Robust retrospective motion correction of head motion using navigator-based and markerless motion tracking techniques

Purpose This study investigated the artifacts arising from different types of head motion in brain MR images and how well these artifacts can be compensated using retrospective correction based on two different motion-tracking techniques. Methods MPRAGE images were acquired using a 3 T MR scanner on a cohort of nine healthy participants. Subjects moved their head to generate circular motion (4 or 6 cycles/min), stepwise motion (small and large) and “simulated realistic” motion (nodding and slow diagonal motion), based on visual instructions. One MPRAGE scan without deliberate motion was always acquired as a “no motion” reference. Three dimensional fat-navigator (FatNavs) and a Tracoline markerless device (TracInnovations) were used to obtain motion estimates and images were separately reconstructed retrospectively from the raw data based on these different motion estimates. Results Image quality was recovered from both motion tracking techniques in our stepwise and slow diagonal motion scenarios in almost all cases, with the apparent visual image quality comparable to the no-motion case. FatNav-based motion correction was further improved in the case of stepwise motion using a skull masking procedure to exclude non-rigid motion of the neck from the co-registration step. In the case of circular motion, both methods struggled to correct for all motion artifacts. Conclusion High image quality could be recovered in cases of stepwise and slow diagonal motion using both motion estimation techniques. The circular motion scenario led to more severe image artifacts that could not be fully compensated by the retrospective motion correction techniques used

Comparison of prospective and retrospective motion correction in 3D-encoded neuroanatomical MRI

PURPOSE: To compare prospective motion correction (PMC) and retrospective motion correction (RMC) in Cartesian 3D-encoded MPRAGE scans and to investigate the effects of correction frequency and parallel imaging on the performance of RMC. METHODS: Head motion was estimated using a markerless tracking system and sent to a modified MPRAGE sequence which can continuously update the imaging FOV to perform PMC. The prospective correction was applied either before each echo-train (Before-ET) or at every sixth readout within the echo-train (Within-ET). RMC was achieved by adjusting k-space trajectories according to the measured motion during image reconstruction. The motion correction frequency was retrospectively decreased or increased through RMC or reverse RMC. Phantom and in vivo experiments were used to compare PMC and RMC, and to compare Within-ET and Before-ET correction frequency during continuous motion. The correction quality was quantitatively evaluated using the structural similarity index measure using a reference image without motion correction and without intentional motion. RESULTS: PMC resulted in superior image quality compared to RMC both visually and quantitatively. Increasing the correction frequency from Before-ET to Within-ET reduced motion artifacts in RMC. A hybrid PMC and RMC correction, i.e. retrospectively increasing the correction frequency of Before-ET PMC to Within-ET also reduced motion artifacts. Inferior performance of RMC compared to PMC was shown with GRAPPA calibration data without intentional motion, and without any GRAPPA acceleration. CONCLUSION: Reductions in local Nyquist violations with PMC resulted in superior image quality compared to RMC. Increasing the motion correction frequency to Within-ET reduced motion artifacts in both RMC and PMC