Quantification of γ-aminobutyric acid (GABA) in 1 H MRS volumes composed heterogeneously of grey and white matter

Prefrontal metabolite alterations in individuals with posttraumatic stress disorder: a 7T magnetic resonance spectroscopy study

Background

Evidence from animal and human studies suggests glutamatergic dysfunction in posttraumatic stress disorder (PTSD). The purpose of this study was to investigate glutamate abnormalities in the dorsolateral prefrontal cortex (DLFPC) of individuals with PTSD using 7T MRS, which has better spectral resolution and signal-to-noise ratio than lower field strengths, thus allowing for better spectral quality and higher sensitivity. We hypothesized that individuals with PTSD would have lower glutamate levels compared to trauma-exposed individuals without PTSD and individuals without trauma exposure. Additionally, we explored potential alterations in other neurometabolites and the relationship between glutamate and psychiatric symptoms.

Methods

Individuals with PTSD (n=27), trauma-exposed individuals without PTSD (n=27), and individuals without trauma exposure (n=26) underwent 7T MRS to measure glutamate and other neurometabolites in the left DLPFC. The severities of PTSD, depression, anxiety, and dissociation symptoms were assessed.

Results

We found that glutamate was lower in the PTSD and trauma-exposed groups compared to the group without trauma exposure. Furthermore, N-acetylaspartate (NAA) was lower and lactate was higher in the PTSD group compared to the group without trauma exposure. Glutamate was negatively correlated with depression symptom severity in the PTSD group. Glutamate was not correlated with PTSD symptom severity.

Conclusion

In this first 7T MRS study of PTSD, we observed altered concentrations of glutamate, NAA, and lactate. Our findings provide evidence for multiple possible pathological processes in individuals with PTSD. High-field MRS offers insight into the neurometabolic alterations associated with PTSD and is a powerful tool to probe trauma- and stress-related neurotransmission and metabolism in vivo.

Neural correlates of transfer of learning in motor coordination tasks: role of inhibitory and excitatory neurometabolites

We aimed to investigate transfer of learning, whereby previously acquired skills impact new task learning. While it has been debated whether such transfer may yield positive, negative, or no effects on performance, very little is known about the underlying neural mechanisms, especially concerning the role of inhibitory (GABA) and excitatory (Glu) (measured as Glu + glutamine (Glx)) neurometabolites, as measured by magnetic resonance spectroscopy (MRS). Participants practiced a bimanual coordination task across four days. The Experimental group trained a task variant with the right hand moving faster than the left (Task A) for three days and then switched to the opposite variant (Task B) on Day4. The control group trained Task B across four days. MRS data were collected before, during, and after task performance on Day4 in the somatosensory (S1) and visual (MT/V5) cortex. Results showed that both groups improved performance consistently across three days. On Day4, the Experimental group experienced performance decline due to negative task transfer while the control group continuously improved. GABA and Glx concentrations obtained during task performance showed no significant group-level changes. However, individual Glx levels during task performance correlated with better (less negative) transfer performance. These findings provide a first window into the neurochemical mechanisms underlying task transfer.

Neuroimaging Insights: Kava's (Piper methysticum) Effect on Dorsal Anterior Cingulate Cortex GABA in Generalized Anxiety Disorder

Generalised Anxiety Disorder (GAD) is a prevalent, chronic mental health disorder. The measurement of regional brain gamma-aminobutyric acid (GABA) offers insight into its role in anxiety and is a potential biomarker for treatment response. Research literature suggests Piper methysticum (Kava) is efficacious as an anxiety treatment, but no study has assessed its effects on central GABA levels. This study investigated dorsal anterior cingulate (dACC) GABA levels in 37 adult participants with GAD. GABA was measured using proton magnetic resonance spectroscopy (1H-MRS) at baseline and following an eight-week administration of Kava (standardised to 120 mg kavalactones twice daily) (n = 20) or placebo (n = 17). This study was part of the Kava for the Treatment of GAD (KGAD; ClinicalTrials.gov: NCT02219880), a 16-week intervention study. Compared with the placebo group, the Kava group had a significant reduction in dACC GABA (p = 0.049) at eight weeks. Baseline anxiety scores on the HAM-A were positively correlated with GABA levels but were not significantly related to treatment. Central GABA reductions following Kava treatment may signal an inhibitory effect, which, if considered efficacious, suggests that GABA levels are modulated by Kava, independent of reported anxiety symptoms. dACC GABA patterns suggest a functional role of higher levels in clinical anxiety but warrants further research for symptom benefit. Findings suggest that dACC GABA levels previously un-examined in GAD could serve as a biomarker for diagnosis and treatment response.

Protocol to conduct functional magnetic resonance spectroscopy in different age groups of human participants

We present a protocol to conduct functional magnetic resonance spectroscopy (fMRS) in human participants before, during, and after training on a visual task. We describe steps for participant setup, volume-of-interest placement, fMRS measurement, and post-scan tests. We discuss the design, analysis, and interpretation of fMRS experiments. This protocol can be adapted to investigate the dynamics of chief excitatory and inhibitory neurotransmitters (glutamate and γ-aminobutyric acid, GABA, respectively) while participants perform or learn perceptual, motor, or cognitive tasks. For complete details on the use and execution of this protocol, please refer to Frank et al. (2022).1.

Quantification of the neurochemical profile of the human putamen using STEAM MRS in a cohort of elderly subjects at 3 T and 7 T: Ruminations on the correction strategy for the tissue voxel composition

The aim of this work is to quantify the metabolic profile of the human putamen in vivo in a cohort of elderly subjects using single-voxel proton magnetic resonance spectroscopy. To obtain metabolite concentrations specific to the putamen, we investigated a correction method previously proposed to account for the tissue composition of the volume of interest. We compared the method with the conventional approach, which a priori assumes equal metabolite concentrations in GM and WM. Finally, we compared the concentrations acquired at 3 Tesla (T) and 7 T MRI scanners. Spectra were acquired from 15 subjects (age: 67.7 ± 8.3 years) at 3 T and 7 T, using an ultra-short echo time, stimulated echo acquisition mode sequence. To robustly estimate the WM-to-GM metabolite concentration ratio, five additional subjects were measured for whom the MRS voxel was deliberately shifted from the putamen in order to increase the covered amount of surrounding WM. The concentration and WM-to-GM concentration ratio for 16 metabolites were reliably estimated. These ratios ranged from ~0.3 for γ-aminobutyric acid to ~4 for N-acetylaspartylglutamate. The investigated correction method led to significant changes in concentrations compared to the conventional method, provided that the ratio significantly differed from unity. Finally, we demonstrated that differences in tissue voxel composition cannot fully account for the observed concentration difference between field strengths. We provide not only a fully comprehensive quantification of the neurochemical profile of the putamen in elderly subjects, but also a quantification of the WM-to-GM concentration ratio. This knowledge may serve as a basis for future studies with varying tissue voxel composition, either due to tissue atrophy, inconsistent voxel positioning or simply when pooling data from different voxel locations.

A comprehensive guide to MEGA-PRESS for GABA measurement

The aim of this guideline is to provide a series of evidence-based recommendations that allow those new to using MEGA-PRESS to produce high-quality data for the measurement of GABA levels using edited magnetic resonance spectroscopy with the MEGA-PRESS sequence at 3T. GABA is the main inhibitory neurotransmitter of the central nervous system and has been increasingly studied due to its relevance in many clinical disorders of the central nervous system. MEGA-PRESS is the most widely used method for quantification of GABA at 3T, but is technically challenging and operates at a low signal-to-noise ratio. Therefore, the acquisition of high-quality MRS data relies on avoiding numerous pitfalls and observing important caveats. The guideline was developed by a working party that consisted of experts in MRS and experts in guideline development and implementation, together with key stakeholders. Strictly following a translational framework, we first identified evidence using a systematically conducted scoping literature review, then synthesized and graded the quality of evidence that formed recommendations. These recommendations were then sent to a panel of 21 world leaders in MRS for feedback and approval using a modified-Delphi process across two rounds. The final guideline consists of 23 recommendations across six domains essential for GABA MRS acquisition (Parameters, Practicalities, Data acquisition, Confounders, Quality/reporting, Post-processing). Overall, 78% of recommendations were formed from high-quality evidence, and 91% received agreement from over 80% of the expert panel. These 23 expert-reviewed recommendations and accompanying extended documentation form a readily useable guideline to allow those new to using MEGA-PRESS to design appropriate MEGA-PRESS study protocols and generate high-quality data.

Evaluating Back-to-Back and Day-to-Day Reproducibility of Cortical GABA+ Measurements Using Proton Magnetic Resonance Spectroscopy (1H MRS)

γ-aminobutyric acid (GABA) is a major inhibitory neurotransmitter implicated in neuropsychiatric disorders. The best method for quantifying GABA is proton magnetic resonance spectroscopy (¹H MRS). Considering that accurate measurements of GABA are affected by slight methodological alterations, demonstrating GABA reproducibility in healthy volunteers is essential before implementing the changes in vivo. Thus, our study aimed to evaluate the back-to-back (B2B) and day-to-day (D2D) reproducibility of GABA+ macromolecules (GABA+) using a 3 Tesla MRI scanner, the new 32-channel head coil (CHC), and Mescher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) technique with the scan time (approximately 10 min), adequate for psychiatric patients. The dorsomedial pre-frontal cortex/anterior cingulate cortex (dmPFC/ACC) was scanned in 29 and the dorsolateral pre-frontal cortex (dlPFC) in 28 healthy volunteers on two separate days. Gannet 3.1 was used to quantify GABA+. The reproducibility was evaluated by Pearson's r correlation, the interclass-correlation coefficient (ICC), and the coefficient of variation (CV%) (r/ICC/CV%). For Day 1, B2B reproducibility was 0.59/0.60/5.02% in the dmPFC/ACC and 0.74/0.73/5.15% for dlPFC. For Day 2, it was 0.60/0.59/6.26% for the dmPFC/ACC and 0.54/0.54/6.89 for dlPFC. D2D reproducibility of averaged GABA+ was 0.62/0.61/4.95% for the dmPFC/ACC and 0.58/0.58/5.85% for dlPFC. Our study found excellent GABA+ repeatability and reliability in the dmPFC/ACC and dlPFC.

Insights from auditory cortex for GABA+ magnetic resonance spectroscopy studies of aging

Changes in levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) may underlie aging-related changes in brain function. GABA and co-edited macromolecules (GABA+) can be measured with MEGA-PRESS magnetic resonance spectroscopy (MRS). The current study investigated how changes in the aging brain impact the interpretation of GABA+ measures in bilateral auditory cortices of healthy young and older adults. Structural changes during aging appeared as decreasing proportion of grey matter in the MRS volume of interest and corresponding increase in cerebrospinal fluid. GABA+ referenced to H₂ O without tissue correction declined in aging. This decline persisted after correcting for tissue differences in MR-visible H₂ O and relaxation times but vanished after considering the different abundance of GABA+ in grey and white matter. However, GABA+ referenced to creatine and N-acetyl aspartate (NAA), which showed no dependence on tissue composition, decreased in aging. All GABA+ measures showed hemispheric asymmetry in young but not older adults. The study also considered aging-related effects on tissue segmentation and the impact of co-edited macromolecules. Tissue segmentation differed significantly between commonly used algorithms, but aging-related effects on tissue-corrected GABA+ were consistent across methods. Auditory cortex macromolecule concentration did not change with age, indicating that a decline in GABA caused the decrease in the compound GABA+ measure. Most likely, the macromolecule contribution to GABA+ leads to underestimating an aging-related decrease in GABA. Overall, considering multiple GABA+ measures using different reference signals strengthened the support for an aging-related decline in auditory cortex GABA levels.

Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

The role of MRS-assessed GABA in human behavioral performance

Understanding the neurophysiological mechanisms that drive human behavior has been a long-standing focus of cognitive neuroscience. One well-known neuro-metabolite involved in the creation of optimal behavioral repertoires is GABA, the main inhibitory neurochemical in the human brain. Converging evidence from both animal and human studies indicates that individual variations in GABAergic function are associated with behavioral performance. In humans, one increasingly used in vivo approach to measuring GABA levels is through Magnetic Resonance Spectroscopy (MRS). However, the implications of MRS measures of GABA for behavior remain poorly understood. In this respect, it is yet to be determined how GABA levels within distinct task-related brain regions of interest account for differences in behavioral performance. This review summarizes findings from cross-sectional studies that determined baseline MRS-assessed GABA levels and examined their associations with performance on various behaviors representing the perceptual, motor and cognitive domains, with a particular focus on healthy participants across the lifespan. Overall, the results indicate that MRS-assessed GABA levels play a pivotal role in various domains of behavior. Even though some converging patterns emerge, it is challenging to draw comprehensive conclusions due to differences in behavioral task paradigms, targeted brain regions of interest, implemented MRS techniques and reference compounds used. Across all studies, the effects of GABA levels on behavioral performance point to generic and partially independent functions that refer to distinctiveness, interference suppression and cognitive flexibility. On one hand, higher baseline GABA levels may support the distinctiveness of neural representations during task performance and better coping with interference and suppression of preferred response tendencies. On the other hand, lower baseline GABA levels may support a reduction of inhibition, leading to higher cognitive flexibility. These effects are task-dependent and appear to be mediated by age. Nonetheless, additional studies using emerging advanced methods are required to further clarify the role of MRS-assessed GABA in behavioral performance.

The Relationship Between Resting Cerebral Blood Flow, Neurometabolites, Cardio-Respiratory Fitness and Aging-Related Cognitive Decline

Older adults typically experience a decline in cognitive function, but improvements in physical health and lifestyle can be neuroprotective across the human lifespan. The primary objective of this study is to advance our basic understanding of how cardiorespiratory fitness and neurophysiological attributes relate to cognitive decline. While cerebral blood flow (CBF) is critical for the supply of nutrients to the tissue, the brain's major neurotransmitters (i.e., gamma-aminobutyric acid, GABA, and glutamate-glutamine complex, Glx) are closely linked to oxidative metabolism. Within the context of flow-metabolism coupling, the critical question is how these neurophysiological parameters interplay, resulting in cognitive decline. Further, how cardiorespiratory fitness may impact aging neurophysiology and cognition is not well understood. To address these questions, we recruited 10 younger and 12 older cognitively intact participants to collect GABA and Glx using magnetic resonance spectroscopy (MRS), CBF using pseudo-continuous arterial spin labeling Magnetic Resonance Imaging (MRI), VO2max as a measure of cardiorespiratory fitness using the YMCA submax test, and cognitive and motor-cognitive measures using a battery of behavioral assessments. We observed expected differences in GABA+, Glx, and CBF between younger and older participants in pre-SMA, a frontal domain-general region. When GABA+ and Glx were related to CBF via multiple linear regression, Glx was identified as the main contributor to the model. For higher-order executive function (i.e., inhibition versus color naming), GABA*Glx*CBF interaction was critical in younger, while only Glx was involved in older participants. For unimanual motor dexterity, GABA*Glx interaction was the common denominator across both groups, but younger participants' brain also engages CBF. In terms of selective motor inhibition, CBF from younger participants was the only major neurophysiological factor. In terms of fitness, cardiorespiratory fitness was significantly related to GABA, Glx, and motor performance when combining cohorts, but no group-specific relationships were observed. Taken together, our results indicate that Glx and CBF coupling decreases with aging, perhaps due to altered glial oxidative metabolism. Our data suggest that GABA, Glx, and CBF are engaged and weighted differently for different cognitive measures sensitized to aging, and higher fitness allows for a more efficient metabolic shift that facilitates improved performance on cognitive-motor tasks.

Neurophysiological modulations in the (pre)motor-motor network underlying age-related increases in reaction time and the role of GABA levels - a bimodal TMS-MRS study

It has been argued that age-related changes in the neurochemical and neurophysiological properties of the GABAergic system may underlie increases in reaction time (RT) in older adults. However, the role of GABA levels within the sensorimotor cortices (SMC) in mediating interhemispheric interactions (IHi) during the processing stage of a fast motor response, as well as how both properties explain interindividual differences in RT, are not yet fully understood. In this study, edited magnetic resonance spectroscopy (MRS) was combined with dual-site transcranial magnetic stimulation (dsTMS) for probing GABA+ levels in bilateral SMC and task-related neurophysiological modulations in corticospinal excitability (CSE), and primary motor cortex (M1)-M1 and dorsal premotor cortex (PMd)-M1 IHi, respectively. Both CSE and IHi were assessed during the preparatory and premotor period of a delayed choice RT task. Data were collected from 25 young (aged 18-33 years) and 28 older (aged 60-74 years) healthy adults. Our results demonstrated that older as compared to younger adults exhibited a reduced bilateral CSE suppression, as well as a reduced magnitude of long latency M1-M1 and PMd-M1 disinhibition during the preparatory period, irrespective of the direction of the IHi. Importantly, in older adults, the GABA+ levels in bilateral SMC partially accounted for task-related neurophysiological modulations as well as individual differences in RT. In contrast, in young adults, neither task-related neurophysiological modulations, nor individual differences in RT were associated with SMC GABA+ levels. In conclusion, this study contributes to a comprehensive initial understanding of how age-related differences in neurochemical properties and neurophysiological processes are related to increases in RT.

Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data

Many methods exist for aligning and quantifying magnetic resonance spectroscopy (MRS) data to measure in vivo γ-aminobutyric acid (GABA). Research comparing the performance of these methods is scarce partly due to the lack of ground-truth measurements. The concentration of GABA is approximately two times higher in grey matter than in white matter. Here we use the proportion of grey matter within the MRS voxel as a proxy for ground-truth GABA concentration to compare the performance of four spectral alignment methods (i.e., retrospective frequency and phase drift correction) and six GABA signal modelling methods. We analyse a diverse dataset of 432 MEGA-PRESS scans targeting multiple brain regions and find that alignment to the creatine (Cr) signal produces GABA+ estimates that account for approximately twice as much of the variance in grey matter as the next best performing alignment method. Further, Cr alignment was the most robust, producing the fewest outliers. By contrast, all signal modelling methods, except for the single-Lorentzian model, performed similarly well. Our results suggest that variability in performance is primarily caused by differences in the zero-order phase estimated by each alignment method, rather than frequency, resulting from first-order phase offsets within subspectra. These results provide support for Cr alignment as the optimal method of processing MEGA-PRESS to quantify GABA. However, more broadly, they demonstrate a method of benchmarking quantification of in vivo metabolite concentration from other MRS sequences.

Regional balance between glutamate+glutamine and GABA+ in the resting human brain

Models of healthy brain function and psychiatric conditions assume that excitatory and inhibitory activity are balanced in the human brain at multiple spatial and temporal scales. In human neuroimaging, concentrations of the major excitatory (glutamate) and inhibitory (γ-aminobutyric acid, GABA) neurotransmitters are measured in vivo using magnetic resonance spectroscopy (MRS). However, despite the central importance of E/I balance to theories of brain function, a relationship between regional glutamate and GABA levels in the human brain has not been shown. We addressed this question in a large corpus of edited MRS data collected at 19 different sites (n = 220). Consistent with the notion of E/I balance, we found that levels of glutamate+glutamine (Glx) and GABA+ were highly correlated (R = 0.52, p = 2.86 x 10⁻¹⁴). This relationship held when controlling for site, scanner vendor, and demographics. Controlling for neurochemicals associated with neuronal density and metabolism (i.e. N-acetylaspartate and creatine) significantly reduced the correlation between GABA+ and Glx, suggesting that the levels of GABA+ and Glx may be critically linked to regional metabolism. These results are consistent with the notion that excitation and inhibition are balanced in the human brain.

Transcranial magnetic stimulation and magnetic resonance spectroscopy: Opportunities for a bimodal approach in human neuroscience

Over the last decade, there has been an increasing number of studies combining transcranial magnetic stimulation (TMS) and magnetic resonance spectroscopy (MRS). MRS provides a manner to non-invasively investigate molecular concentrations in the living brain and thus identify metabolites involved in physiological and pathological processes. Particularly the MRS-detectable metabolites glutamate, the major excitatory neurotransmitter, and gamma-aminobutyric acid (GABA), the major inhibitory neurotransmitter, are of interest when combining TMS and MRS. TMS is a non-invasive brain stimulation technique that can be applied either as a neuromodulation or neurostimulation tool, specifically targeting glutamatergic and GABAergic mechanisms. The combination of TMS and MRS can be used to evaluate alterations in brain metabolite levels following an interventional TMS protocol such as repetitive TMS (rTMS) or paired associative stimulation (PAS). MRS can also be combined with a variety of non-interventional TMS protocols to identify the interplay between brain metabolite levels and measures of excitability or receptor-mediated inhibition and facilitation. In this review, we provide an overview of studies performed in healthy and patient populations combining MRS and TMS, both as a measurement tool and as an intervention. TMS and MRS may reveal complementary and comprehensive information on glutamatergic and GABAergic neurotransmission. Potentially, connectivity changes and dedicated network interactions can be probed using the combined TMS-MRS approach. Considering the ongoing technical developments in both fields, combined studies hold future promise for investigations of brain network interactions and neurotransmission.

A comparison of sLASER and MEGA-sLASER using simultaneous interleaved acquisition for measuring GABA in the human brain at 7T

γ-Aminobutyric acid (GABA), the major inhibitory neurotransmitter, is challenging to measure using proton spectroscopy due to its relatively low concentration, J-coupling and overlapping signals from other metabolites. Currently, the prevalent methods for detecting GABA at ultrahigh field strengths (≥ 7 T) are GABA-editing and model fitting of non-editing single voxel spectra. These two acquisition approaches have their own advantages: the GABA editing approach directly measures the GABA resonance at 3 ppm, whereas the fitting approach on the non-editing spectrum allows the detection of multiple metabolites, and has an SNR advantage over longer echo time (TE) acquisitions. This study aims to compare these approaches for estimating GABA at 7 T. We use an interleaved sequence of semi-LASER (sLASER: TE = 38 ms) and MEGA-sLASER (TE = 80 ms). This simultaneous interleaved acquisition minimizes the differential effect of extraneous factors, and enables an accurate comparison of the two acquisition methods. Spectra were acquired with an 8 ml isotropic voxel at six different brain regions: anterior-cingulate cortex, dorsolateral-prefrontal cortex, motor cortex, occipital cortex, posterior cingulate cortex, and precuneus. Spectral fitting with LCModel quantified the GABA to total Cr (tCr: Creatine + Phosphocreatine) concentration ratio. After correcting the T2 relaxation time variation, GABA/tCr ratios were similar between the two acquisition approaches. GABA editing showed smaller spectral fitting error according to Cramér-Rao lower bound than the sLASER approach for all regions examined. We conclude that both acquisition methods show similar accuracy but the precision of the MEGA-editing approach is higher for GABA measurement. In addition, the 2.28 ppm GABA resonance was found to be important for estimating GABA concentration without macromolecule contamination in the GABA-edited acquisition, when utilizing spectral fitting with LCModel.

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.

Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer

Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data. Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T₁-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions. Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes. Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias.

Age-related differences in GABA levels are driven by bulk tissue changes

Levels of GABA, the main inhibitory neurotransmitter in the brain, can be regionally quantified using magnetic resonance spectroscopy (MRS). Although GABA is crucial for efficient neuronal functioning, little is known about age-related differences in GABA levels and their relationship with age-related changes in brain structure. Here, we investigated the effect of age on GABA levels within the left sensorimotor cortex and the occipital cortex in a sample of 85 young and 85 older adults using the MEGA-PRESS sequence. Because the distribution of GABA varies across different brain tissues, various correction methods are available to account for this variation. Considering that these correction methods are highly dependent on the tissue composition of the voxel of interest, we examined differences in voxel composition between age groups and the impact of these various correction methods on the identification of age-related differences in GABA levels. Results indicated that, within both voxels of interest, older (as compared to young adults) exhibited smaller gray matter fraction accompanied by larger fraction of cerebrospinal fluid. Whereas uncorrected GABA levels were significantly lower in older as compared to young adults, this age effect was absent when GABA levels were corrected for voxel composition. These results suggest that age-related differences in GABA levels are at least partly driven by the age-related gray matter loss. However, as alterations in GABA levels might be region-specific, further research should clarify to what extent gray matter changes may account for age-related differences in GABA levels within other brain regions.

Randomised controlled trial of simvastatin treatment for autism in young children with neurofibromatosis type 1 (SANTA)

Background

Neurofibromatosis 1 (NF1) is a monogenic model for syndromic autism. Statins rescue the social and cognitive phenotype in animal knockout models, but translational trials with subjects > 8 years using cognition/behaviour outcomes have shown mixed results. This trial breaks new ground by studying statin effects for the first time in younger children with NF1 and co-morbid autism and by using multiparametric imaging outcomes.

Methods

A single-site triple-blind RCT of simvastatin vs. placebo was done. Assessment (baseline and 12-week endpoint) included peripheral MAPK assay, awake magnetic resonance imaging spectroscopy (MRS; GABA and glutamate+glutamine (Glx)), arterial spin labelling (ASL), apparent diffusion coefficient (ADC), resting state functional MRI, and autism behavioural outcomes (Aberrant Behaviour Checklist and Clinical Global Impression).

Results

Thirty subjects had a mean age of 8.1 years (SD 1.8). Simvastatin was well tolerated. The amount of imaging data varied by test. Simvastatin treatment was associated with (i) increased frontal white matter MRS GABA (t(12) = - 2.12, p = .055), GABA/Glx ratio (t(12) = - 2.78, p = .016), and reduced grey nuclei Glx (ANCOVA p < 0.05, Mann-Whitney p < 0.01); (ii) increased ASL perfusion in ventral diencephalon (Mann-Whitney p < 0.01); and (iii) decreased ADC in cingulate gyrus (Mann-Whitney p < 0.01). Machine-learning classification of imaging outcomes achieved 79% (p < .05) accuracy differentiating groups at endpoint against chance level (64%, p = 0.25) at baseline. Three of 12 (25%) simvastatin cases compared to none in placebo met 'clinical responder' criteria for behavioural outcome.

Conclusions

We show feasibility of peripheral MAPK assay and autism symptom measurement, but the study was not powered to test effectiveness. Multiparametric imaging suggests possible simvastatin effects in brain areas previously associated with NF1 pathophysiology and the social brain network.

Trial registration

EU Clinical Trial Register (EudraCT) 2012-005742-38 (www.clinicaltrialsregister.eu).

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.