Diagnostic Performance of CT-FFR in Atherosclerotic Lesions

This chapter reviews the diagnostic performance of CT-FFR in evaluating coronary atherosclerotic lesions. CT-FFR, derived from resting coronary CT angiography, noninvasively assesses hemodynamic significance, overcoming limitations of traditional anatomic evaluation. Various models (3D-CFD, reduced-order CFD, machine/deep learning) demonstrate improved specificity (82–95%) and accuracy (79–97%) compared to CCTA alone, validated in multicenter trials like DISCOVER-FLOW and NXT. Technical factors (image quality, reconstruction algorithms) and patient-related factors (calcification, diabetes, microcirculation) influence accuracy, with Chinese-developed software (e.g., uCT-FFR) showing promising results. CT-FFR aids in identifying ischemic intermediate lesions (30–69% stenosis) and reduces unnecessary invasive procedures. Ongoing research in China highlights its growing clinical role in CAD diagnosis and treatment guidance.