Background: Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide. Conventional CCTA has limited ability to evaluate functional significance of stenosis, highlighting the need for non-invasive physiological assessment methods.
Objective: This study aimed to assess the diagnostic performance of a CT-FFR algorithm based on CFD in identifying ischemic coronary artery stenosis.
Methods: A total of 184 vessels from 171 patients undergoing both CCTA and ICA were retrospectively analyzed. CT-FFR and QFR were computed, with QFR ≤0.8 serving as the reference standard for ischemia. The diagnostic capabilities of CT-FFR were compared with anatomical evaluation via CCTA.
Results: CT-FFR demonstrated superior diagnostic performance over CCTA, with per-vessel sensitivity of 95.5%, specificity of 74.2%, and accuracy of 91.8% (AUC: 0.839 vs. 0.637, P<0.001). In lesions with intermediate QFR values (0.75-0.85), CT-FFR maintained high diagnostic accuracy (79.4%) and AUC (0.785), outperforming CCTA. Furthermore, CT-FFR remained reliable across various calcification levels, with diagnostic efficacy unaffected by Agatston scores.
Conclusion: CT-FFR based on CFD offers a robust, non-invasive solution for the functional assessment of coronary stenosis. Its diagnostic superiority over CCTA and consistent performance in calcified vessels highlight its clinical utility in precision cardiovascular care.
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