Dynamic CT myocardial perfusion combined with coronary CT angiography for detecting hemodynamical significance of coronary artery stenosis: a comparative study

This study aimed to evaluate the diagnostic performance of combined dynamic stress CT myocardial perfusion imaging (CTP) and coronary CT angiography (CTA) alongside CT-derived fractional flow reserve (CT-FFR) in detecting hemodynamically significant coronary artery disease (CAD). A total of 33 patients (86 vessels) who underwent coronary CTA, dynamic stress CTP, and coronary angiography were included. Vessels exhibiting 30-90% stenosis were subjected to FFR analysis based on coronary angiography (Angio-FFR). Hemodynamic significance, determined by Angio-FFR ≤ 0.80, and imaging findings were evaluated. The evaluation involved a comparison between the combined use of coronary CTA, CTP and CT-FFR, versus the sole use of coronary CTA. Out of 86 coronary vessels, 17 (19.8%) exhibited hemodynamically significant stenosis. The sensitivity, specificity, and accuracy of coronary CTA for detecting ischemia were 94.12%, 34.78%, and 46.51%, respectively. Adding CTP to CTA improved specificity to 88.41%, and accuracy to 87.21%, respectively. The area under the curve (AUC) for the discrimination of functional significant stenosis was 0.798 when using CTA alone, and for CTA plus CTP, it reached 0.910. Furthermore, the combination of CTA, CTP and CT-FFR, showed accuracy of 88.37%, sensitivity of 88.24% and specificity of 88.41% with the AUC of 0.946. The integration of dynamic CTP with CTA significantly enhances the diagnostic accuracy for identifying patients with hemodynamically significant CAD, compared to the use of CTA alone. This study underscores the value of combining CTP, CT-FFR, and CTA in improving diagnostic precision for CAD. The combination of CTP, CT-FFR and CTA offers a multifaceted assessment for patients with CAD by simultaneously providing anatomical detail, functional analysis, and physiological quantification, which facilitating rapid, accurate, and optimal clinical decision-making and significantly enhances patient management.