vNav-QALAS: Motion robust 3D multi-parametric brain mapping with volumetric navigators

Motivation: Subject motion during long, 3D-encoded multi-parametric MRI scans can significantly hamper the image quality of the reconstructed quantitative maps. Goal(s): We propose a motion-robust quantitative brain mapping method, vNav-QALAS, that uses no additional hardware for head motion tracking. Approach: We embedded low-resolution 3D volumetric EPI navigators (EPI-vNavs) in the QALAS sequence, enabling head motion estimates every TR. The motion trajectory was then incorporated into a retrospectively motion corrected parallel imaging reconstruction. Results: The EPI-vNavs enable a motion-robust quantitative brain mapping and ~9% TR increase. The motion-mitigated quantitative maps show significantly reduced artifacts and provide improved agreement with the maps obtained from motion-free scans. Impact: We presented a motion-robust 3D multiparametric brain mapping technique that requires no external hardware for motion tracking and minimal increase (~9%) of the overall acquisition time.