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 Greenhouse; Ashley 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

doi:10.1016/j.neuroimage.2019.02.059

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

Mark Mikkelsen (Corresponding author), 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

Signal Processing Systems

Onderzoeksoutput: Bijdrage aan tijdschrift › Tijdschriftartikel › Academic › peer review

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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.

Originele taal-2	Engels
Pagina's (van-tot)	537-548
Aantal pagina's	12
Tijdschrift	Neuroimage
Volume	191
DOI's	https://doi.org/10.1016/j.neuroimage.2019.02.059
Status	Gepubliceerd - 1 mei 2019

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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 ). AJW was supported by NIA grants K01 AG050707 and R01 AG054077 and the University of Florida (UF) , the Center for Cognitive Aging and Memory (CAM) and the McKnight Brain Research Foundation (MBRF) . DAE was supported by NIH grant F31 ES028081 . ECP was supported by NIAAA grant K01 AA025306 and UF, CAM and MBRF. HJZ was supported by DFG grant SFB 974 TP B07 . IDW and NH thank The Wellcome Trust , the NIHR-Sheffield Biomedical Research Center and Mrs. J. Bigley of the University of Sheffield MRI Unit for her assistance with data acquisition. JJP was supported by NIAAA grant K23 AA020842 . KMC was supported by NIH grants R01 MH095014 and R01 NS096207 . MPS was supported by NIH grant F32 EY025121 . NAJP receives salary support from NIH grant R00 MH107719 . SPS was supported by the Research Foundation - Flanders ( G089818N ), the Excellence of Science ( EOS, 30446199 , MEMODYN) and the KU Leuven Research Fund ( C16/15/070 ). 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. Appendix A

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Mikkelsen, M., Rimbault, D. L., Barker, P. B., Bhattacharyya, P. K., Brix, M. K., Buur, P. F., Cecil, K. M., Chan, K. L., Chen, D. Y. T., Craven, A. R., Cuypers, K., Dacko, M., Duncan, N. W., Dydak, U., Edmondson, D. A., Ende, G., Ersland, L., Forbes, M. A., Gao, F., ... Saleh, M. G. (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

@article{26cafecdd58548e5a9e3c82d57f366a9,

title = "Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites",

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. ",

keywords = "Editing, GABA, MEGA-PRESS, MRS, Quantification, Tissue correction",

author = "Mark Mikkelsen and Rimbault, {Daniel L.} and Barker, {Peter B.} and Bhattacharyya, {Pallab K.} and Brix, {Maiken K.} and Buur, {Pieter F.} and Cecil, {Kim M.} and Chan, {Kimberly L.} and Chen, {David Y.T.} and Craven, {Alexander R.} and Koen Cuypers and Michael Dacko and Duncan, {Niall W.} and Ulrike Dydak and Edmondson, {David A.} and Gabriele Ende and Lars Ersland and Forbes, {Megan A.} and Fei Gao and Ian Greenhouse and Harris, {Ashley D.} and Naying He and Stefanie Heba and Nigel Hoggard and Hsu, {Tun Wei} and Jansen, {Jacobus F.A.} and Alayar Kangarlu and Thomas Lange and Lebel, {R. Marc} and Yan Li and Lin, {Chien Yuan E.} and Liou, {Jy Kang} and Lirng, {Jiing Feng} and Feng Liu and Long, {Joanna R.} and Ruoyun Ma and Celine Maes and Marta Moreno-Ortega and Murray, {Scott O.} and Sean Noah and Ralph Noeske and Noseworthy, {Michael D.} and Georg Oeltzschner and Porges, {Eric C.} and Prisciandaro, {James J.} and Puts, {Nicolaas A.J.} and Roberts, {Timothy P.L.} and Markus Sack and Napapon Sailasuta and Saleh, {Muhammad G.}",

year = "2019",

month = may,

day = "1",

doi = "10.1016/j.neuroimage.2019.02.059",

language = "English",

volume = "191",

pages = "537--548",

journal = "Neuroimage",

issn = "1053-8119",

publisher = "Academic Press Inc.",

}

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 2019, 'Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites', Neuroimage, vol. 191, blz. 537-548. https://doi.org/10.1016/j.neuroimage.2019.02.059

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.

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

UR - http://www.scopus.com/inward/record.url?scp=85062493930&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2019.02.059

DO - 10.1016/j.neuroimage.2019.02.059

M3 - Article

C2 - 30840905

AN - SCOPUS:85062493930

SN - 1053-8119

VL - 191

SP - 537

EP - 548

JO - Neuroimage

JF - Neuroimage

ER -

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

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