Impact of gradient scheme and non-linear shimming on out-of-voxel echo artifacts in edited MRS

Abstract

Out-of-voxel (OOV) signals are common spurious echo artifacts in MRS. These signals often manifest in the spectrum as very strong "ripples," which interfere with spectral quantification by overlapping with targeted metabolite resonances. Dephasing optimization through coherence order pathway selection (DOTCOPS) gradient schemes are algorithmically optimized to suppress all potential alternative coherence transfer pathways (CTPs), and should suppress unwanted OOV echoes. In addition, second-order shimming uses non-linear gradient fields to maximize field homogeneity inside the voxel, which unfortunately increases the diversity of local gradient fields outside of the voxel. Given that strong local spatial B₀ gradients can refocus unintended CTPs, it is possible that OOVs are less prevalent when only linear first-order shimming is applied. Here we compare the size of unwanted OOV signals in Hadamard-edited (HERMES) data acquired with either a local gradient scheme (which we refer to here as "Shared") or DOTCOPS, and with first- or second-order shimming. We collected data from 15 healthy volunteers in two brain regions (voxel size 30 × 26 × 26 mm³ ) from which it is challenging to acquire MRS data: medial prefrontal cortex and left temporal cortex. Characteristic OOV echoes were seen in both GABA- and GSH-edited spectra for both brain regions, gradient schemes, and shimming approaches. A linear mixed-effect model revealed a statistically significant difference in the average residual based on the gradient scheme in both GABA- (p < 0.001) and GSH-edited (p < 0.001) spectra: that is, the DOTCOPS gradient scheme resulted in smaller OOV artifacts compared with the Shared scheme. There were no significant differences in OOV artifacts associated with shimming method. Thus, these results suggest that the DOTCOPS gradient scheme for J-difference-edited PRESS acquisitions yields spectra with smaller OOV echo artifacts than the Shared gradient scheme implemented in a widely disseminated editing sequence.

Keywords: DOTCOPS; GABA; GSH; HERMES; coherence transfer pathway (CTP); out of voxel (OOV).

Figure 1.

PRESS pulses sequence and coherence transfer pathway (CTP) diagram. The intended CTP is shown in black, and one example of an undesirable coherence pathway is shown in red.

Figure 2.

A. DOTCOPS and Philips “Shared” Gradient schemes. Values are gradient areas in units of mT.ms/m. B. In vivo HERMES spectra were acquired from medial prefrontal (MPFC) and left temporal cortex (LTC) voxels (30 × 26 × 26 mm³), shown here for a single exemplar subject. C. Edited difference spectrum and Osprey model of both GABA and GSH for DOTCOPS data from a single, randomly selected exemplar subject. This spectrum shows several small OOV echoes between 3.5 and 4 ppm. Gold line: Model. Green line: Spectrum. Blue line: Model residual (i.e., the difference in Spectrum-Model).

Figure 3.

GABA- and GSH-edited difference spectra overlaid from all subjects, for two regions with or without line-broadening (LB): A medial prefrontal (MPFC) without LB, B MPFC with line-broadening, C left temporal cortex (LTC) without LB, and D LTC with LB. Spectra acquired with the Shared and DOTCOPS gradient schemes are depicted in gold and cyan, respectively. Mean spectra calculated across subjects are depicted in black. Data acquired with shimming to the first- or second-order are labeled 1° and 2°, respectively.

Figure 4.

Ball and whisker plots of the model residuals of the two gradient schemes, shimming orders, and brain regions for both GABA- and GSH-edited spectra. (A) medial prefrontal cortex (MPFC) voxel; (B) left temporal cortex (LTC) voxel. Data acquired with the DOTCOPS and Shared gradient schemes are depicted in cyan and gold, respectively. Data acquired with shimming to the first- or second-order are labeled 1° and 2°, respectively. Open white circles indicate group-mean values. Whiskers represent mean ± SD.