Compressed sensing CPMG with group-sparse reconstruction for myelin water imaging.

PURPOSE: Myelin content is a marker for nervous system pathology and is quantifiable by myelin water imaging using multi-echo CPMG sequence, which is inherently slow. One way to accelerate the scan is to utilize compressed sensing. However, reconstructing the images piecemeal by standard compressed sensing methods is not the optimal solution, because it only exploits intraimage spatial redundancy. It does not recognize that the different T2 weighted images are scans of the same anatomical volume and hence correlated. The purpose of this work is to test the feasibility of compressed sensed CPMG with group-sparsity promoting optimization for myelin water imaging. METHODS: Group-sparse reconstruction was performed at various simulated and actual undersampling factors for an electronic phantom, ex vivo rat spinal cord, and in vivo rat spinal cord. Normalized mean square error was used as the metric for comparison. RESULTS: For both simulated undersampling and the actual undersampling, the method was found to minimally impact myelin water fraction map quality (normalized mean square error < 0.25) when acceleration factor was below two. CONCLUSION: Compressed sensed CPMG with group-sparse reconstruction is useful for achieving a shorter scan time than traditionally possible.