Coronary artery disease remains a major worldwide health threat, requiring consistent developments in non-invasive diagnostic tools. Coronary Computed Tomography Angiography (CCTA) is frequently used for anatomical assessments of coronary arteries. However, its traditional limitation has been the inability to provide functional assessments of coronary lesions. The advent of CT-derived Fractional Flow Reserve (FFRCT) and Instantaneous Wave-Free Ratio derived from CT (iFR-CT) has addressed this gap by employing computational modeling to evaluate the hemodynamic significance of coronary stenosis. This review evaluates the diagnostic performance, and clinical impact of CCTA, FFRCT and iFR-CT. Studies indicate that FFRCT and iFR-CT improve diagnostic specificity and accuracy. Furthermore, research demonstrates that functional imaging influences downstream clinical management and provide significant prognostic information related to major adverse cardiac events. Moreover, advancements in Artificial Intelligence and patient-specific computational models are assessed for their diagnostic accuracy, their reductions in analysis time and their prognostic abilities. Despite these advancements, further clinical trials are fundamental to confirm long-term clinical benefits and standardization.
Keywords: Artificial intelligence; Cardiac imaging techniques; Coronary angiography; Coronary artery disease; Fractional flow reserve; Tomography.
© 2026. The Author(s), under exclusive licence to Springer Nature B.V.