Dataset Information

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

ABSTRACT: 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 ?-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.

SUBMITTER: Mikkelsen M

PROVIDER: S-EPMC6818968 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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

Mikkelsen Mark M Rimbault Daniel L DL Barker Peter B PB Bhattacharyya Pallab K PK Brix Maiken K MK Buur Pieter F PF Cecil Kim M KM Chan Kimberly L KL Chen David Y-T DY Craven Alexander R AR Cuypers Koen K Dacko Michael M Duncan Niall W NW Dydak Ulrike U Edmondson David A DA Ende Gabriele G Ersland Lars L Forbes Megan A MA Gao Fei F Greenhouse Ian I Harris Ashley D AD He Naying N Heba Stefanie S Hoggard Nigel N Hsu Tun-Wei TW Jansen Jacobus F A JFA Kangarlu Alayar A Lange Thomas T Lebel R Marc RM Li Yan Y Lin Chien-Yuan E CE Liou Jy-Kang JK Lirng Jiing-Feng JF Liu Feng F Liu Feng F Long Joanna R JR Ma Ruoyun R Maes Celine C Moreno-Ortega Marta M Murray Scott O SO Noah Sean S Noeske Ralph R Noseworthy Michael D MD Oeltzschner Georg G Porges Eric C EC Prisciandaro James J JJ Puts Nicolaas A J NAJ Roberts Timothy P L TPL Sack Markus M Sailasuta Napapon N Saleh Muhammad G MG Schallmo Michael-Paul MP Simard Nicholas N Stoffers Diederick D Swinnen Stephan P SP Tegenthoff Martin M Truong Peter P Wang Guangbin G Wilkinson Iain D ID Wittsack Hans-Jörg HJ Woods Adam J AJ Xu Hongmin H Yan Fuhua F Zhang Chencheng C Zipunnikov Vadim V Zöllner Helge J HJ Edden Richard A E RAE

NeuroImage 20190303

Accurate and reliable quantification of brain metabolites measured in vivo using <sup>1</sup>H 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 ...[more]

PMID: 30840905

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Project description: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.

Project description: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.

Dataset Information

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

Publications

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

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