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.

Accurate and reliable quantification of brain metabolites measured in vivo using 1 H magnetic resonance spectroscopy (MRS) is a topic of continued interest in the field. 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, we analyze spectrally edited -aminobutyric acid (GABA) MRS data and quantify GABA levels relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using standard GABA+ editing. Unsuppressed water acquisitions from the same volume of interest were acquired for signal referencing. Whole-brain T1-weighted structural images were acquired and tissue-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%, which was largely driven by vendor-related differences according to a linear mixed-effects analysis. The mean within-site coefficient of variation was 9%. Vendor differences contributed 53% to the total variance in the data, while the remaining variance was attributed to site-(11%) and participant-level (36%) effects. Results from an exploratory analysis suggested that the vendor differences were related to the water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA+ measurements exhibit levels of variance similar to creatine-referenced GABA+ measurements. It is concluded that quantification using internal tissue water referencing remains a viable and reliable method for the in vivo quantification of GABA+ levels.

Over the last decade, the brain's default‐mode network (DMN) and its function has attracted a lot of attention in the field of neuroscience. However, the exact underlying mechanisms of DMN functional connectivity, or more specifically, the blood‐oxygen level‐dependent (BOLD) signal, are still incompletely understood. In the present study, we combined 2‐deoxy‐2‐[18F]fluoroglucose positron emission tomography (FDG‐PET), proton magnetic resonance spectroscopy (1H‐MRS), and resting‐state functional magnetic resonance imaging (rs‐fMRI) to investigate more directly the association between local glucose consumption, local glutamatergic neurotransmission and DMN functional connectivity during rest. The results of the correlation analyzes using the dorsal posterior cingulate cortex (dPCC) as seed region showed spatial similarities between fluctuations in FDG‐uptake and fluctuations in BOLD signal. More specifically, in both modalities the same DMN areas in the inferior parietal lobe, angular gyrus, precuneus, middle, and medial frontal gyrus were positively correlated with the dPCC. Furthermore, we could demonstrate that local glucose consumption in the medial frontal gyrus, PCC and left angular gyrus was associated with functional connectivity within the DMN. We did not, however, find a relationship between glutamatergic neurotransmission and functional connectivity. In line with very recent findings, our results lend further support for a close association between local metabolic activity and functional connectivity and provide further insights towards a better understanding of the underlying mechanism of the BOLD signal. Hum Brain Mapp 36:2027–2038, 2015. © 2015 Wiley Periodicals, Inc.

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Spectral editing allows direct measurement of low-concentration metabolites, such as GABA, glutathione (GSH) and lactate (Lac), relevant for understanding brain (patho)physiology. The most widely used spectral editing technique is MEGA-PRESS, which has been diversely implemented across research sites and vendors, resulting in variations in the final resolved edited signal. In this paper, we describe an effort to develop a new universal MEGA-PRESS sequence with HERMES functionality for the major MR vendor platforms with standardized RF pulse shapes, durations, amplitudes and timings. New RF pulses were generated for the universal sequence. Phantom experiments were conducted on Philips, Siemens, GE and Canon 3 T MRI scanners using 32-channel head coils. In vivo experiments were performed on the same six subjects on Philips and Siemens scanners, and on two additional subjects, one on GE and one on Canon scanners. On each platform, edited MRS experiments were conducted with the vendor-native and universal MEGA-PRESS sequences for GABA (TE ¼ 68 ms) and Lac editing (TE ¼ 140 ms). Additionally, HERMES for GABA and GSH was performed using the universal sequence at TE ¼ 80 ms. The universal sequence improves inter-vendor similarity of GABA-edited and Lac-edited MEGA-PRESS spectra. The universal HERMES sequence yields both GABA-and GSH-edited spectra with negligible levels of crosstalk on all four platforms, and with strong agreement among vendors for both edited spectra. In vivo GABAþ/Cr, Lac/Cr and GSH/Cr ratios showed relatively low variation between scanners using the universal sequence. In conclusion, phantom and in vivo experiments demonstrate successful implementation of the universal sequence across all four major vendors, allowing editing of several metabolites across a range of TEs.

Magnetic resonance spectroscopy (MRS) from voxels placed in the left anterior cingulate cortex (ACC) was measured from 14 boys with Autism Spectrum Disorder (ASD) and 24 gender and age-matched typically developing (TD) control group. Our main aims were to compare the concentration of γ-aminobutyric acid (GABA) between the two groups, and to investigate the relationship between brain metabolites and autism symptom severity in the ASD group. We did find a significant negative correlation in the ASD group between Autism Spectrum Screening Questionnaire (ASSQ) and GABA+/Cr, which may imply that severity of symptoms in ASD is associated with differences in the level of GABA in the brain, supporting the excitatory/inhibitory (E/I) imbalance theory. However we did not find a significant difference between the two groups in GABA levels.

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