Real‐time correction of rigid body motion‐induced phase errors for diffusion‐weighted steady‐state free precession imaging

Abstract

Purpose Diffusion contrast in diffusion-weighted steady state free precession MRI is generated through the constructive addition of signal from many coherence pathways. Motion-induced phase causes destructive interference which results in loss of signal magnitude and diffusion contrast. In this work, a 3D navigator-based real-time correction of the rigid-body-motion-induced phase errors is developed for diffusion-weighted steady state free precession MRI. Methods The efficacy of the real-time prospective correction method in preserving phase coherence of the steady-state is tested in 3D phantom experiments and 3D scans of healthy human subjects. Results In nearly all experiments, the signal magnitude in images obtained with proposed prospective correction was higher than the signal magnitude in images obtained with no correction. In the human subjects the mean magnitude signal in the data was up to 30 percent higher with prospective motion correction than without. Prospective correction never resulted in a decrease in mean signal magnitude in either the data or in the images. Conclusions The proposed prospective motion correction method is shown to preserve the phase coherence of the steady state in diffusion-weighted steady state free precession MRI, thus mitigating signal magnitude losses that would confound the desired diffusion contrast.

Diffusion‐weighted DESS protocol optimization for simultaneous mapping of the mean diffusivity, proton density and relaxation times at 3 Tesla

“…This aspect however is beyond the scope of the work presented here and the implementation of such techniques is left as a perspective. The presence of physiological motion, which tends to disrupt the steady‐state and to artificially reduce the MR signal , also causes errors in the PD estimation, as shown by the S 0 2D‐histogram in Figure a. By comparison with the respective gold standard maps, appears less affected by physiological motion than MD and S 0 , probably because its estimation is dominated by the non‐DW‐DESS signals.…”

“…In attempting to perform high‐resolution diffusion tensor imaging (DTI) in brain tissue, remarkable efforts have also been made to solve the major weakness of DW‐SSFP sequences, namely, its inherent sensitivity to physiological motion . So far, advanced techniques have been developed enabling the prospective correction of rigid body motion by means of navigator echoes and real‐time feedback into the sequence and the attenuation of non‐rigid body motion effects (brain pulsation) by combining navigator echoes and advanced image reconstruction as well as new pulse design techniques . It is thus expected that the progress made in the reduction of motion‐related DW‐SSFP artifacts will soon be sufficient to add diffusivity to the list of MR parameters quantitatively accessible in brain tissue via SSFP sequences.…”

A comparison of navigators, snap‐shot field monitoring, and probe‐based field model training for correcting B0‐induced artifacts in ‐weighted images at 7 T

“…Because of the high sensitivity of FPs, head motion will be reflected in the signal, but how to interpret the data from FPs during motion is still an open question and was out of the scope of this study. However, tracking motion with navigators has already been used in several studies (eg, (30)(31)(32)). Although all methods were quite successful in reducing the artifacts, there is still room for improvement.…”

Analysis of phase error effects in multishot diffusion-prepared turbo spin echo imaging

“…Analysis of phase error effects in multishot diffusion-prepared turbo spin echo imaging during the diffusion encoding, multi-shot DW techniques require an accompanied phase correction method (7)(8)(9)(10)(11)(12).…”

“…When a multi-shot acquisition is needed, such as in the case of high-resolution three-dimensional (3D) diffusion imaging, if the phase error is constant across shots (e.g., eddy-current-induced phase errors) the phase-error dependence can also be ignored. However, with multi-shot imaging in the presence of a time-varying phase error (e.g., MiPe) the signal phase modulation has to be accounted for before the shots are combined (8,9,11,12).…”