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

Yuhang Shi,Signe Johanna Vannesjo,Stuart Clare

doi:10.1002/mrm.28951

Yuhang Shi, Signe Johanna Vannesjo + Show 1 more

Open Access

https://doi.org/10.1002/mrm.28951

Copy DOI

Abstract

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, . THEORY AND METHODS: 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. 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. 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.

Highlights

Most MR acquisitions benefit from a homogeneous background magnetic field, especially imaging techniques relying on fast echo planar imaging (EPI) readouts, such as functional MRI and diffusion-weighted imaging
We present a novel approach to regularized shim optimization based on Tikhonov regularization, where the degree of regularization is individually tuned for each region of interest (ROI)
We have here presented a novel approach to regularized shim optimization based on a ROI-wise variable Tikhonov regularization

Summary

Introduction

Most MR acquisitions benefit from a homogeneous background magnetic field, especially imaging techniques relying on fast echo planar imaging (EPI) readouts, such as functional MRI and diffusion-weighted imaging. . |2 scanners are equipped with shim coils that generate low- order spherical harmonic magnetic fields.[1,2] The currents through the shim coils are adjusted to improve magnetic field homogeneity within a given region of interest (ROI). The ROI is defined to be the full imaging volume, such as the whole brain. Optimizing the shims for smaller volumes can generally improve field homogeneity further, as the field in smaller regions can be better approximated by low-order spherical harmonics.[3] it has been suggested to perform shimming on a slice-wise basis instead of over the full imaging volume in 2D imaging. Slice-wise shimming has been shown to improve field homogeneity and geometric accuracy of EPI acquisitions in high-field brain imaging.4-8

Methods

Findings

Discussion

Conclusion