Big GABA: Edited MR spectroscopy at 24 research sites

Mark Mikkelsen, Peter B. Barker, Pallab K. Bhattacharyya, Maiken K. Brix, Pieter F. Buur, Kim M. Cecil, Kimberly L. Chan, David Y.T. Chen, Alexander R. Craven, Koen Cuypers, Michael Dacko, Niall W. Duncan, Ulrike Dydak, David A. Edmondson, Gabriele Ende, Lars Ersland, Fei Gao, Ian Greenhouse, Ashley D. Harris, Naying HeStefanie Heba, Nigel Hoggard, Tun Wei Hsu, Jacobus F.A. Jansen, Alayar Kangarlu, Thomas Lange, R. Marc Lebel, Yan Li, Chien Yuan E. Lin, Jy Kang Liou, Jiing Feng Lirng, Feng Liu, Ruoyun Ma, Celine Maes, Marta Moreno-Ortega, Scott O. Murray, Sean Noah, Ralph Noeske, Michael D. Noseworthy, Georg Oeltzschner, James J. Prisciandaro, Nicolaas A.J. Puts, Timothy P.L. Roberts, Markus Sack, Napapon Sailasuta, Muhammad G. Saleh, Michael Paul Schallmo, Nicholas Simard, Stephan P. Swinnen, Martin Tegenthoff, Peter Truong, Guangbin Wang, Iain D. Wilkinson, Hans Jörg Wittsack, Hongmin Xu, Fuhua Yan, Chencheng Zhang, Vadim Zipunnikov, Helge J. Zöllner, Richard A.E. Edden

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)32-45
Number of pages14
StatePublished - Oct 1 2017

Bibliographical note

Funding Information:
This work was supported by NIH grants R01 EB016089, R01 EB023963 and P41 EB015909. Data collection was supported by the Shandong Provincial Key Research and Development Plan of China (2016ZDJS07A16) and the National Natural Science Foundation of China for Young Scholars (no. 81601479). IDW thanks Mrs. J. Bigley of the University of Sheffield MRI Unit for her assistance with data acquisition. JJP was supported by NIAAA grant K23 AA020842. MPS was supported by NIH grant F32 EY025121. NAJP receives salary support from NIH grant K99 MH107719. The authors acknowledge implementation contributions from a number of employees of Siemens Medical Solutions, including Dr. Keith Heberlein and Dr. Sinyeob Ahn, to the Siemens WIP sequences, which are shared with several research sites under sequence-specific agreements.

Publisher Copyright:
© 2017 Elsevier Inc.


  • Editing
  • GABA
  • MRS
  • Multi-site study


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