Calibration-free regional RF shims for MRS

Abstract

Purpose: Achieving a desired RF transmit field ( $B_1^{+}$ ) in small regions of interest is critical for single-voxel MRS at ultrahigh field. Radio-frequency (RF) shimming, using parallel transmission, requires $B_1^{+}$ mapping and optimization, which limits its ease of use. This work aimed to generate calibration-free RF shims for predefined target regions of interest, which can be applied to any participant, to produce a desired absolute magnitude $B_1^{+}$ (| $B_1^{+}$ |).

Methods: The RF shims were found offline by joint optimization on a database comprising $B_1^{+}$ maps from 11 subjects, considering regions of interest in occipital cortex, hippocampus and posterior cingulate, as well as whole brain. The | $B_1^{+}$ | achieved was compared with a tailored shimming approach, and MR spectra were acquired using tailored and calibration-free shims in 4 participants. Global and local 10g specific-absorption-rate deposition were estimated using Duke and Ella dielectric models.

Results: There was no difference in the mean | $B_1^{+}$ | produced using calibration-free versus tailored RF shimming in the occipital cortex (p = .15), hippocampus (p = .5), or posterior cingulate (p = .98), although differences were observed in the RMS error | $B_1^{+}$ |. Spectra acquired using calibration-free shims had similar SNR and low residual water signal. Under identical power settings, specific-absorption-rate deposition was lower compared with operating in quadrature mode. For example, the total head specific absorption rate was around 35% less for the occipital cortex.

Conclusion: This work demonstrates that static RF shims, optimized offline for small regions, avoid the need for $B_1^{+}$ mapping and optimization for each region of interest and participant. Furthermore, power settings may be increased when using calibration-free shims, to better take advantage of RF shimming.

Keywords: ${\mathrm{B}}_1^{+}$; 7 T; MR spectroscopy; RF shimming; parallel transmission; universal.