无创血流储备分数诊断冠心病的研究进展

Progress in the Diagnosis of Coronary Artery Disease by Non-invasive Fractional Flow Reserve

随着光子计数探测器CT(photon-counting detector CT,PCD-CT)的商用化以及人工智能(artificial intelligence, AI)深度学习(deep learning, DL)的应用,冠状动脉CT血管成像(coronary computed tomography angiography, CCTA)的图像质量越来越清晰,CCTA实现了冠状动脉狭窄性病变及斑块性质的无创解剖学评估,基于CCTA的无创血流储备分数CT(fractional flow reserve, CT-FFR)实现了冠状动脉粥样硬化性心脏病(冠心病)的无创功能学评估,为临床医师更好、更快做出决策贡献巨大。现就基于CCTA的CT-FFR临床应用等方面进行简要阐述,以期为该领域进一步深入研究提供参考。

With the commercialization of photon count detector CT(photon-counting detector CT,PCD-CT)and the application of artificial intelligence(AI)deep learning,the image quality of coronary CT vascular imaging(CCTA)has become more and more clear.CCTA achieved non-invasive anatomical evaluation of coronary stenotic lesions and plaque nature.CT(fractional flow reserve,CT-FFR)based on CCTA achieves the non-invasive functional assessment of coronary atherosclerotic heart disease(coronary heart disease),which contributes greatly to the better and faster decisions made by clinicians.In this paper,the clinical application of CT-FFR based on CCTA is now briefly expounded,in order to provide a reference for further in-depth research in this field.