1. Big GABA II
- Author
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Alayar Kangarlu, Jacobus F.A. Jansen, Feng Liu, Helge J. Zöllner, Koen Cuypers, David Yen Ting Chen, Muhammad G. Saleh, Sean Noah, Scott O. Murray, David A. Edmondson, Ralph Noeske, Adam J. Woods, Georg Oeltzschner, Fei Gao, Lars Ersland, Richard A.E. Edden, Ian Greenhouse, Peter B. Barker, Mark Mikkelsen, Joanna R. Long, Chien-Yuan E. Lin, Thomas Lange, Naying He, Yan Li, Peter Truong, Ruoyun Ma, Nicolaas A.J. Puts, Niall W. Duncan, Michael Dacko, R. Marc Lebel, Hans-Jörg Wittsack, Guangbin Wang, Kimberly L. Chan, Celine Maes, Martin Tegenthoff, Pallab K. Bhattacharyya, Kim M. Cecil, Diederick Stoffers, Jy-Kang Liou, Gabriele Ende, Michael D. Noseworthy, Pieter F. Buur, Jiing-Feng Lirng, Alexander R. Craven, Stephan P. Swinnen, Michael-Paul Schallmo, Megan A. Forbes, Marta Moreno-Ortega, Stefanie Heba, Chencheng Zhang, James J. Prisciandaro, Iain D. Wilkinson, Markus Sack, Vadim Zipunnikov, Eric C. Porges, Timothy P.L. Roberts, Ulrike Dydak, Tun-Wei Hsu, Nicholas Simard, Ashley D. Harris, Daniel L. Rimbault, Fuhua Yan, Maiken K. Brix, Napapon Sailasuta, Nigel Hoggard, Hongmin Xu, Signal Processing Systems, MUMC+: DA BV Klinisch Fysicus (9), RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, Beeldvorming, Spinoza Centre for Neuroimaging, and Netherlands Institute for Neuroscience (NIN)
- Subjects
Male ,In vivo magnetic resonance spectroscopy ,Magnetic Resonance Spectroscopy ,Metabolite ,Datasets as Topic ,computer.software_genre ,TISSUE SEGMENTATION ,chemistry.chemical_compound ,GABA ,0302 clinical medicine ,Nuclear magnetic resonance ,Reference Values ,Voxel ,gamma-Aminobutyric Acid ,Chemistry ,05 social sciences ,Brain ,MAGNETIC-RESONANCE-SPECTROSCOPY ,H-1 MRS ,ALZHEIMERS-DISEASE ,medicine.anatomical_structure ,Neurology ,BRAIN IN-VIVO ,Female ,RELAXATION-TIMES ,METABOLITE CONCENTRATIONS ,medicine.drug ,Adult ,MRS ,Adolescent ,Volume of interest ,Cognitive Neuroscience ,Coefficient of variation ,POSTERIOR CINGULATE CORTEX ,Editing ,Article ,050105 experimental psychology ,gamma-Aminobutyric acid ,White matter ,Young Adult ,03 medical and health sciences ,Tissue correction ,MEGA-PRESS ,Quantification ,medicine ,Humans ,0501 psychology and cognitive sciences ,ABSOLUTE QUANTITATION ,GAMMA-AMINOBUTYRIC-ACID ,Water ,Exploratory analysis ,nervous system ,computer ,030217 neurology & neurosurgery - 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 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. ispartof: NEUROIMAGE vol:191 pages:537-548 ispartof: location:United States status: published
- Published
- 2019