Factor analysis of medical image sequences improves evaluation of first-pass MR imaging acquisitions for myocardial perfusion

RATIONALE AND OBJECTIVES: Factor analysis of medical image sequences (FAMIS) applied to gadolinium chelate-enhanced subsecond magnetic resonance (MR) imaging was evaluated as a postprocessing method for assessing myocardial perfusion in coronary artery disease (CAD). MATERIALS AND METHODS: To assess the accuracy of motion correction, five normal volunteers underwent MR imaging at rest. Thirteen patients with well-documented CAD and no myocardial infarction underwent MR imaging at rest and after dipyridamole administration. After motion correction, a single myocardial tissue factor (FAMISt) image was obtained with FAMIS for each raw MR imaging series acquisition. To evaluate how FAMIS could improve the analysis of these acquisitions, five readers visually assessed myocardial perfusion with FAMISt and raw MR images, and a multicase, multireader receiver operating characteristic analysis was performed. RESULTS: FAMISt images significantly improved detection of the perfusion defects when compared with raw MR images (P = .002). Areas under the receiver operating characteristic curves ranged from 0.84 to 0.93 with FAMISt images and from 0.48 to 0.85 with raw MR images. CONCLUSION: FAMIS applied to first-pass MR imaging series provided myocardial perfusion images that improve the objective assessment of myocardial perfusion in patients with CAD.