Frequency drift in MR spectroscopy at 3T

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Frequency drift in MR spectroscopy at 3T. / Hui, Steve C N; Mikkelsen, Mark; Zöllner, Helge J et al.
In: Neuroimage, Vol. 241, 118430, 01.11.2021.

Research output: Contribution to journalArticlepeer-review

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Hui, SCN, Mikkelsen, M, Zöllner, HJ, Ahluwalia, V, Alcauter, S, Baltusis, L, Barany, DA, Barlow, LR, Becker, R, Berman, JI, Berrington, A, Bhattacharyya, PK, Blicher, JU, Bogner, W, Brown, MS, Calhoun, VD, Castillo, R, Cecil, KM, Choi, YB, Chu, WCW, Clarke, WT, Craven, AR, Cuypers, K, Dacko, M, de la Fuente-Sandoval, C, Desmond, P, Domagalik, A, Dumont, J, Duncan, NW, Dydak, U, Dyke, K, Edmondson, DA, Ende, G, Ersland, L, Evans, CJ, Fermin, ASR, Ferretti, A, Fillmer, A, Gong, T, Greenhouse, I, Grist, JT, Gu, M, Harris, AD, Hat, K, Heba, S, Heckova, E, Hegarty, JP, Heise, K-F, Jacobson, A, Jansen, JFA, Jenkins, CW, Johnston, SJ, Juchem, C, Kangarlu, A, Kerr, AB, Landheer, K, Lange, T, Lee, P, Levendovszky, SR, Limperopoulos, C, Liu, F, Lloyd, W, Lythgoe, DJ, Machizawa, MG, MacMillan, EL, Maddock, RJ, Manzhurtsev, AV, Martinez-Gudino, ML, Miller, JJ, Mirzakhanian, H, Moreno-Ortega, M, Mullins, PG, Near, J, Noeske, R, Nordhøy, W, Oeltzschner, G, Osorio-Duran, R, Otaduy, MCG, Pasaye, EH, Peeters, R, Peltier, SJ, Pilatus, U, Polomac, N, Porges, EC, Pradhan, S, Prisciandaro, JJ, Puts, NA, Rae, CD, Reyes-Madrigal, F, Roberts, TPL, Robertson, CE, Rosenberg, JT, Rotaru, D-G, O'Gorman Tuura, RL, Saleh, MG, Sandberg, K, Sangill, R, Schembri, K, Schrantee, A, Semenova, NA, Singel, D, Sitnikov, R, Smith, J, Song, Y, Stark, C, Stoffers, D, Swinnen, SP, Tain, R, Tanase, C, Tapper, S, Tegenthoff, M, Thiel, T, Thioux, M, Truong, P, van Dijk, P, Vella, N, Vidyasagar, R, Vovk, A, Wang, G, Westlye, LT, Wilbur, TK, Willoughby, WR, Wilson, M, Wittsack, H-J, Woods, AJ, Wu, Y-C, Xu, J, Lopez, MY, Yeung, DKW, Zhao, Q, Zhou, X, Zupan, G, Edden, RAE, Nakajima, SL & Honda, S 2021, 'Frequency drift in MR spectroscopy at 3T', Neuroimage, vol. 241, 118430. https://doi.org/10.1016/j.neuroimage.2021.118430

APA

Hui, S. C. N., Mikkelsen, M., Zöllner, H. J., Ahluwalia, V., Alcauter, S., Baltusis, L., Barany, D. A., Barlow, L. R., Becker, R., Berman, J. I., Berrington, A., Bhattacharyya, P. K., Blicher, J. U., Bogner, W., Brown, M. S., Calhoun, V. D., Castillo, R., Cecil, K. M., Choi, Y. B., ... Honda, S. (2021). Frequency drift in MR spectroscopy at 3T. Neuroimage, 241, Article 118430. https://doi.org/10.1016/j.neuroimage.2021.118430

CBE

Hui SCN, Mikkelsen M, Zöllner HJ, Ahluwalia V, Alcauter S, Baltusis L, Barany DA, Barlow LR, Becker R, Berman JI, et al. 2021. Frequency drift in MR spectroscopy at 3T. Neuroimage. 241:Article 118430. https://doi.org/10.1016/j.neuroimage.2021.118430

MLA

VancouverVancouver

Hui SCN, Mikkelsen M, Zöllner HJ, Ahluwalia V, Alcauter S, Baltusis L et al. Frequency drift in MR spectroscopy at 3T. Neuroimage. 2021 Nov 1;241:118430. Epub 2021 Jul 24. doi: 10.1016/j.neuroimage.2021.118430

Author

Hui, Steve C N ; Mikkelsen, Mark ; Zöllner, Helge J et al. / Frequency drift in MR spectroscopy at 3T. In: Neuroimage. 2021 ; Vol. 241.

RIS

TY - JOUR

T1 - Frequency drift in MR spectroscopy at 3T

AU - Hui, Steve C N

AU - Mikkelsen, Mark

AU - Zöllner, Helge J

AU - Ahluwalia, Vishwadeep

AU - Alcauter, Sarael

AU - Baltusis, Laima

AU - Barany, Deborah A

AU - Barlow, Laura R

AU - Becker, Robert

AU - Berman, Jeffrey I

AU - Berrington, Adam

AU - Bhattacharyya, Pallab K

AU - Blicher, Jakob Udby

AU - Bogner, Wolfgang

AU - Brown, Mark S

AU - Calhoun, Vince D

AU - Castillo, Ryan

AU - Cecil, Kim M

AU - Choi, Yeo Bi

AU - Chu, Winnie C W

AU - Clarke, William T

AU - Craven, Alexander R

AU - Cuypers, Koen

AU - Dacko, Michael

AU - de la Fuente-Sandoval, Camilo

AU - Desmond, Patricia

AU - Domagalik, Aleksandra

AU - Dumont, Julien

AU - Duncan, Niall W

AU - Dydak, Ulrike

AU - Dyke, Katherine

AU - Edmondson, David A

AU - Ende, Gabriele

AU - Ersland, Lars

AU - Evans, C John

AU - Fermin, Alan S R

AU - Ferretti, Antonio

AU - Fillmer, Ariane

AU - Gong, Tao

AU - Greenhouse, Ian

AU - Grist, James T

AU - Gu, Meng

AU - Harris, Ashley D

AU - Hat, Katarzyna

AU - Heba, Stefanie

AU - Heckova, Eva

AU - Hegarty, John P

AU - Heise, Kirstin-Friederike

AU - Jacobson, Aaron

AU - Jansen, Jacobus F A

AU - Jenkins, Christopher W

AU - Johnston, Stephen J

AU - Juchem, Christoph

AU - Kangarlu, Alayar

AU - Kerr, Adam B

AU - Landheer, Karl

AU - Lange, Thomas

AU - Lee, Phil

AU - Levendovszky, Swati Rane

AU - Limperopoulos, Catherine

AU - Liu, Feng

AU - Lloyd, William

AU - Lythgoe, David J

AU - Machizawa, Maro G

AU - MacMillan, Erin L

AU - Maddock, Richard J

AU - Manzhurtsev, Andrei V

AU - Martinez-Gudino, María L

AU - Miller, Jack J

AU - Mirzakhanian, Heline

AU - Moreno-Ortega, Marta

AU - Mullins, Paul G

AU - Near, Jamie

AU - Noeske, Ralph

AU - Nordhøy, Wibeke

AU - Oeltzschner, Georg

AU - Osorio-Duran, Raul

AU - Otaduy, Maria C G

AU - Pasaye, Erick H

AU - Peeters, Ronald

AU - Peltier, Scott J

AU - Pilatus, Ulrich

AU - Polomac, Nenad

AU - Porges, Eric C

AU - Pradhan, Subechhya

AU - Prisciandaro, James Joseph

AU - Puts, Nicolaas A

AU - Rae, Caroline D

AU - Reyes-Madrigal, Francisco

AU - Roberts, Timothy P L

AU - Robertson, Caroline E

AU - Rosenberg, Jens T

AU - Rotaru, Diana-Georgiana

AU - O'Gorman Tuura, Ruth L

AU - Saleh, Muhammad G

AU - Sandberg, Kristian

AU - Sangill, Ryan

AU - Schembri, Keith

AU - Schrantee, Anouk

AU - Semenova, Natalia A

AU - Singel, Debra

AU - Sitnikov, Rouslan

AU - Smith, Jolinda

AU - Song, Yulu

AU - Stark, Craig

AU - Stoffers, Diederick

AU - Swinnen, Stephan P

AU - Tain, Rongwen

AU - Tanase, Costin

AU - Tapper, Sofie

AU - Tegenthoff, Martin

AU - Thiel, Thomas

AU - Thioux, Marc

AU - Truong, Peter

AU - van Dijk, Pim

AU - Vella, Nolan

AU - Vidyasagar, Rishma

AU - Vovk, Andrej

AU - Wang, Guangbin

AU - Westlye, Lars T

AU - Wilbur, Timothy K

AU - Willoughby, William R

AU - Wilson, Martin

AU - Wittsack, Hans-Jörg

AU - Woods, Adam J

AU - Wu, Yen-Chien

AU - Xu, Junqian

AU - Lopez, Maria Yanez

AU - Yeung, David K W

AU - Zhao, Qun

AU - Zhou, Xiaopeng

AU - Zupan, Gasper

AU - Edden, Richard A E

AU - Nakajima, Shinichiro Luke

AU - Honda, Shiori

N1 - Copyright © 2021. Published by Elsevier Inc.

PY - 2021/11/1

Y1 - 2021/11/1

N2 - PURPOSE: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.METHOD: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).RESULTS: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.DISCUSSION: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

AB - PURPOSE: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.METHOD: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).RESULTS: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.DISCUSSION: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

U2 - 10.1016/j.neuroimage.2021.118430

DO - 10.1016/j.neuroimage.2021.118430

M3 - Article

C2 - 34314848

VL - 241

JO - Neuroimage

JF - Neuroimage

SN - 1053-8119

M1 - 118430

ER -