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dc.contributor.authorMikkelsen, Mark
dc.contributor.authorRimbault, Daniel L.
dc.contributor.authorBarker, Peter B.
dc.contributor.authorBhattacharyya, Pallab K.
dc.contributor.authorBrix, Maiken Kirkegaard
dc.contributor.authorBuur, Pieter F.
dc.contributor.authorCecil, Kim M.
dc.contributor.authorChan, Kimberly L.
dc.contributor.authorChen, David Y.-T.
dc.contributor.authorCraven, Alexander R.
dc.contributor.authorCuypers, Koen
dc.contributor.authorDacko, Michael
dc.contributor.authorDuncan, Niall W.
dc.contributor.authorDydak, Ulrike
dc.contributor.authorEdmondson, David A.
dc.contributor.authorEnde, Gabriele
dc.contributor.authorErsland, Lars
dc.contributor.authorForbes, Megan A.
dc.contributor.authorGao, Fei
dc.contributor.authorGreenhouse, Ian
dc.contributor.authorHarris, Ashley D.
dc.contributor.authorHe, Naying
dc.contributor.authorHeba, Stefanie
dc.contributor.authorHoggard, Nigel
dc.contributor.authorHsu, Tun-Wei
dc.contributor.authorJansen, Jacobus F.A.
dc.contributor.authorKangarlu, Alayar
dc.contributor.authorLange, Thomas
dc.contributor.authorLebel, R. Marc
dc.contributor.authorLi, Yan
dc.contributor.authorLin, Chien-Yuan E.
dc.contributor.authorLiou, Jy-Kang
dc.contributor.authorLirng, Jiing-Feng
dc.contributor.authorLiu, Feng
dc.contributor.authorLong, Joanna R.
dc.contributor.authorMa, Ruoyun
dc.contributor.authorMaes, Celine
dc.contributor.authorMoreno-Ortega, Marta
dc.contributor.authorMurray, Scott O.
dc.contributor.authorNoah, Sean
dc.contributor.authorNoeske, Ralph
dc.contributor.authorNoseworthy, Michael D.
dc.contributor.authorOeltzschner, Georg
dc.contributor.authorPorges, Eric C.
dc.contributor.authorPrisciandaro, James J.
dc.contributor.authorPuts, Nicolaas A.J.
dc.contributor.authorRoberts, Timothy P.L.
dc.contributor.authorSack, Markus
dc.contributor.authorSailasuta, Napapon
dc.contributor.authorSaleh, Muhammad G.
dc.contributor.authorSchallmo, Michael-Paul
dc.contributor.authorSimard, Nicholas
dc.contributor.authorStoffers, Diederick
dc.contributor.authorSwinnen, Stephan P.
dc.contributor.authorTegenthoff, Martin
dc.contributor.authorTruong, Peter
dc.contributor.authorWang, Guangbin
dc.contributor.authorWilkinson, Iain D.
dc.contributor.authorWittsack, Hans-Jörg
dc.contributor.authorWoods, Adam J.
dc.contributor.authorXu, Hongmin
dc.contributor.authorYan, Fuhua
dc.contributor.authorZhang, Chencheng
dc.contributor.authorZipunnikov, Vadim
dc.contributor.authorZöllner, Helge J.
dc.contributor.authorEdden, Richard A.E.
dc.PublishedMikkelsen M, Rimbault, Barker, Bhattacharyya, Brix MK, Buur, Cecil, et al. Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites. NeuroImage. 2019;191:537-548eng
dc.description.abstractAccurate 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.en_US
dc.rightsAttribution-NonCommercial-NoDerivs CC BY-NC-ND
dc.titleBig GABA II: Water-referenced edited MR spectroscopy at 25 research siteseng
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright 2019 Elsevier Inc.eng

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