Highly-Accelerated First-Pass Cardiac Perfusion MRI Using Compressed Sensing and Parallel Imaging

INTRODUCTION: First-pass cardiac perfusion MRI is a promising modality for the assessment of coronary artery disease. Recently developed dynamic parallel imaging techniques, such as k-t SENSE [1] and k-t GRAPPA [2], can be used to perform up to 10-fold accelerated perfusion imaging by exploiting the difference in coil sensitivities and spatio-temporal correlations. Such techniques can be used to increase the data acquisition efficiency, which can then be utilized to increase the spatio-temporal resolution and/or spatial coverage. However, these k-t parallel imaging techniques require dynamic training data which reduces the effective acceleration rate. An alternative technique which does not require training data is compressed sensing [3]. Four-fold accelerated cardiac perfusion MRI has been demonstrated with a compressed sensing technique exploiting the sparsity of the dynamic image set in x-f space and employing k-t random undersampling [4]. In this work, a joint reconstruction approach, named k-t Parallel-Sparse, is developed to combine compressed sensing and parallel imaging for highly (> 6-fold) accelerated cardiac perfusion MRI.