Coronary artery disease: myocardial perfusion MR imaging with sensitivity encoding versus conventional angiography.

PURPOSE To evaluate the technical performance of sensitivity encoding (SENSE)-accelerated myocardial perfusion magnetic resonance (MR) imaging and prospectively assess the diagnostic accuracy of this examination for depiction of significant coronary artery disease (CAD). MATERIALS AND METHODS All 102 subjects provided written informed consent, and the local ethics committee approved the study. A saturation-recovery segmented k-space gradient-echo pulse sequence was combined with SENSE to allow dynamic acquisition of myocardial perfusion data on four parallel short-axis MR image sections at every heartbeat. This technique was evaluated in 10 healthy volunteers and in 92 patients scheduled to undergo conventional coronary angiography. Gadopentetate dimeglumine was peripherally injected at rest and during adenosine-induced stress. The maximal upslope of the signal intensity-time profiles was plotted for 16 myocardial segments defined on three MR image sections, and a myocardial perfusion reserve index (MPRI) between stress and rest, normalized to the input function from the blood pool of the most basal section, was calculated. Areas under receiver operating characteristic curves (AUCs) were used to assess the diagnostic performance of cardiac MR imaging for depiction of greater than 70% CAD seen at coronary angiography, the reference standard. RESULTS In volunteers, the mean myocardial enhancement was 2.1 +/- 1.2 (standard deviation), with homogeneous signal intensity distribution across the segments. The diagnostic accuracy of MPRI measurements was high (AUC, 0.908; sensitivity, 88% [52 of 59 patients]; specificity, 82% [27 of 33 patients]). Diagnostic performance was similar among separate analyses of the three coronary territories and among separate analyses of data in the patients with diabetes mellitus, left ventricular hypertrophy, or myocardial infarction. CONCLUSION Multisection myocardial perfusion MR imaging with SENSE is feasible and has high diagnostic accuracy in the detection of CAD.