Navigator-free multi-shot diffusion MRI via non-local low-rank reconstruction.

Purpose: To develop a non-local low-rank (NLLR) reconstruction method for multi-shot EPI (ms-EPI) in DWI, addressing phase inconsistencies and noise issues while maintaining high spatial resolution in clinically feasible scan times.

Theory and methods: Single-shot EPI (ss-EPI) is widely used for DWI but suffers from geometric distortions and T₂* blurring. ms-EPI improves spatial resolution but introduces shot-to-shot phase variations requiring correction strategies. Traditional navigator-based approaches may increase acquisition time. Recent low-rank regularization reconstruction techniques, such as locally low-rank (LLR) methods, can estimate the phase errors but rely strictly on local neighborhood information along the shot dimension. The proposed NLLR method extends this framework by leveraging non-local patch matching by grouping similar image patches across spatially distant image locations, enhancing non-local redundancy exploitation for improved phase estimation and correction as well as noise suppression. The method was validated in simulations and in vivo experiments and compared to existing post-processing denoising and navigator-free approaches.

Results: In simulation experiments, compared to post-processing denoising algorithms, NLLR demonstrated superior noise suppression and structural preservation across all metrics, even when reconstructing from a single diffusion direction. In the in-vivo experiments, NLLR outperformed conventional navigator-free approaches particularly regarding noise suppression. Fractional anisotropy maps reconstructed using NLLR exhibited improved visualization of fine structures with improved SNR, with performance differences becoming more pronounced at higher resolutions.

Conclusion: The proposed NLLR approach provides an efficient and good solution for high-resolution DWI reconstruction, improving image quality while mitigating phase variations and noise.