Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter.

PURPOSE: Spinal cord gray-matter imaging is valuable for a number of applications, but remains challenging. The purpose of this work was to compare various MRI protocols at 1.5 T, 3 T, and 7 T for visualizing the gray matter. METHODS: In vivo data of the cervical spinal cord were collected from nine different imaging centers. Data processing consisted of automatically segmenting the spinal cord and its gray matter and co-registering back-to-back scans. We computed the SNR using two methods (SNR_single using a single scan and SNR_diff using the difference between back-to-back scans) and the white/gray matter contrast-to-noise ratio per unit time. Synthetic phantom data were generated to evaluate the metrics performance. Experienced radiologists qualitatively scored the images. We ran the same processing on an open-access multicenter data set of the spinal cord MRI (N = 267 participants). RESULTS: Qualitative assessments indicated comparable image quality for 3T and 7T scans. Spatial resolution was higher at higher field strength, and image quality at 1.5 T was found to be moderate to low. The proposed quantitative metrics were found to be robust to underlying changes to the SNR and contrast; however, the SNR_single method lacked accuracy when there were excessive partial-volume effects. CONCLUSION: We propose quality assessment criteria and metrics for gray-matter visualization and apply them to different protocols. The proposed criteria and metrics, the analyzed protocols, and our open-source code can serve as a benchmark for future optimization of spinal cord gray-matter imaging protocols.

Shim optimization with region of interest-specific Tikhonov regularization: Application to second-order slice-wise shimming of the brain.

PURPOSE: Slice-wise shimming can improve field homogeneity, but suffers from large noise propagation in the shim calculation. Here, we propose a robust shim current optimization for higher-order dynamic shim updating, based on Tikhonov regularization with a variable regularization parameter, λ . THEORY AND METHODS: λ was selected for each slice separately in a fully automatic procedure based on a combination of boundary constraints and an L-curve search algorithm. Shimming performance was evaluated for second order slice-wise shimming of the brain at 7T, by simulation on a database of field maps from 143 subjects, and by direct measurements in 8 subjects. RESULTS: Simulations yielded on average 36% reduction in the shim current norm for just 0.4 Hz increase in residual field SD as compared to unconstrained unregularized optimization. In vivo results yielded on average 34.0 Hz residual field SD as compared to 34.3 Hz with a constrained unregularized optimization, while simultaneously reducing the shim current norm to 2.8 A from 3.9 A. The proposed regularization also reduced the average step in the shim current between slices. CONCLUSION: Slice-wise variable Tikhonov regularization yielded reduced current norm and current steps to a negligible cost in field inhomogeneity. The method holds promise to increase the robustness, and thereby the utility, of higher-order shim updating.

Fast iterative pre-emphasis calibration method enabling third-order dynamic shim updated fMRI.

PURPOSE: To calibrate a pre-emphasis to sufficiently compensate eddy currents for application of dynamic shim updating to fMRI without extension of scan times. METHODS: Eddy current effects induced into all shim terms up to third-order were characterized by spatiotemporal field monitoring, using a third-order field camera. Pre-emphasis settings were derived from the measurements and iteratively evaluated and refined. The calibrated pre-emphasis was applied to slice-wise dynamic shim updating in combination with a dynamic excitation frequency (F0) determination and a slice-wise B0 optimization routine for in vivo echo planar imaging and resting-state functional MRI. RESULTS: The described method for pre-emphasis calibration led to settling times of remaining eddy current effects below 2 ms, allowing for the application of dynamic shim updating to fMRI without extension of scan times or induction of eddy current related artifacts. A dynamic F0 determination compensates frequency shifts induced by the superposition of different shim fields, and therefore, prevents an image shift within the field of view. Hardware limitations necessitate the reduction of the maximum applicable B0 shim field amplitudes and restrict the shim performance. CONCLUSION: The proposed method enables accurate pre-emphasis calibration, and therefore, the application of dynamic shim updating to fMRI.