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

Abstract

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 ET (within-ET). RMC was applied during image reconstruction by adjusting k-space trajectories according to the measured motion. The motion correction frequency was retrospectively increased with RMC or decreased with reverse RMC. Phantom and in vivo experiments were used to compare PMC and RMC, as well as to compare within-ET and before-ET correction frequency during continuous motion. The correction quality was quantitatively evaluated using the structural similarity index measure with 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 the motion artifacts in RMC. A hybrid PMC and RMC correction, that is, retrospectively increasing the correction frequency of before-ET PMC to within-ET, also reduced motion artifacts. Inferior performance of RMC

Tracking of rigid head motion duringMRIusing an EEGsystem

“…Artifacts primarily arise from Nyquist violations locally in k‐space, limited motion‐tracking frequency, uncompensated field fluctuations, and lack of sampling density compensation. For large sudden rotations, the lack of density compensation and undersampled regions of k‐space introduce ringing artifacts that counteract the benefits of correction, which is a limitation of the retrospective motion correction and reconstruction rather than the motion tracking itself 4,54 . These can be avoided when prospectively updating the scanner FOV and with reacquisition of corrupted k‐space lines.…”

“…These can be avoided when prospectively updating the scanner FOV and with reacquisition of corrupted k‐space lines. Simulation of the best attainable retrospective correction using the measured motion to corrupt images in silico followed by correction could serve as a comparison to “best‐case correction” but was beyond the scope of the study 54 …”

Data‐driven motion‐corrected brain MRI incorporating pose‐dependent B0 fields

“…This experiment was conducted on the first subject on both a 3 T and 7 T scanner. Additional sequence parameters were at 3 T, 1.50 × 1.741.74 mm 3 For each scan session on both scanners, coil array sensitivity profiles used in the reconstructions were estimated from a separate low-resolution (6 × 6 × 6 mm 3 ) reference scan using a custom implementation of the ESPIRiT algorithm. 33…”

“…Prospective techniques have shown to be advantageous in terms of spin history and k-space sampling density, but the need for extra hardware limits these methods in clinical workflow. 3 Retrospective methods, on the other hand, can be applied to a variety of sequences and do not require any type of additional hardware. The aligned sensitivity encoding (SENSE) framework 4 achieves intrascan motion estimation and correction for volumetric anatomical imaging by temporally subdividing k-space samples and accounting for different motion states in each segment.…”

“…Prospective and retrospective motion‐correcting schemes have been proposed that enable motion‐tolerant imaging. Prospective techniques have shown to be advantageous in terms of spin history and k‐space sampling density, but the need for extra hardware limits these methods in clinical workflow 3 . Retrospective methods, on the other hand, can be applied to a variety of sequences and do not require any type of additional hardware.…”