Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

PURPOSE

To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-encoded FID navigator) in each radial spoke.

METHODS

A forward model was created from low-resolution calibration data to simulate the effect of relative motion between the coil sensitivity profiles and the underlying object on the self-encoded FID navigator signal. Trajectory deviations were included in the model as low spatial-order field variations. Three volunteers were imaged at 3 T using a modified 3D gradient-echo sequence acquired with a Kooshball trajectory while performing abrupt and continuous head motion. Rigid body-motion parameters were estimated from the central k-space signal of each spoke using a least-squares fitting algorithm. The accuracy of self-navigated motion parameters was assessed relative to an established external tracking system. Quantitative image quality metrics were computed for images with and without retrospective correction using external and self-navigated motion measurements.

RESULTS

Self-encoded FID navigators achieved mean absolute errors of 0.69 ± 0.82 mm and 0.73 ± 0.87° relative to external tracking for maximum motion amplitudes of 12 mm and 10°. Retrospective correction of the 3D radial data resulted in substantially improved image quality for both abrupt and continuous motion paradigms, comparable to external tracking results.

CONCLUSIONS

Accurate rigid body motion parameters can be rapidly obtained from self-encoded FID navigator signals in 3D radial MRI to continuously correct for head movements. This approach is suitable for robust neuroanatomical imaging in subjects that exhibit patterns of large and frequent motion.

Rapid measurement and correction of spatiotemporal B0 field changes using FID navigators and a multi-channel reference image

PURPOSE

To measure spatiotemporal B₀ field changes in real time using FID navigators (FIDnavs) and to demonstrate the efficacy of retrospectively correcting high-resolution T 2 * -weighted images using a novel FIDnav framework.

METHODS

A forward model of the complex FIDnav signals was generated by simulating the effect of changes in the underlying B₀ inhomogeneity coefficients, with spatial encoding provided by a multi-channel reference image. Experiments were performed at 3T to assess the accuracy of B₀ field estimates from FIDnavs acquired from a 64-channel head coil under different shim settings and in 5 volunteers performing deep-breathing and nose-touching tasks designed to modulate the B₀ field. Second-order, in-plane spherical harmonic (SH) inhomogeneity coefficients estimated from FIDnavs were incorporated into an iterative reconstruction to retrospectively correct 2D gradient-echo images acquired in both axial and sagittal planes.

RESULTS

Spatiotemporal B₀ field changes measured from rapidly acquired FIDnavs were in good agreement with the results of second-order SH fitting to the measured field maps. FIDnav field estimates accounted for a significant proportion of the ΔB₀ variance induced by deep breathing (64 ± 21%) and nose touching (67 ± 34%) across all volunteers. Ghosting, blurring, and intensity modulation artifacts in T 2 * -weighted images, induced by spatiotemporal field changes, were visibly reduced following retrospective correction with FIDnav inhomogeneity coefficients.

CONCLUSIONS

Spatially resolved B₀ inhomogeneity changes up to second order can be characterized in real time using the proposed approach. Retrospective FIDnav correction substantially improves T 2 * -weighted image quality in the presence of strong B₀ field modulations, with potential for real-time shimming.