Drug-coated balloon (DCB) intervention is a non-drug treatment of coronary heart disease with the advantage of no implantation. In recent years, it is more and more used in primary coronary artery disease. Timely detection of restenosis after DCB is very important to ensure the safety of patients. Invasive coronary angiography (ICA) is the gold standard to reflect coronary artery stenosis, but it is difficult to become a routine follow-up tool for surgical trauma, radiation exposure and other reasons, let alone for elderly patients.~Coronary artery computed tomography angiography (CCTA) can provide a variety of anatomical information such as the degree of coronary artery stenosis and the nature of plaques. It is a commonly used tool for non-invasive imaging diagnosis of coronary heart disease. However, because of its low diagnostic specificity and can not reflect the lesion-related myocardial ischemia, the positive rate of coronary heart disease and the rate of revascularization in patients undergoing ICA are low. In recent years, based on CCTA data, CT-derived fractional flow reserve (CT-FFR) developed by artificial intelligence and other technologies can provide both anatomical and functional information of coronary artery disease. A number of studies have shown that, compared with CCTA alone, CT-FFR has a better ability to diagnose coronary ischemic lesions and can effectively reduce the need for unnecessary ICA, to predict revascularization more accurately. Due to the absence of metal foreign body implantation, DCB intervention makes it possible for CT-FFR to be used in imaging evaluation after DCB. At present, there is no study on the use of CT-FFR in patients after DCB.~In this study, the self-developed CT-FFR based on artificial intelligence was used for the first time to analyze coronary artery lesions in patients after DCB, and to compare the guiding value of CT-FFR and simple CCTA in ICA and revascularization, in order to provide an ideal non-invasive imaging follow-up tool for elderly patients after DCB.
In recent years, based on CCTA data, CT-derived fractional flow reserve (CT-FFR) developed by artificial intelligence and other technologies can provide both anatomical and functional information of coronary artery disease. Compared with CCTA alone, CT-FFR has a better ability to diagnose coronary ischemic lesions and can effectively reduce the need for unnecessary ICA, to predict revascularization more accurately.