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. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: Magn Reson Med. 2023 Dec 3;91(4):1314–1322. doi: 10.1002/mrm.29929

Glutamate Measurements using Edited Magnetic Resonance Spectroscopy

Muhammad G Saleh 1,2,*, Andrew Prescot 3, Linda Chang 4, Christine Cloak 4, Eric Cunningham 4, Punitha Subramaniam 5,6, Perry F Renshaw 5,6, Deborah Yurgelun-Todd 5,6, Helge J Zöllner 7,8, Timothy PL Roberts 1,2, Richard AE Edden 7,8, Thomas Ernst 4
PMCID: PMC10865745  NIHMSID: NIHMS1943283  PMID: 38044723

Abstract

Purpose:

To demonstrate J-difference co-editing of glutamate using Hadamard Encoding and Reconstruction of Mega-Edited Spectroscopy (HERMES).

Methods:

Density-matrix simulations of HERMES (TE 80 ms) and 1D J-resolved (TE 31-229 ms) of glutamate (Glu), glutamine (Gln), γ-aminobutyric acid (GABA), and glutathione (GSH) were performed. HERMES comprised four sub-experiments with editing pulses applied as follows: A) 1.9/4.56 ppm simultaneously (ONGABA /ONGSH); B) 1.9 ppm only (ONGABA/OFFGSH); C) 4.56 ppm only (OFFGABA/ONGSH); and D) 7.5 ppm (OFFGABA/OFFGSH). Phantom HERMES and 1D J-resolved experiments of Glu were performed. Finally, in vivo HERMES (20-ms editing pulses) and 1D J-resolved (TE 31-229 ms) experiments were performed on 137 participants using Siemens 3T MRI scanners. LCModel was used for quantification.

Results:

HERMES simulation and phantom experiments show a Glu-edited signal at 2.34 ppm in the Hadamard sum combination A+B+C+D with no overlapping Gln signal. The J-resolved simulations and phantom experiments show substantial TE-modulation of the Glu and Gln signals across the TEs, whose average yields a well-resolved Glu signal closely matching the Glu-edited signal from the HERMES sum spectrum. In vivo quantification of Glu show that the two methods are highly correlated (p<0.001) with a bias of ~10%, along with similar between-subject coefficients of variation (HERMES/TE-averaged: ~7.3%/~6.9%). Other Hadamard combinations produce the expected GABA-edited (A+B−C−D) or GSH-edited (A−B+C−D) signal.

Conclusion:

HERMES simulation and phantom experiments show the separation of Glu from Gln. In vivo HERMES experiments yield Glu (without Gln), GABA, and GSH in a single MRS scan.

Keywords: glutamate, J-difference, HERMES, GABA, glutathione

Introduction

Glutamate (Glu) is an excitatory neurotransmitter in the central nervous system. Glu serves as a precursor of various metabolites, including the inhibitory neurotransmitter γ-aminobutyric acid (GABA) and the antioxidant glutathione (GSH). Glu may play an important role in brain development and pathology (1), including schizophrenia, epilepsy, amyotrophic lateral sclerosis, stroke, and traumatic brain injury.

Proton (1H) magnetic resonance spectroscopy (MRS) is a non-invasive technique that can measure brain Glu levels in healthy and patient populations. However, measurements of Glu are complicated due to its complex J-coupling spin systems, overlapping with glutamine (Gln) and N-acetyl compounds (N-acetyl aspartate NAA and N-acetylaspartylglutamate NAAG) when measured using MRI at clinical field strengths (≤3T). Several 1H-MRS methods were proposed to reduce these overlapping signals and acquire a purer Glu signal. These methods included optimizing sequence timing parameters and excellent shimming (2, 3), using very short-TE to minimize T2 relaxations effects and limit peak phase modulation, or long TEs (>40 ms) to allow J-modulation effects for a better detection of Glu at the cost of T2-related signal losses (4). Acquiring Glu at ultra-high-field scanners (5), employing chemical exchange saturation transfer between bulk water and Glu (GluCEST) (6), or employing singlet-order filtering can yield cleaner Glu signal (7). Another method is the TE-averaged experiment, which is equivalent to the one-dimensional (1D) J-resolved (indirect dimension, F1= 0) point resolved spectroscopy (PRESS) to resolve the Glu peak (8). The TE-averaged method acquires and averages 1D spectra for a range of TEs to produce a TE-averaged spectrum, with the Glu signal uncontaminated with Gln or NAA. It is a simple and reliable method, but the resulting spectrum has a low resolution arising from the coupling evolution of other metabolites.

The Glu spin system consists of a methine (CH) group with a chemical shift at 3.74 ppm, one methylene (CH2) group with chemical shifts at 2.03 ppm and 2.12 ppm (center at ~2.08 ppm), and another CH2 group at 2.33 ppm and 2.35 ppm (center at ~2.34 ppm) (9). Although these groups are coupled to each other, the two CH2 groups provide a unique opportunity for edited detection of Glu. J-difference editing methods, such as MEscher-GArwood PRESS (MEGA-PRESS (10)), reduce signal overlap by detecting one J-coupled brain metabolite selectively. Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) extends the MEGA functionality to allow selective detection of multiple metabolites simultaneously, such as GABA and GSH (11). In the HERMES of GABA and GSH experiment, editing pulses are applied at 1.9 ppm to edit GABA, partially inverting (co-editing) the Glu spins at 2.08 ppm and refocusing (co-detecting) the Glu spins at 2.34 ppm. However, the co-detection of Glu at 2.34 ppm has not been assessed. Therefore, through simulations and in vivo experiments, we demonstrate the co-editing of Glu using the HERMES of GABA and GSH, followed by a comparison with the 1D J-resolved PRESS (TE-averaged) measurements of Glu. In comparing these two methods, we consider potential factors that introduce variance and bias between the methods, including macromolecules and editing efficiency.

Methods

MR imaging and spectroscopy (MRI/MRS) experiments were performed using 3T MRI scanners (Siemens, Erlangen, Germany). Adolescent participants who fulfilled the MRS substudy criteria were co-enrolled from the Adolescent Brain Cognitive Development (ABCD) study near the time of their 3-year follow-up visit. The study and consent were approved by a central Institutional Review Board at the University of California San Diego and the local IRBs at the University of Maryland Baltimore and the University of Utah. Parents gave written permission, and youths signed assents to participate.

Simulations:

Density-matrix simulations (12, 13) of the Glu, Gln, GABA, and GSH spins systems were performed following the HERMES-PRESS and 1D J-resolved PRESS experiments in MRSCloud (14). HERMES comprised four sub-experiments with editing pulses applied as follows: A) 1.9/4.56 ppm simultaneously (ONGABA /ONGSH); B) 1.9 ppm only (ONGABA/OFFGSH); C) 4.56 ppm only (OFFGABA/ONGSH); and D) 7.5 ppm (OFFGABA/OFFGSH). The ONGABA editing lobe fully inverted the GABA spins at 1.9 ppm, partially inverted the Glu spins at 2.08 ppm and the Gln spins at 2.12 ppm. The ONGSH editing lobe fully inverted the GSH signal at 4.56 ppm. The 1D J-resolved PRESS TE-series involved TEs ranging from 31 ms to 229 ms in steps of 2 ms. All simulations were performed using the following parameters: ideal excitation pulse; 101x101 two-dimensional spatial array in the refocusing dimensions; 8192 complex data points; 4 kHz spectral width; simulated linewidth of 2 Hz. The integral of the detected Glu signal (range: 2.31–2.38 ppm) from the HERMES sum spectrum was calculated. Another ideal pulse-acquire simulation (“zero-TE”) was performed for the Glu signal to determine the total available signal (Stotal) without scalar coupling evolution. Editing efficiency was calculated as the ratio of the integral of the edited signal in the HERMES sum spectrum normalized to the Stotal integral of the respective signal (using the same ppm range). In the context of this work, we also extended this definition to include the analogous signal from the TE-averaged spectrum.

Phantom Experiments:

Phantom HERMES and 1D J-PRESS experiments were carried out in two separate phantoms to determine the bias between the two methods: a) creatine (Cr), Gln, Glu (each 20 mM, pH 7.3); b) Cr and Glu (each 20mM, pH 7.3). HERMES acquisition was performed using the PRESS localizer with the following parameters: TR/TE 2000/80 ms; 20-ms editing pulses (60.5 Hz FWHM); 2048 datapoints; 2 kHz spectral width; 3x3x3 cm3 voxel size; 64 transients; and WET water suppression. The PRESS sequence acquired multi-TE (1D J-PRESS) data using the above HERMES parameters, except TE 30-235 ms in steps of 5 ms and 32 transients per TE.

In vivo Acquisition:

In vivo experiments were performed on 137 participants (64/73 girls/boys; age: 13.1±0.7 years). In every participant, a whole-brain T1-weighted 1 mm3 structural image was acquired to guide voxel placements in the frontal grey matter (GM) (Figure 2a). The multi-vendor standardized HERMES and J-resolved PRESS sequences were performed for each voxel (11, 15) with the same parameters as the phantom experiments, except 3x2.5x2.5 cm3 voxel size, 320 transients for HERMES, and TE 31-229 ms in steps of 2 ms (100 steps total and 4 transients per TE) for J-PRESS. For every participant, the scan time for HERMES was ~11 min and the J-resolved PRESS was ~14 min.

Data Processing:

HERMES data were frequency-and-phase corrected using the spectral registration (16). The 3.02-ppm total creatine (tCr=creatine+phosphocreatine) signal was used to estimate B0 drift in the in vivo data before frequency-and-phase correction. Finally, the fully processed HERMES sub-spectra were combined to generate GABA-edited, GSH-edited, and sum spectra. The residual water signal was removed using an HSVD filter (17). The multi-TE MRS PRESS data were processed using in-house functions written in MATLAB (MATLAB, Mathworks Inc), as described elsewhere (18). Finally, the processed data were averaged across all TE steps to generate the TE-averaged data.

Data Modeling:

The HERMES sum and TE-averaged spectra from phantom and in vivo experiments were modeled using LCModel (6.3-1N, http://s-provencher.com/lcmodel.shtml). 2D localized density-matrix simulations were performed using the abovementioned HERMES and PRESS simulation parameters to generate LCModel basis sets, which included the following metabolites: alanine, ascorbate, aspartate, tCr, GABA, glycerophosphocholine (GPC), GSH, Glu, Gln, glycine, myo-inositol, lactate, NAA, NAAG, phosphocholine (PCh), phosphocreatine (PCr), scyllo-inositol, and taurine. The LCModel analysis was performed without macromolecule (MM) and lipid basis functions and later repeated with the default MM and lipid basis functions. Glu estimates were obtained from the sum and TE-averaged spectra as basis-function amplitude ratios relative to the corresponding Cr (for phantom) or in vivo tCr. The LCModel outputs were also used to estimate signal linewidth in Hz. The in vivo ratios were corrected for T2-relaxation effects using the values outlined previously (4). For the phantom data, only the relevant simulated signals were included in the LCModel analysis. The phantom data were analyzed with no baseline (NOBASE=T) and MM/lipid basis functions in LCModel. Using the phantom with Glu and Cr only, the T2 values were calculated by fitting monoexponential functions to the basis-function amplitudes and later used for the T2 correction of the phantom Glu/Cr ratio. The effective TE for the multi-TE PRESS acquisitions was 132.5 and 130 ms for the phantom and in vivo data, respectively.

Statistical Analysis:

The mean and three times the standard deviation (SD) of the Cramer Rao Lower Bounds (CRLB) of Glu models (from the combined analysis with and without the MM and lipid basis functions) were obtained from LCModel for each method. The Glu models had 3SD above the mean error value of ~5.4% for HERMES and ~6.9% for TE-averaged modeled spectra. These values were used as thresholds for data rejection before further analysis. Data from both methods were also visually assessed for lipid contamination. Correlation analysis was performed using Pearson or Spearman correlations (depending on the residual distribution) to examine the association between HERMES and TE-averaged Glu. Bland Altman analysis was performed to determine agreement between the methods. Between-subject coefficients of variation (CoV) were calculated as the standard deviation of Glu/tCr divided by their corresponding mean, separately for each sequence. All values are presented as mean or mean ± SD unless stated otherwise.

Results

Simulated Experiments

Density matrix simulations of Glu, Gln, GABA, and GSH spin systems following the HERMES experiment are shown in Figure 1b. As expected, simulated sub-experiments showed the modulation of the above spin systems across all four subexperiments. Specifically, the Glu, Gln and GABA signals were affected by the ONGABA editing lobe in the sub-experiments A and B. The ONGABA lobe partially inverted the Glu (2.08 ppm) and Gln (2.12 ppm) spins, and fully inverted the GABA (1.9 ppm) spins, resulting in the refocusing of coupling evolution of signals at 2.34, 2.44 ppm and 2.28 ppm. However, in sub-experiments C and D (OFFGABA), the Glu, Gln, and GABA signals freely evolved, with the outer peaks acquiring opposite phases, but the center peaks did not evolve. The Hadamard combination of sub-experiments A+B+C+D (sum) substantially reduced the amplitude of the outer peaks, eliminating the overlap among the Glu, Gln, and GABA signals. Other Hadamard combinations produced the GABA-edited (A+B−C−D) or GSH-edited (A−B+C−D) signal.

Figure 1:

Figure 1:

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HERMES and the one-dimensional (1D) J-resolved simulations: a) Inversion profiles of editing pulses in the HERMES sub-experiments A-D editing Glu, GABA, and GSH; b) The Hadamard combinations of sub-experiments A-D result in the sum spectrum (A+B+C+D) with the Glu-edited signal without the Gln and GABA overlap, A+B−C−D spectrum with the GABA-edited signal, and A−B+C−D spectrum with the GSH-edited signal. c) The 1D J-resolved experiment shows the TE modulation of Glu, Gln, and GABA signals. The average of these signals yields the TE-averaged spectrum with the well-resolved and cleaner Glu signal without the Gln and GABA overlap. Phantom experiments in a Glu, Gln, and Cr phantom: d) The HERMES experiment at TE 80 ms shows refocusing of the Gln and Glu signals in experiments A and B and free evolution of these signals in experiments C and D; the sum spectrum (A+B+C+D) yields the Glu-edited signal without the Gln overlap; e) The 1D J-PRESS experiment shows the TE modulation of the Glu and Gln signals. The TE-averaged spectrum yields the Glu signal without the Gln overlap.

In the TE-averaged experiment, the multiplet pattern and intensity of the Glu, Gln, and GABA signals change with TE due to the coupling evolution (Figure 1c). More specifically, these signals evolved along TEs such that the outer peaks evolved, but the center peak remained unchanged. The TE-averaged spectrum averaged the data within the range of TEs, canceling the outer peaks and leaving the center peak, yielding a well-resolved Glu signal without the Gln and GABA overlap. Consequently, the TE-averaged Glu signal closely matched the Glu-edited signal from the HERMES sum spectrum. The Glu editing efficiency was ~39% for HERMES and ~41% for TE-averaged.

Phantom Experiments

Using both methods, the phantom experiments in the Glu, Gln, and Cr phantom showed excellent separation between the Glu and Gln signals (Figures 1d and 1e). The Glu/Cr ratio was comparable between the two methods (HERMES/TE-averaged: 1.411/1.312) with a 7% absolute bias (∣differences between values∣/average of values).

The other phantom (Glu and Cr only) also revealed the Glu-edited signal using both methods (Figure S1). Using the multi-TE data, the estimated T2 value was 262 ms for Glu and 632 ms for Cr. The T2-corrected Glu/Cr ratio had an absolute bias of 0.9% (1.479/1.465).

In Vivo Experiments

All participants successfully completed the MRS scans for the study. Figures 2b and c show typical HERMES sum (A+B+C+D), HERMES-edited (A+B−C−D and A−B+C−D), and TE-averaged spectra from the frontal grey matter. The HERMES spectra show a well-resolved Glu-edited signal at 2.34 ppm, a GABA-edited signal at 3 ppm, and a GSH-edited signal at 2.95 ppm. The main magnetic field (B0) drift during the acquisition was 1.6±1.5 Hz, suggesting excellent frequency stability. Figure 3 shows HERMES and TE-averaged spectra overlaid with their respective Glu, Gln, and GABA models from the LCModel fitting. The modeled data (with and without MM and lipid modeling) show contributions from the Glu signals with negligible overlap from the neighboring Gln and GABA signals.

Figure 2:

Figure 2:

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a) Voxel localization in the frontal grey matter for the in vivo experiments using the HERMES and 1D J-resolved methods. b) HERMES spectra with the Glu-edited (A+B+C+D), GABA-edited (A+B−C−D), and GSH-edited (A−B+C−D) signals. c) TE-averaged spectrum with the resolved Glu signal at 2.34 ppm.

Figure 3:

Figure 3:

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Data Modeling without (left) and with (right) the default macromolecular and lipid basis functions in LCModel: a and b) HERMES sum and c and d) TE-averaged spectra.

Four HERMES sum and three TE-averaged spectra were removed before the final group analysis due to considerable lipid contamination or the Glu CRLBs exceeding the threshold. After removal, the linewidths/Glu CRLBs was 3.1±0.5Hz/3.9±0.4% for the HERMES spectra and 4.0±1.0Hz/3.4±0.5% for the TE-averaged spectra, indicating excellent magnetic field homogeneity and modeling of the Glu signals. In both analyses, Glu/tCr estimates from the HERMES were slightly lower than the estimates from the TE-averaged method (1.0133±0.0742/1.1184±0.0778 without the MM and lipid modeling; 1.0134±0.0746/1.1195±0.0777 with the modeling). Between-subject coefficients of variation (CoV) in Glu measurements were similar between the two methods in both analyses (HERMES/TE-averaged: ~7.3%/~6.9%). The correlations and Bland Altman analysis between the HERMES sum and TE-averaged measurements are shown in Figure 4. Irrespective of the inclusion of the MM and lipids basis functions, significant correlations (p<0.001) and ~10% biases (~20% before T2 correction) were observed between the two methods.

Figure 4:

Figure 4:

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Correlations (a and b) and Bland-Altman analysis (c and d) of T2-corrected ratios estimated without (left) and with (right) the default macromolecular and lipid basis functions in LCModel. For Bland-Altman analyses (bottom), the difference (y-axis) is calculated (TE-averaged – Sum) relative to the means and expressed as a percentage; solid lines represent the mean of the difference; dotted lines represent the 95% confidence interval.

Discussion

In this study, we exploited the coupling evolution of Glu using HERMES to successfully co-edit Glu (with no Gln and GABA overlap) along with GABA and GSH. Since Glu is a precursor of GSH and GABA, all three chemicals are metabolically related. HERMES provides a unique opportunity to study all three chemicals concurrently to understand their relationships under homeostasis or drug interventions that might affect the glutamatergic, GABAergic, or antioxidant systems (19-21).

Simulation of the HERMES experiment shows editing and excellent separation of Glu, GABA, and GSH signals in their respective Hadamard combinations. Simulations closely match the phantom results. Specifically, the HERMES sum spectrum shows the Glu-edited signal separated from the Gln-edited signal, showing an excellent resemblance with the TE-averaged Glu signal.

The HERMES and TE-averaged in vivo data demonstrate excellent separation of Glu from Gln, with similar measurement variations and significant correlation between methods. Both in vivo and phantom experiments revealed an improvement in bias after the T2 correction, suggesting that including T2 in the Glu quantification benefits the agreement between the methods. The remaining bias in the in vivo data could be due to the differences in macromolecular contribution. Although we included MM in our in vivo analyses, the MM profiles were not method-specific. The in vivo MM profile for both methods can be acquired using an inversion pulse before localization to cause metabolite nulling and later included in the basis functions to model Glu and MM. However, this approach requires separate experiments, increasing scan time. Other factors that might differentially impact the methods include editing efficiency, subtraction artifacts remaining in the HERMES spectra, and inaccuracies in simulations (e.g., related to imperfect spin system parametrization). The editing efficiency should not be considered as an explicit factor since we rely on the simulated basis functions for quantification. Simulations consider editing efficiency as the modulation of signal intensity to properly model the in vivo Glu-edited signal. Linear combination modeling is widely performed using simulated basis sets rather than experimentally acquired basis sets. Further refinement of spin system parameters is important and can improve measurement accuracy (22, 23). This study used PRESS to localize the region of interest. Incorporating HERMES in other localization sequences with increased bandwidth and better slice profiles (24, 25) can reduce chemical shift displacement artifacts, permit short acquisitions with sufficient SNR, and further improve measurement variation.

One issue for editing Glu at 2.34 ppm is the limited chemical shift difference between the Glu spins (detected at 2.34 ppm and targeted at 2.08 ppm, ~33 Hz at 3T). In this study, we employed the standardized HERMES experiment for GABA and GSH editing, with 20-ms editing pulses with 60.5 Hz bandwidth (FWHM) that resulted in ~8% inversion of the co-detected Glu signal. Despite the inversion, the editing efficiency of the two methods is similar. HERMES is sensitive to subject and hardware instability and can adversely affect editing and reduce efficiency. Including prospective motion and frequency corrections in the HERMES sequence will ensure robust editing of Glu (26). The duration of the editing pulses restricted the minimum achievable TE to 80 ms with a peak radiofrequency field (B1) limit of 13.5 uT. Usually, signals with triplet-like multiplets, such as Glu at 2.34 ppm, can be optimally edited at TE 68-80 ms (27, 28). This is supported by our simulation, phantom, and in vivo experiments of HERMES at TE 80 ms, yielding excellent Glu-edited signal, strongly resembling the TE-averaged signal, and significantly correlating with the TE-averaged measurements.

Conclusion

In summary, we demonstrated measurements of Glu using edited MRS. We employed HERMES to deliver Glu, GABA, and GSH simultaneously in a single in vivo MRS experiment.

Supplementary Material

Supinfo1
Supinfo2
Supinfo3

Figure S1: Phantom experiments in a Glu and Cr phantom. a) The HERMES experiment at TE 80 ms yields the Glu-edited signal in the sum spectrum (A+B+C+D). b) The 1D J-PRESS experiment yields the Glu and Cr signal in the TE-averaged spectrum. c) and d) The signal intensities of Glu and Cr (from the modeled multi-TE data) plotted against TE, respectively. Models are from the LCModel software. The LCModel fitting range was 0.6 and 3.4 ppm.

Figure S2: Bland-Altman analysis using the T2-corrected a) tNAA/tCr, b) tCho/tCr, and c) mI/tCr ratios from the TE-averaged and HERMES sum spectra without the default macromolecular and lipid basis functions in LCModel. The difference (y-axis) is calculated (TE-averaged – Sum) relative to the means and expressed as a percentage; solid lines represent the mean of the difference; dotted lines represent the 95% confidence interval.

Acknowledgement

This work was supported by NIH grants R00DA051315, R21DA047673, U01DA041134, U01DA041117, R01 EB016089, R01 EB023963, P41 EB031771.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supinfo1
NIHMS1943283-supplement-Supinfo1.md (1.8KB, md)
Supinfo2
NIHMS1943283-supplement-Supinfo2.md (1.9KB, md)
Supinfo3

Figure S1: Phantom experiments in a Glu and Cr phantom. a) The HERMES experiment at TE 80 ms yields the Glu-edited signal in the sum spectrum (A+B+C+D). b) The 1D J-PRESS experiment yields the Glu and Cr signal in the TE-averaged spectrum. c) and d) The signal intensities of Glu and Cr (from the modeled multi-TE data) plotted against TE, respectively. Models are from the LCModel software. The LCModel fitting range was 0.6 and 3.4 ppm.

Figure S2: Bland-Altman analysis using the T2-corrected a) tNAA/tCr, b) tCho/tCr, and c) mI/tCr ratios from the TE-averaged and HERMES sum spectra without the default macromolecular and lipid basis functions in LCModel. The difference (y-axis) is calculated (TE-averaged – Sum) relative to the means and expressed as a percentage; solid lines represent the mean of the difference; dotted lines represent the 95% confidence interval.

NIHMS1943283-supplement-Supinfo3.pdf (288.1KB, pdf)

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