Purpose: To evaluate the diagnostic performance of coronary computed tomography angiography derived fractional flow reserve (CT-FFR) with invasive fractional flow reserve (FFR) in patients with coronary artery disease" before "with invasive fractional flow reserve serving as the reference standard. Materials and methods: CT-FFR values based on a machine learning algorithm (cFFR(ML)) in 183 vessels of 136 patients from four centers were measured with invasive FFR as reference standard. The diagnostic performance from our multicenter study was combined into a meta-analysis following a literature search in Web of Science, PubMed, Cochrane library to identify studies comparing diagnostic performance of coronary computed tomography angiography (CCTA) and CT-FFR. Sensitivity, specificity, accuracy were analyzed on both per-vessel and per-patient basis for intermediate lesions and by algorithm. Results: Our multicenter study demonstrated sensitivities, specificities, and accuracies of cFFR. L and CCTA of 0.85, 0.94, 0.90, and 0.95, 0.28, 0.55 on a per-vessel basis, respectively. For our meta-analysis, pooled sensitivities, specificities, and accuracies of CT-FFR and CCTA were 0.85, 0.82, 0.82, and 0.85, 0.57, 0.65 with AUC of 0.86 (95%CI: 0.83(similar to) 0.89) and 0.83 (95%CI: 0.79 (similar to)0.86) on a per-vessel basis, respectively. The sensitivity, specificity and accuracy for intermediate lesions using cFFR(ML) were 0.84, 0.92, and 0.89. No significant difference was found among different algorithms of CT-FFR (P < 0.001). Conslusion: This multicenter study with meta-analysis showed that CT-FFR had a high diagnostic accuracy in determining ischemia-specific lesions and intermediate lesions. There was no significant difference when comparing the combined diagnostic performance of different algorithms of CT-FFR with invasive FFR as the reference standard.