分数；  人工智能

英文关键词：Coronaryarterystenosis;  CoronaryCTangiography;  Fractionalflowreserve;  CTangiographyfractionalflowreserve;  Artificialintelligence

• 摘要：

• 人工智能通过冠状动脉CT血管造影（CCTA）数据，计算出冠状动脉的CT血管造影血流储备分数（CT-FFR）。这种能力通过机器学习不断提升和改进，可以用于自动检测和评估冠状动脉狭窄，识别斑块成分以及预测病变的进展，还可以显著提高诊断的准确性和效率。人工智能在CCTA中的应用也面临着一些挑战和问题，包括算法的泛化能力、数据的标准化和隐私保护等。为了进一步提高CT-FFR技术在临床中的实用性和效率，需要对这些挑战进行深入研究，并开发出更加优化的解决方案。

• Artificial intelligence is used to calculate the fractional flow reserve (CT-FFR) of coronary artery by coronary CT angiography (CCTA) data. This ability can be used to automatically detect and assess coronary stenosis, identify plaque components, and predict disease progression. It can also significantly improve the accuracy and efficiency of diagnosis. The application of artificial intelligence in CCTA also faces some challenges and problems, including the generalization ability of the algorithm, data standardization, and privacy protection. In order to further improve the practicability and efficiency of CT-FFR technology in clinical practice, in-depth research on these challenges and the development of more optimized solutions are needed.