Analysis of first-pass myocardial perfusion MRI using Independent Component Analysis

Myocardial perfusion MRI has emerged as a suitable imaging technique for the detection of ischemic regions of the heart. However, manual post-processing is labor intensive, seriously hampering its daily clinical use. We propose a novel, data driven analysis method based on Independent Component Analysis (ICA). By performing ICA on the complete perfusion sequence, physiologically meaningful feature images, representing events occurring during the perfusion sequence, can be factored out. Results obtained using our method are compared with results obtained using manual contouring by a medical expert. The estimated weight functions are correlated against the perfusion time-intensity curves from manual contours, yielding promising results.