1H and 31P magnetic resonance spectroscopy reveals potential pathogenic and biomarker metabolite alterations in Lafora disease.

Lafora disease is a fatal teenage-onset progressive myoclonus epilepsy and neurodegenerative disease associated with polyglucosan bodies. Polyglucosans are long-branched and as a result precipitation- and aggregation-prone glycogen. In mouse models, downregulation of glycogen synthase, the enzyme that elongates glycogen branches, prevents polyglucosan formation and rescues Lafora disease. Mouse work, however, has not yet revealed the mechanisms of polyglucosan generation, and few in vivo human studies have been performed. Here, non-invasive in vivo magnetic resonance spectroscopy (1H and 31P) was applied to test scan feasibility and assess neurotransmitter balance and energy metabolism in Lafora disease towards a better understanding of pathogenesis. Macromolecule-suppressed gamma-aminobutyric acid (GABA)-edited 1H magnetic resonance spectroscopy and 31P magnetic resonance spectroscopy at 3 and 7 tesla, respectively, were performed in 4 Lafora disease patients and a total of 21 healthy controls (12 for the 1H magnetic resonance spectroscopy and 9 for the 31PMRS). Spectra were processed using in-house software and fit to extract metabolite concentrations. From the 1H spectra, we found 33% lower GABA concentrations (P = 0.013), 34% higher glutamate + glutamine concentrations (P = 0.011) and 24% lower N-acetylaspartate concentrations (P = 0.0043) in Lafora disease patients compared with controls. From the 31P spectra, we found 34% higher phosphoethanolamine concentrations (P = 0.016), 23% lower nicotinamide adenine dinucleotide concentrations (P = 0.003), 50% higher uridine diphosphate glucose concentrations (P = 0.004) and 225% higher glucose 6-phosphate concentrations in Lafora disease patients versus controls (P = 0.004). Uridine diphosphate glucose is the substrate of glycogen synthase, and glucose 6-phosphate is its extremely potent allosteric activator. The observed elevated uridine diphosphate glucose and glucose 6-phosphate levels are expected to hyperactivate glycogen synthase and may underlie the generation of polyglucosans in Lafora disease. The increased glutamate + glutamine and reduced GABA indicate altered neurotransmission and energy metabolism, which may contribute to the disease's intractable epilepsy. These results suggest a possible basis of polyglucosan formation and potential contributions to the epilepsy of Lafora disease. If confirmed in larger human and animal model studies, measurements of the dysregulated metabolites by magnetic resonance spectroscopy could be developed into non-invasive biomarkers for clinical trials.

Metabolic profile of complete spinal cord injury in pons and cerebellum: A 3T 1H MRS study.

The aim of this exploratory study was the assessment of the metabolic profiles of persons with complete spinal cord injury (SCI) in three region-of-interests (pons, cerebellar vermis, and cerebellar hemisphere), with magnetic resonance spectroscopy, and their correlations to clinical scores. Group differences and association between metabolic and clinical scores were examined. Fifteen people with chronic SCI (cSCI), five people with subacute SCI (sSCI) and fourteen healthy controls were included. Group comparison between cSCI and HC showed lower total N-acetyl-aspartate (tNAA) in the pons (p = 0.04) and higher glutathione (GSH) in the cerebellar vermis (p = 0.02). Choline levels in the cerebellar hemisphere were different between cSCI and HC (p = 0.02) and sSCI and HC (p = 0.02). A correlation was reported for choline containing compounds (tCho) to clinical scores in the pons (rho = - 0.55, p = 0.01). tNAA to total creatine (tNAA/tCr ratio) correlated to clinical scores in the cerebellar vermis (rho = 0.61, p = 0.004) and GSH correlated to the independence score in the cerebellar hemisphere (rho = 0.56, p = 0.01). The correlation of tNAA, tCr, tCho and GSH to clinical scores might be indicators on how well the CNS copes with the post-traumatic remodeling and might be further examined as outcome markers.

Improved signal-to-noise performance of MultiNet GRAPPA 1 H FID MRSI reconstruction with semi-synthetic calibration data.

PURPOSE: To further develop MultiNet GRAPPA, a neural-network-based reconstruction, for lower SNR proton MRSI (1 H MRSI) data using adapted undersampling schemes and improved training sets. METHODS: 1 H FID-MRSI data and an anatomical image for GRAPPA reconstruction were acquired in two slices in the human brain (n = 6) at 7T. MRSI data were retrospectively undersampled for a 4×, 6×, and 7× acceleration rate. Signal-to-noise, relative error (RE) between accelerated and fully sampled metabolic maps, RMS of the lipid artifacts, and fitting reliability were compared across acceleration rates, to the fully sampled data, and with different kinds and amounts of training images. RESULTS: Training with semi-synthetic images resulted in higher SNR and lower lipid RMS relative to training with acquired images from one or several subjects. SNR increased with the number of semi-synthetic training images and the 4× accelerated data retains ∼30% more SNR than other accelerated data. Spectra reconstructed with 20 semi-synthetic averages retained ∼100% more SNR and had ∼5% lower lipid RMS than those reconstructed with the center k-space points of one image as was originally proposed for very high SNR MRSI data and had higher fitting reliability. The metabolite RE was lowest when training with 20-semi-synthetic training images and highest when training with the center k-space points of one image. CONCLUSION: MultiNet GRAPPA is feasible with lower SNR 1 H MRSI data if 20-semi-synthetic training images are used at a 4× acceleration rate. This acceleration rate provided the best trade-off between scan time and spectral SNR.

Sensorimotor Cortex GABA Moderates the Relationship between Physical Exertion and Assessments of Effort.

Experiences of physical exertion guide our assessments of effort. While these assessments critically influence our decisions to engage in daily activities, little is known about how they are generated. We had female and male human participants exert grip force and assess how effortful these exertions felt; and used magnetic resonance spectroscopy to measure their brain GABA concentration. We found that variability in exertion (i.e., the coefficient of variation in their force exertion profile) was associated with increases in assessments of effort, making participants judge efforts as more costly. GABA levels in the sensorimotor cortex (SM1) moderated the influence of exertion variability on overassessments of effort. In individuals with higher sensorimotor GABA, exertion variability had a diminished influence on overassessments of effort. Essentially, sensorimotor GABA had a protective effect on the influence of exertion variability on inflations of effort assessment. Our findings provide a neurobiological account of how the brain's GABAergic system integrates features of physical exertion into judgments of effort, and how basic sensorimotor properties may influence higher-order judgments of effort.SIGNIFICANCE STATEMENT Feelings of effort critically shape our decisions to partake in activities of daily living. It remains unclear how the brain translates physical activity into judgments about effort (i.e., "How effortful did that activity feel?"). Using modeling of behavior and neuroimaging, we show how the nervous system uses information about physical exertion to generate assessments of effort. We found that higher variability in exertion was associated with increases in assessments of effort, making participants judge efforts as more costly. GABA, the brain's main inhibitory neurotransmitter, moderated the influence of exertion variability on overassessments of effort. These findings illustrate how low-level features of motor performance and sensorimotor neurochemistry influence higher-order cognitive processes related to feelings of effort.

Multimodal Imaging and Visual Evoked Potentials Reveal Key Structural and Functional Features That Distinguish Symptomatic From Presymptomatic Huntington's Disease Brain.

BACKGROUND: Huntington's disease (HD) is a progressive neurodegenerative disorder characterized by motor, cognitive, and psychiatric abnormalities. Currently, matched analyses of structural and functional differences in the brain from the same study cohort and, specifically, in HD patients from an ethnically diverse Indian population are lacking. Such findings aid in identifying noninvasive and sensitive imaging biomarkers. OBJECTIVE: The aim of the study was to understand the structural and functional differences between HD and control brain, and presymptomatic and symptomatic HD brain in the Indian population. MATERIALS AND METHODS: Seventeen HD (11 symptomatic HD [S-HD] and six presymptomatic HD [P-HD], with comparable CAG repeats), and 12 healthy controls were examined. Macrostructural (volume), microstructural (diffusivity), and functional (neurochemical levels and glucose metabolism) imaging of the brain was done along with the determination of visual latencies. RESULTS: HD brain showed increased intercaudate distance; significant subcortical volumetric loss; reduced fractional anisotropy; increased mean, axial, and radial diffusivity; lower levels of total N-acetyl aspartate; elevated total choline levels; and reduced glucose metabolism compared with control brain. Interestingly, compared with P-HD, S-HD patients demonstrated a strong inverse correlation between age at onset and CAG repeat length, and prolonged P100 latency. In addition, caudate and putamen in S-HD brain showed significant volumetric loss and increased diffusivity compared with P-HD brain. CONCLUSIONS: HD brain showed distinct macrostructural, microstructural, and functional differences compared with control brain in the Indian population. Interestingly, patients with S-HD had a significant volumetric loss, increased diffusivity, altered neurochemical profile, and delayed P100 latency compared with P-HD patients. Examining these alterations clinically could aid in monitoring the progression of HD.

Improved prospective frequency correction for macromolecule-suppressed GABA editing with metabolite cycling at 3T.

PURPOSE: To combine metabolite cycling with J-difference editing (MC MEGA) to allow for prospective frequency correction at each transient without additional acquisitions and compare it to water-suppressed MEGA-PRESS (WS MEGA) editing with intermittent prospective frequency correction. METHODS: Macromolecule-suppressed gamma aminobutyric acid (GABA)-edited experiments were performed in a phantom and in the occipital lobe (OCC) (n = 12) and medial prefrontal cortex (mPFC) (n = 8) of the human brain. Water frequency consistency and average offset over acquisition time were compared. GABA multiplet patterns, signal intensities, and choline subtraction artifacts were evaluated. In vivo GABA concentrations were compared and related to frequency offset in the OCC. RESULTS: MC MEGA was more stable with 21% and 32% smaller water frequency SDs in the OCC and mPFC, respectively. MC MEGA also had 39% and 40% smaller average frequency offsets in the OCC and mPFC, respectively. Phantom GABA multiplet patterns and signal intensities were similar. In vivo GABA concentrations were smaller in MC MEGA than in WS MEGA, with median (interquartile range) of 2.52 (0.27) and 2.29 (0.19) institutional units (i.u.), respectively in the OCC scans without prior DTI, and 0.99 (0.3) and 1.72 (0.5), respectively in the mPFC. OCC WS MEGA GABA concentrations, but not MC MEGA GABA concentrations were moderately correlated with frequency offset. mPFC WS MEGA spectra contained significantly more subtraction artifacts than MC MEGA spectra. CONCLUSION: MC MEGA is feasible and allows for prospective frequency correction at every transient. MC MEGA GABA concentrations were not biased by frequency offsets and contained less subtraction artifacts compared to WS MEGA.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation.

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites.

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. © RSNA, 2020 Online supplemental material is available for this article.

Retrospective motion compensation for edited MR spectroscopic imaging.

Edited magnetic resonance spectroscopic imaging (MRSI) is capable of mapping the distribution of low concentration metabolites such as gamma-aminobutyric acid (GABA) or and glutathione (GSH), but is prone to subtraction artifacts due to head motion or other instabilities. In this study, a retrospective motion compensation algorithm for edited MRSI is proposed. The algorithm identifies movement-affected signals by comparing residual water and lipid peaks between different transients recorded at the same point in k-space, and either phase corrects, replaces or removes affected spectra prior to spatial Fourier transformation. The method was tested on macromolecule-unsuppressed GABA-edited spin-echo MR spectroscopic imaging data acquired from 8 healthy adults scanned at 3T. Relative to non-motion compensated data sets, the motion compensated data had significantly less subtraction artifacts across subjects. The residual choline (Cho) peak in the spectrum (which is well resolved from as a different chemical shift from GABA and is completely absent in a spectrum without subtraction artifact) was used as a metric of motion artifact severity. The normalized Cho area was 5.14 times lower with motion compensation than without motion compensation. A 'removal-only' version of the technique is also shown to be promising in removing motion-corrupted artifacts in a GSH-edited MRSI acquisition acquired in 1 healthy subject. This study introduces a motion compensation technique and demonstrates that retrospective compensation in k-space is possible and significantly reduces the amount of subtraction artifacts in the resulting edited spectra.

Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites.

Accurate and reliable quantification of brain metabolites measured in vivo using 1H magnetic resonance spectroscopy (MRS) is a topic of continued interest. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, spectrally edited γ-aminobutyric acid (GABA) MRS data were analyzed and GABA levels were quantified relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using GABA+ (GABA + co-edited macromolecules (MM)) and MM-suppressed GABA editing. The unsuppressed water signal from the volume of interest was acquired for concentration referencing. Whole-brain T1-weighted structural images were acquired and segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17% for the GABA + data and 29% for the MM-suppressed GABA data. The mean within-site coefficient of variation was 10% for the GABA + data and 19% for the MM-suppressed GABA data. Vendor differences contributed 53% to the total variance in the GABA + data, while the remaining variance was attributed to site- (11%) and participant-level (36%) effects. For the MM-suppressed data, 54% of the variance was attributed to site differences, while the remaining 46% was attributed to participant differences. Results from an exploratory analysis suggested that the vendor differences were related to the unsuppressed water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA measurements exhibit similar levels of variance to creatine-referenced GABA measurements. It is concluded that quantification using internal tissue water referencing is a viable and reliable method for the quantification of in vivo GABA levels.

Simultaneous editing of GABA and GSH with Hadamard-encoded MR spectroscopic imaging.

PURPOSE: To evaluate the feasibility of simultaneous MR spectroscopic imaging (MRSI) of gamma-aminobutyric acid (GABA) and glutathione (GSH) in the human brain using Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES). METHODS: Point RESolved Spectroscopy (PRESS)-localized MRSI was performed in GABA and GSH phantoms and in the human brain (n = 3) using HERMES editing and compared to conventional MEGA editing of each metabolite. Multiplet patterns, signal intensities, and metabolite crosstalk were compared between methods. GABA+ and GSH levels were compared between methods for bias and variability. Linear regression of HERMES-MRSI GABA+/H2 O and GSH/H2 O versus gray matter (GM) fraction were performed to assess differences between GM and white matter (WM). RESULTS: Phantom HERMES-MRSI scans gave comparable GABA+ and GSH signals to MEGA-MRSI across the PRESS-localized volume. In vivo, HERMES-reconstructed GABA+ and GSH values had minimal measurement bias and variability relative to MEGA-MRSI. Intersubject coefficients of variation (CV) from two regions within the PRESS-localized volume for HERMES and MEGA were 6-12% for GABA+ and 6-19% for GSH. Interregion CVs were 5-15% for GABA+ and 3-17% for GSH. The GABA+/H2 O and GSH/H2 O ratios were ~1.8 times higher and ~1.9 times higher, respectively, in GM than in WM. CONCLUSION: HERMES-MRSI of GABA+ and GSH was found to be practical in the human brain with minimal measurement bias and comparable variability to separate MEGA-edited acquisitions of each metabolite performed in double the scan time. The HERMES-MRSI is a promising method for simultaneously mapping the distribution of multiple low-concentration metabolites.

Advanced Hadamard-encoded editing of seven low-concentration brain metabolites: Principles of HERCULES.

PURPOSE: To demonstrate the framework of a novel Hadamard-encoded spectral editing approach for simultaneously detecting multiple low-concentration brain metabolites in vivo at 3T. METHODS: HERCULES (Hadamard Editing Resolves Chemicals Using Linear-combination Estimation of Spectra) is a four-step Hadamard-encoded editing scheme. 20-ms editing pulses are applied at: (A) 4.58 and 1.9 ppm; (B) 4.18 and 1.9 ppm; (C) 4.58 ppm; and (D) 4.18 ppm. Edited signals from γ-aminobutyric acid (GABA), glutathione (GSH), ascorbate (Asc), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), aspartate (Asp), lactate (Lac), and likely 2-hydroxyglutarate (2-HG) are separated with reduced signal overlap into distinct Hadamard combinations: (A+B+C+D); (A+B-C-D); and (A-B+C-D). HERCULES uses a novel multiplexed linear-combination modeling approach, fitting all three Hadamard combinations at the same time, maximizing the amount of information used for model parameter estimation, in order to quantify the levels of these compounds. Fitting also allows estimation of the levels of total choline (tCho), myo-inositol (Ins), glutamate (Glu), and glutamine (Gln). Quantitative HERCULES results were compared between two grey- and white-matter-rich brain regions (11 min acquisition time each) in 10 healthy volunteers. Coefficients of variation (CV) of quantified measurements from the HERCULES fitting approach were compared against those from a single-spectrum fitting approach, and against estimates from short-TE PRESS data. RESULTS: HERCULES successfully segregates overlapping resonances into separate Hadamard combinations, allowing for the estimation of levels of seven coupled metabolites that would usually require a single 11-min editing experiment each. Metabolite levels and CVs agree well with published values. CVs of quantified measurements from the multiplexed HERCULES fitting approach outperform single-spectrum fitting and short-TE PRESS for most of the edited metabolites, performing only slightly to moderately worse than the fitting method that gives the lowest CVs for tCho, NAA, NAAG, and Asp. CONCLUSION: HERCULES is a new experimental approach with the potential for simultaneous editing and multiplexed fitting of up to seven coupled low-concentration and six high-concentration metabolites within a single 11-min acquisition at 3T.

Water suppression in the human brain with hypergeometric RF pulses for single-voxel and multi-voxel MR spectroscopy.

PURPOSE: To develop and investigate a novel water suppression sequence with hypergeometric pulses at 3 T. METHODS: Simulations were used to optimize the delays and amplitudes of 5 hypergeometric prepulses, to minimize the residual water over a range of T1 and B1 values. Single-voxel data with hypergeometric water suppression (HGWS) prepulses were acquired in the centrum semiovale, 2 parietal regions, and insula of 7 subjects, and compared with VAPOR water suppression. Magnetic resonance spectroscopic imaging (MRSI) data using both VAPOR and HGWS prepulses were also collected and compared. Water suppression performance was calculated as the residual water peak height relative to the unsuppressed water peak. MRSI voxel-by-voxel comparison was performed by calculating the ratio between HGWS and VAPOR residual water peaks. RESULTS: In simulations, HGWS and VAPOR are insensitive to B1 and water T1 variations, but with no B1 variation, HGWS has a lower average residual water fraction (0.0033) than that of VAPOR (0.0091). In single-voxel acquisitions, HGWS performs better than VAPOR in all regions with a 2.3-fold to 5.7-fold lower residual water. In MRSI acquisitions, HGWS performs on average 2.3-fold better than VAPOR in 98.9% of the voxels. CONCLUSION: HGWS provides better water suppression than VAPOR in both single-voxel and multivoxel acquisitions with a shorter sequence duration.

Frequency and phase correction for multiplexed edited MRS of GABA and glutathione.

PURPOSE: Detection of endogenous metabolites using multiplexed editing substantially improves the efficiency of edited magnetic resonance spectroscopy. Multiplexed editing (i.e., performing more than one edited experiment in a single acquisition) requires a tailored, robust approach for correction of frequency and phase offsets. Here, a novel method for frequency and phase correction (FPC) based on spectral registration is presented and compared against previously presented approaches. METHODS: One simulated dataset and 40 γ-aminobutyric acid-/glutathione-edited HERMES datasets acquired in vivo at three imaging centers were used to test four FPC approaches: no correction; spectral registration; spectral registration with post hoc choline-creatine alignment; and multistep FPC. The performance of each routine for the simulated dataset was assessed by comparing the estimated frequency/phase offsets against the known values, whereas the performance for the in vivo data was assessed quantitatively by calculation of an alignment quality metric based on choline subtraction artifacts. RESULTS: The multistep FPC approach returned corrections that were closest to the true values for the simulated dataset. Alignment quality scores were on average worst for no correction, and best for multistep FPC in both the γ-aminobutyric acid- and glutathione-edited spectra in the in vivo data. CONCLUSIONS: Multistep FPC results in improved correction of frequency/phase errors in multiplexed γ-aminobutyric acid-/glutathione-edited magnetic resonance spectroscopy experiments. The optimal FPC strategy is experiment-specific, and may even be dataset-specific. Magn Reson Med 80:21-28, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Hadamard editing of glutathione and macromolecule-suppressed GABA.

The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) and the major antioxidant glutathione (GSH) are compounds of high importance for the function and integrity of the human brain. In this study, a method for simultaneous J-difference spectral-edited magnetic resonance spectroscopy (MRS) of GSH and GABA with suppression of macromolecular (MM) signals at 3 T is proposed. MM-suppressed Hadamard encoding and reconstruction of MEGA (Mescher-Garwood)-edited spectroscopy (HERMES) consists of four sub-experiments (TE = 80 ms), with 20-ms editing pulses applied at: (A) 4.56 and 1.9 ppm; (B) 4.56 and 1.5 ppm; (C) 1.9 ppm; and (D) 1.5 ppm. One Hadamard combination (A + B - C - D) yields GSH-edited spectra, and another (A - B + C - D) yields GABA-edited spectra, with symmetric suppression of the co-edited MM signal. MM-suppressed HERMES, conventional HERMES and separate Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) data were successfully acquired from a (33 mm)3 voxel in the parietal lobe in 10 healthy subjects. GSH- and GABA-edited MM-suppressed HERMES spectra were in close agreement with the respective MEGA-PRESS spectra. Mean GABA (and GSH) estimates were 1.10 ± 0.15 i.u. (0.59 ± 0.12 i.u.) for MM-suppressed HERMES, and 1.13 ± 0.09 i.u. (0.66 ± 0.09 i.u.) for MEGA-PRESS. Mean GABA (and GSH) differences between MM-suppressed HERMES and MEGA-PRESS were -0.03 ± 0.11 i.u. (-0.07 ± 0.11 i.u.). The mean signal-to-noise ratio (SNR) improvement of MM-suppressed HERMES over MEGA-PRESS was 1.45 ± 0.25 for GABA and 1.32 ± 0.24 for GSH. These results indicate that symmetric suppression of the MM signal can be accommodated into the Hadamard editing framework. Compared with sequential single-metabolite MEGA-PRESS experiments, MM-suppressed HERMES allows for simultaneous edited measurements of GSH and GABA without MM contamination in only half the scan time, and SNR is maintained.

Simultaneous editing of GABA and glutathione at 7T using semi-LASER localization.

PURPOSE: To demonstrate simultaneous editing of the two most commonly edited and overlapping signals, γ-aminobutyric acid (GABA), and glutathione (GSH), with Hadamard encoding and reconstruction of MEGA-edited spectroscopy (HERMES) using sLASER localization at 7T. METHODS: Density matrix simulations of HERMES at 7T were carried out and compared with phantom experiments. Additional phantom experiments were performed to characterize the echo time (TE) -dependent modulation of GABA- and GSH-edited HERMES spectra at TE of 80-160 ms. In vivo experiments were performed in 10 healthy volunteers, comparing HERMES (11 min) to sequentially acquired MEGA-sLASER detection of GABA and GSH (2 × 11 min). RESULTS: Simulations of HERMES show GABA- and GSH-edited spectra with negligible levels of crosstalk, and give modest agreement with phantom spectra. The TE series of GABA- and GSH-edited HERMES spectra modulate as a result of T2 relaxation and coupling evolution, with GABA showing a stronger TE-dependence. In vivo HERMES experiments show well-edited GABA and GSH signals. Measured concentrations are not statistically different between HERMES and MEGA-sLASER for GABA (1. 051 ± 0.254 i.u. and 1.053 ± 0.248 i.u; P > 0.985) or GSH (0.300 ± 0.091 i.u. and 0.302 ± 0.093 i.u; P > 0.940). CONCLUSION: Simulated, phantom and in vivo measurements of HERMES show excellent segregation of GABA- and GSH-edited signals, and excellent agreement with separately acquired MEGA-sLASER data. HERMES allows two-fold acceleration of editing while maintaining spectral quality compared with sequentially acquired MEGA-sLASER measurements. Magn Reson Med 80:474-479, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Simultaneous detection of glutathione and lactate using spectral editing at 3 T.

Two spectral editing techniques for the simultaneous detection of glutathione (GSH) and lactate (Lac) in the human brain at 3 T are described and evaluated. These methods, 'sMEGA' (sinc-MEscher and GArwood) and 'DEW' (Double Editing With), were optimized to detect GSH and Lac simultaneously at 3 T using density-matrix simulations and validation in phantoms. Simulations to test for co-edited metabolites within the detected GSH region of the spectrum were also performed. In vivo data were acquired in the midline parietal region of seven subjects using both methods, and compared with conventional MEGA-PRESS (MEscher and GArwood-Point RESolved Spectroscopy) acquisitions of GSH and Lac. Simulations and phantom experiments showed that sMEGA and DEW had a high editing efficiency for both GSH and Lac. In the phantom, the editing efficiency of GSH was >88% relative to a conventional GSH MEGA-PRESS acquisition, whereas, for Lac, the editing efficiency was >95% relative to a conventional Lac MEGA-PRESS acquisition. Simulations also showed that the editing efficiency of both methods was comparable with separate MEGA-PRESS acquisitions of the same metabolites. In addition, simulations and in vivo spectra showed that, at a TE of 140 ms, there was a partial overlap between creatine (Cr) and GSH peaks, and that N-acetyl aspartate/N-acetyl aspartyl glutamate (NAA/NAAG) were sufficiently resolved from GSH. In vivo measurements showed that both sMEGA and DEW edited GSH and Lac reliably with the same editing efficiency as conventional MEGA-PRESS acquisitions of the same metabolites, with measured GSH integrals of 2.23 ± 0.51, 2.31 ± 0.38, 2.38 ± 0.53 and measured Lac integrals of 1.72 ± 0.67, 1.55 ± 0.35 and 1.53 ± 0.54 for MEGA-PRESS, DEW and sMEGA, respectively. Simultaneous detection of GSH and Lac using sMEGA and DEW is possible at 3 T with high editing efficiency.

Big GABA: Edited MR spectroscopy at 24 research sites.

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.

Simultaneous measurement of Aspartate, NAA, and NAAG using HERMES spectral editing at 3 Tesla.

It has previously been shown that the HERMES method ('Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy') can be used to simultaneously edit pairs of metabolites (such as N-acetyl-aspartate (NAA) and N-acetyl aspartyl glutamate (NAAG), or glutathione and GABA). In this study, HERMES is extended for the simultaneous editing of three overlapping signals, and illustrated for the example of NAA, NAAG and Aspartate (Asp). Density-matrix simulations were performed in order to optimize the HERMES sequence. The method was tested in NAA and Asp phantoms, and applied to the centrum semiovale of the nine healthy control subjects that were scanned at 3T. Both simulations and phantom experiments showed similar metabolite multiplet patterns with good segregation of all three metabolites. In vivo measurements show consistent relative signal intensities and multiplet patterns with concentrations in agreement with literature values. Simulations indicate co-editing of glutathione, glutamine, and glutamate, but their signals do not significantly overlap with the detected aspartyl resonances. This study demonstrates that a four-step Hadamard-encoded editing scheme can be used to simultaneously edit three otherwise overlapping metabolites, and can measure NAA, NAAG, and Asp in vivo in the brain at 3T with minimal crosstalk.

Spatial Hadamard encoding of J-edited spectroscopy using slice-selective editing pulses.

A new approach for simultaneous dual-voxel J-difference spectral editing is described, which uses spatially selective spectral-editing pulses and Hadamard encoding. A theoretical framework for spatial Hadamard editing and reconstruction for parallel acquisition (SHERPA) was developed, applying gradient pulses during the frequency-selective editing pulses. Spectral simulations were performed for either one (gamma-aminobutyric acid, GABA) or two molecules (glutathione and lactate) simultaneously detected in two voxels. The method was tested in a two-compartment GABA phantom, and finally applied to the left and right hemispheres of 10 normal control subjects, scanned at 3 T. SHERPA was successfully implemented at 3 T and gave results in close agreement with conventional MEGA-PRESS scans in both the phantom and in vivo experiments. Simulations for GABA editing for (3 cm)3 voxels in the left and right hemispheres suggest that both editing efficiency losses and contamination between voxels are about 2%. Compared with conventional single-voxel single-metabolite J-difference editing, two- or fourfold acceleration is possible without significant loss of SNR using the SHERPA method. Unlike some other dual-voxel methods, the method can be used with single-channel receiver coils, and there is no SNR loss due to unfavorable receive-coil geometry factors.