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

Mark Mikkelsen, Daniel L. Rimbault, 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, Megan A. Forbes, Fei Gao, Ian GreenhouseAshley D. Harris, Naying He, Stefanie 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, Joanna R. Long, Ruoyun Ma, Celine Maes, Marta Moreno-Ortega, Scott O. Murray, Sean Noah, Ralph Noeske, Michael D. Noseworthy, Georg Oeltzschner, Eric C. Porges, James J. Prisciandaro, Nicolaas A.J. Puts, Timothy P.L. Roberts, Markus Sack, Napapon Sailasuta, Muhammad G. Saleh, Michael Paul Schallmo, Nicholas Simard, Diederick Stoffers, Stephan P. Swinnen, Martin Tegenthoff, Peter Truong, Guangbin Wang, Iain D. Wilkinson, Hans Jörg Wittsack, Adam J. Woods, Hongmin Xu, Fuhua Yan, Chencheng Zhang, Vadim Zipunnikov, Helge J. Zöllner, Richard A.E. Edden

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Accurate and reliable quantification of brain metabolites measured in vivo using 1 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 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 T 1 -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.

Original languageEnglish
Pages (from-to)537-548
Number of pages12
JournalNeuroImage
Volume191
DOIs
Publication statusPublished - May 1 2019

Fingerprint

gamma-Aminobutyric Acid
Magnetic Resonance Spectroscopy
Water
Research
Aminobutyrates
Creatine
Brain
Cerebrospinal Fluid
Volunteers

Keywords

  • Editing
  • GABA
  • MEGA-PRESS
  • MRS
  • Quantification
  • Tissue correction

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

Cite this

Mikkelsen, M., Rimbault, D. L., Barker, P. B., Bhattacharyya, P. K., Brix, M. K., Buur, P. F., ... Edden, R. A. E. (2019). Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites. NeuroImage, 191, 537-548. https://doi.org/10.1016/j.neuroimage.2019.02.059

Big GABA II : Water-referenced edited MR spectroscopy at 25 research sites. / Mikkelsen, Mark; Rimbault, Daniel L.; Barker, Peter B.; Bhattacharyya, Pallab K.; Brix, Maiken K.; Buur, Pieter F.; Cecil, Kim M.; Chan, Kimberly L.; Chen, David Y.T.; Craven, Alexander R.; Cuypers, Koen; Dacko, Michael; Duncan, Niall W.; Dydak, Ulrike; Edmondson, David A.; Ende, Gabriele; Ersland, Lars; Forbes, Megan A.; Gao, Fei; Greenhouse, Ian; Harris, Ashley D.; He, Naying; Heba, Stefanie; Hoggard, Nigel; Hsu, Tun Wei; Jansen, Jacobus F.A.; Kangarlu, Alayar; Lange, Thomas; Lebel, R. Marc; Li, Yan; Lin, Chien Yuan E.; Liou, Jy Kang; Lirng, Jiing Feng; Liu, Feng; Long, Joanna R.; Ma, Ruoyun; Maes, Celine; Moreno-Ortega, Marta; Murray, Scott O.; Noah, Sean; Noeske, Ralph; Noseworthy, Michael D.; Oeltzschner, Georg; Porges, Eric C.; Prisciandaro, James J.; Puts, Nicolaas A.J.; Roberts, Timothy P.L.; Sack, Markus; Sailasuta, Napapon; Saleh, Muhammad G.; Schallmo, Michael Paul; Simard, Nicholas; Stoffers, Diederick; Swinnen, Stephan P.; Tegenthoff, Martin; Truong, Peter; Wang, Guangbin; Wilkinson, Iain D.; Wittsack, Hans Jörg; Woods, Adam J.; Xu, Hongmin; Yan, Fuhua; Zhang, Chencheng; Zipunnikov, Vadim; Zöllner, Helge J.; Edden, Richard A.E.

In: NeuroImage, Vol. 191, 01.05.2019, p. 537-548.

Research output: Contribution to journalArticle

Mikkelsen, M, Rimbault, DL, Barker, PB, Bhattacharyya, PK, Brix, MK, Buur, PF, Cecil, KM, Chan, KL, Chen, DYT, Craven, AR, Cuypers, K, Dacko, M, Duncan, NW, Dydak, U, Edmondson, DA, Ende, G, Ersland, L, Forbes, MA, Gao, F, Greenhouse, I, Harris, AD, He, N, Heba, S, Hoggard, N, Hsu, TW, Jansen, JFA, Kangarlu, A, Lange, T, Lebel, RM, Li, Y, Lin, CYE, Liou, JK, Lirng, JF, Liu, F, Long, JR, Ma, R, Maes, C, Moreno-Ortega, M, Murray, SO, Noah, S, Noeske, R, Noseworthy, MD, Oeltzschner, G, Porges, EC, Prisciandaro, JJ, Puts, NAJ, Roberts, TPL, Sack, M, Sailasuta, N, Saleh, MG, Schallmo, MP, Simard, N, Stoffers, D, Swinnen, SP, Tegenthoff, M, Truong, P, Wang, G, Wilkinson, ID, Wittsack, HJ, Woods, AJ, Xu, H, Yan, F, Zhang, C, Zipunnikov, V, Zöllner, HJ & Edden, RAE 2019, 'Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites', NeuroImage, vol. 191, pp. 537-548. https://doi.org/10.1016/j.neuroimage.2019.02.059
Mikkelsen M, Rimbault DL, Barker PB, Bhattacharyya PK, Brix MK, Buur PF et al. Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites. NeuroImage. 2019 May 1;191:537-548. https://doi.org/10.1016/j.neuroimage.2019.02.059
Mikkelsen, Mark ; Rimbault, Daniel L. ; Barker, Peter B. ; Bhattacharyya, Pallab K. ; Brix, Maiken K. ; Buur, Pieter F. ; Cecil, Kim M. ; Chan, Kimberly L. ; Chen, David Y.T. ; Craven, Alexander R. ; Cuypers, Koen ; Dacko, Michael ; Duncan, Niall W. ; Dydak, Ulrike ; Edmondson, David A. ; Ende, Gabriele ; Ersland, Lars ; Forbes, Megan A. ; Gao, Fei ; Greenhouse, Ian ; Harris, Ashley D. ; He, Naying ; Heba, Stefanie ; Hoggard, Nigel ; Hsu, Tun Wei ; Jansen, Jacobus F.A. ; Kangarlu, Alayar ; Lange, Thomas ; Lebel, R. Marc ; Li, Yan ; Lin, Chien Yuan E. ; Liou, Jy Kang ; Lirng, Jiing Feng ; Liu, Feng ; Long, Joanna R. ; Ma, Ruoyun ; Maes, Celine ; Moreno-Ortega, Marta ; Murray, Scott O. ; Noah, Sean ; Noeske, Ralph ; Noseworthy, Michael D. ; Oeltzschner, Georg ; Porges, Eric C. ; Prisciandaro, James J. ; Puts, Nicolaas A.J. ; Roberts, Timothy P.L. ; Sack, Markus ; Sailasuta, Napapon ; Saleh, Muhammad G. ; Schallmo, Michael Paul ; Simard, Nicholas ; Stoffers, Diederick ; Swinnen, Stephan P. ; Tegenthoff, Martin ; Truong, Peter ; Wang, Guangbin ; Wilkinson, Iain D. ; Wittsack, Hans Jörg ; Woods, Adam J. ; Xu, Hongmin ; Yan, Fuhua ; Zhang, Chencheng ; Zipunnikov, Vadim ; Zöllner, Helge J. ; Edden, Richard A.E. / Big GABA II : Water-referenced edited MR spectroscopy at 25 research sites. In: NeuroImage. 2019 ; Vol. 191. pp. 537-548.
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abstract = "Accurate and reliable quantification of brain metabolites measured in vivo using 1 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 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 T 1 -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.",
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TY - JOUR

T1 - Big GABA II

T2 - Water-referenced edited MR spectroscopy at 25 research sites

AU - Mikkelsen, Mark

AU - Rimbault, Daniel L.

AU - Barker, Peter B.

AU - Bhattacharyya, Pallab K.

AU - Brix, Maiken K.

AU - Buur, Pieter F.

AU - Cecil, Kim M.

AU - Chan, Kimberly L.

AU - Chen, David Y.T.

AU - Craven, Alexander R.

AU - Cuypers, Koen

AU - Dacko, Michael

AU - Duncan, Niall W.

AU - Dydak, Ulrike

AU - Edmondson, David A.

AU - Ende, Gabriele

AU - Ersland, Lars

AU - Forbes, Megan A.

AU - Gao, Fei

AU - Greenhouse, Ian

AU - Harris, Ashley D.

AU - He, Naying

AU - Heba, Stefanie

AU - Hoggard, Nigel

AU - Hsu, Tun Wei

AU - Jansen, Jacobus F.A.

AU - Kangarlu, Alayar

AU - Lange, Thomas

AU - Lebel, R. Marc

AU - Li, Yan

AU - Lin, Chien Yuan E.

AU - Liou, Jy Kang

AU - Lirng, Jiing Feng

AU - Liu, Feng

AU - Long, Joanna R.

AU - Ma, Ruoyun

AU - Maes, Celine

AU - Moreno-Ortega, Marta

AU - Murray, Scott O.

AU - Noah, Sean

AU - Noeske, Ralph

AU - Noseworthy, Michael D.

AU - Oeltzschner, Georg

AU - Porges, Eric C.

AU - Prisciandaro, James J.

AU - Puts, Nicolaas A.J.

AU - Roberts, Timothy P.L.

AU - Sack, Markus

AU - Sailasuta, Napapon

AU - Saleh, Muhammad G.

AU - Schallmo, Michael Paul

AU - Simard, Nicholas

AU - Stoffers, Diederick

AU - Swinnen, Stephan P.

AU - Tegenthoff, Martin

AU - Truong, Peter

AU - Wang, Guangbin

AU - Wilkinson, Iain D.

AU - Wittsack, Hans Jörg

AU - Woods, Adam J.

AU - Xu, Hongmin

AU - Yan, Fuhua

AU - Zhang, Chencheng

AU - Zipunnikov, Vadim

AU - Zöllner, Helge J.

AU - Edden, Richard A.E.

N1 - Copyright © 2019 Elsevier Inc. All rights reserved.

PY - 2019/5/1

Y1 - 2019/5/1

N2 - Accurate and reliable quantification of brain metabolites measured in vivo using 1 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 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 T 1 -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.

AB - Accurate and reliable quantification of brain metabolites measured in vivo using 1 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 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 T 1 -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.

KW - Editing

KW - GABA

KW - MEGA-PRESS

KW - MRS

KW - Quantification

KW - Tissue correction

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