SMS MUSSELS: A navigator-free reconstruction for simultaneous multi-slice-accelerated multi-shot diffusion weighted imaging.

Abstract

To introduce a novel reconstruction method for simultaneous multi-slice (SMS)-accelerated multi-shot diffusion weighted imaging (ms-DWI). SMS acceleration using blipped-CAIPI schemes have been proposed to speed up the acquisition of ms-DWIs. The reconstruction of the data requires (a) phase compensation to combine data from different shots and (b) slice unfolding to separate the data of different slices. The traditional approaches first estimate the phase maps corresponding to each shot and slice which are then employed to iteratively recover the slice unfolded DWIs without phase artifacts. In contrast, the proposed reconstruction directly recovers the slice-unfolded k-space data of the multiple shots for each slice in a single-step recovery scheme. The proposed method is enabled by the low-rank property inherent in the k-space samples of ms-DW acquisition. This enabled to formulate a joint recovery scheme that simultaneously (a) unfolds the k-space data of each slice using a SENSE-based scheme and (b) recover the missing k-space samples in each slice of the multi-shot acquisition employing a structured low-rank matrix completion. Additional smoothness regularization is also utilized for higher acceleration factors. The proposed joint recovery is tested on simulated and in vivo data and compared to similar un-navigated methods. Our experiments show effective slice unfolding and successful recovery of DWIs with minimal phase artifacts using the proposed method. The performance is comparable to existing methods at low acceleration factors and better than existing methods for higher acceleration factors. For the slice accelerations considered in this study, the proposed method can successfully recover DWIs from SMS-accelerated ms-DWI acquisitions.