Semi-quantitative Analysis of Adenosine Perfusion Magnetic Resonance Imaging Outperforms Visual Analysis in Identifying Fractional Flow Reserve-Altered Intermediate-grade Coronary Artery Stenosis: A Pilot Study

PurposeTo evaluate the diagnostic accuracy of semi-quantitative adenosine perfusion magnetic resonance imaging(MRI) to determine fractional flow reserve(FFR)≤0.80 intermediate-grade coronary stenoses as compared to visual analysis.Methods Forty-six patients (mean age 61±9 years;33 males) with 49 intermediate-grade stenoses underwent adenosine perfusion MRI and FFR measurement within 4 months between 2010 and 2013. Retrospective interpretation of all prospectively acquired data was performed. MRI was visually assessed by 2 experienced readers twice with one-year interval, the second time with the knowledge of the diseased artery. All myocardial enhancement maximal upslopes were evaluated distal to the coronary stenosis (=RISK) and in remote myocardium supplied by normal arteries (=REMOTE); stress subendocardial relative myocardial perfusion index (RMPI; RISK/REMOTE upslopes) was assessed in predicting FFR≤0.80 stenoses. Deep learning boosting models including all RISK and REMOTE upslopes were fitted to confirm the added value of accounting for perfusion changes in remote myocardium for FFR prediction. Results The average FFR value was 0.84±0.09 and 15/49 (31%) stenoses were FFR≤0.80. Both readers had moderate accuracy (range: 36/49(73%)-38/49(78%)) in predicting FFR≤0.80 stenoses, even with the knowledge of the stenosis location. At a cutoff value of 0.84, stress subendocardial RMPI had higher accuracy (43/49(88%)) than individual visual readings to predict FFR≤0.80 stenoses. The best FFR prediction using the boosting model occurred when accounting for REMOTE myocardial perfusion parameters, leading to diagnostic accuracy of 44/49(90%) for FFR≤0.80. Conclusion Semi-quantitative adenosine perfusion MRI accounting for stress perfusion in remote myocardium predicts FFR≤0.80 intermediate-grade coronary stenoses with a higher accuracy than individual visual analysis.