Prediction of Flow-Limiting Fractional Flow Reserve in Patients With Stable Coronary Artery Disease Based on Quantitative Myocardial Perfusion Imaging

Although fractional flow reserve (FFR) and myocardial perfusion imaging (MPI) findings fundamentally differ, several cohort studies have revealed that these findings correlate. Here, we investigated whether flow-limiting FFR could be predicted from adenosine stress thallium-201 MPI with single-photon emission computed tomography (SPECT) findings derived from 84 consecutive, prospectively identified patients with stable coronary artery disease and 212 diseased vessels. Among them, FFR was measured in 136 diseased vessels (64%). The findings were compared with regional perfusion abnormalities including stress total perfusion defect (TPD) − rest TPD determined using quantitative perfusion single-photon emission computed tomography software. The FFR inversely correlated the most accurately with stress TPD − rest TPD (r = −0.552, p <0.001). Predictors of major vessels of interest comprising FFR <0.80, included stress TPD − rest TPD, the transient ischemic dilation ratio, left ventricular ejection fraction at rest and beta blockers for left anterior descending artery (LAD) regions, and stress TPD − rest TPD, left ventricular mass, left ventricular ejection fraction at rest, right coronary artery lesions, the transient ischemic dilation ratio, and age for non-LAD regions. The diagnostic accuracy of formulas to predict major vessels of interest with FFR <0.80 was high (sensitivity, specificity and accuracy for LAD and non-LAD: 84%, 87% and 86%, and 75%, 93% and 87%, respectively). In conclusion, although somewhat limited by a sample size and a single-center design, flow-limiting FFR could be predicted from MPI findings with a defined probability. A cohort study might validate our results and provide a novel adjunctive tool with which to diagnose functionally significant coronary artery disease from MPI findings.