Our study provides evidence that machine learning-based CT-FFR values exhibit a probably positive correlation with individuals presenting high-risk factors for coronary artery disease. Furthermore, we observed a influence of CT-FFR on the clinical decisions made by physicians. The integration of CT-FFR and CCTA has the potential to enhance diagnostic efficacy.
An et al. (Tue,) studied this question.