Computationally simulated fractional flow reserve from coronary computed tomography angiography based on fractional myocardial mass

Abstract

Computed tomography angiography (CCTA)-based calculations of fractional flow reserve (FFR) can improve the diagnostic performance of CCTA for physiologically significant stenosis but the computational resource requirements are high. This study aimed at establishing a simple and efficient algorithm for computing simulated FFR (S-FFR). A total of 107 patients who underwent CCTA and invasive FFR measurements were enrolled in the study. S-FFR was calculated using 145 evaluable coronary arteries with off-the-shelf softwares. FFR0.80 was a reference threshold for diagnostic performance of diameter stenosis (DS)50%, DS70%, or S-FFR0.80. FFR0.80 was identified in 78 vessels (54%). In per-vessel analysis, S-FFR showed good correlation (r=0.83) and agreement (mean difference=0.02 +/- 0.08) with FFR. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of S-FFR0.80 for FFR0.80 were 84%, 92%, 92%, 83%, and 88%, respectively. S-FFR0.80 showed much higher predictive performance for FFR0.80 compared with DS50% or DS70% (c-statistics=0.92 vs. 0.58 or 0.65, p<0.001, all). The classification agreement between FFR and S-FFR was >80% when the average of FFR and S-FFR was <0.76 or >0.86. Per-patient analysis showed consistent results. In this study, a simple and computationally efficient simulated FFR (S-FFR) algorithm is designed and tested using non-proprietary off-the-shelf software. This algorithm may expand the accessibility of clinical applications for non-invasive coronary physiology study.