Intermodel Agreement of Myocardial Blood Flow Estimation From Stress-Rest Myocardial Perfusion Magnetic Resonance Imaging in Patients With Coronary Artery Disease

Objectives: The aim of this study was to assess the intermodel agreement of different magnetic resonance myocardial perfusion models and evaluate their correspondence to stenosis diameter. Materials and Methods: In total, 260 myocardial segments were analyzed from rest and adenosine stress first-pass myocardial perfusion magnetic resonance images (1.5 T, 0.050 +/- 0.005 mmol/kg body weight gadolinium; 122 segments in rest, 138 in stress) in 10 patients with suspected or known coronary artery disease. Signal intensity curves were calculated per myocardial segment, of which the contours were traced with QMASS MR V. 7.6 (Medis, Leiden, the Netherlands), and exported to Matlab. Myocardial blood flow quantification was performed with distributed parameter, extended Toft, Patlak, and Fermi parametric models (in-house programs; Matlab R2013a; Mathworks Inc, Natick, MA). Modeling was applied after the signal intensity curves were corrected for spatial magnetic field inhomogeneity and contrast saturation. Overall and grouped perfusion values based on presence of coronary stenosis (> 50% diameter reduction) at coronary computed tomography angiography at second generation dual-source computed tomography were compared between the perfusion models. Results: Rest and stress myocardial perfusion estimates for all models were significantly related to each other (P <0.001). The highest correlation coefficients were found between the extended Toft and Fermi models (R = 0.89-0.91) and low correlation coefficients between the distributed parameter and Patlak models (R = 0.66-0.68). The models resulted in significantly different perfusion estimates in stress (P = 0.03), but not in rest (P = 0.74). The differences in perfusion estimates in stress were caused by differences between the distributed parameter and Patlak models and between the Patlak and Fermi models (both P