Motion-Robust Reconstruction of Multishot Diffusion-Weighted Images without Phase Estimation through Locally Low-Rank Regularization

Diffusion-weighted MRI is a widely used technique in neuroscience research, as well as for many clinical applications. Compared with single-shot acquisition, multi-shot acquisition help achieve higher resolution and SNR with reduced distortion. But the motion-induced shot-to-shot phase variations lead to ghosting artifacts. In this work, we propose a relaxed model for multi-shot diffusion-weighted MRI reconstruction (shot-LLR), in which spatial-shot matrices are constructed and low-rank regularizations are applied on them. Shot-LLR shows decreased ghost artifacts versus state-of-the-art reconstruction methods (POCS-MUSE and POCS-ICE), and compared with the single-shot image, the 8-shot acquisition and shot-LLR reconstruction together provide higher in-plane resolution (1 mm) and sharper boundaries for clinical evaluation.

Hu Y, Levine EG, Tian Q, Moran CJ, Wang X, Taviani V, Vasanawala SS, McNab JA, Daniel BL, Hargreaves BA. Motion-robust reconstruction of multishot diffusion-weighted images without phase estimation through locally low-rank regularization. Magn Reson Med. 2019 Feb;81(2):1181-90.

Online Journal Article

Breast images of a volunteer (1st and 2nd columns) and a patient (3rd column) (slice thickness = 4 mm, b-value = 600 s/mm², nex = 2) reconstructed by different methods under different numbers of shots and different in-plane resolutions. The last row shows the results using the conventional method, in which single-shot and parallel imaging were used, and the reduction factor was 4. Yellow arrows highlight aliasing artifacts. In the 3rd column, an enlarged view of the tumor is provided in the white boxes. Note the improved depiction of the lesion detail in shot-LLR vs conventional single-shot DWI, with reduced artifacts compared to POCS-ICE and POCS-MUSE.