Frequency drift in MR spectroscopy at 3T.
3T
Frequency drift
Magnetic resonance spectroscopy (MRS)
Multi-site
Multi-vendor
Press
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
01 11 2021
01 11 2021
Historique:
received:
26
03
2021
revised:
18
06
2021
accepted:
22
07
2021
pubmed:
28
7
2021
medline:
21
10
2021
entrez:
27
7
2021
Statut:
ppublish
Résumé
Heating of gradient coils and passive shim components is a common cause of instability in the B 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). 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. 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.
Identifiants
pubmed: 34314848
pii: S1053-8119(21)00705-9
doi: 10.1016/j.neuroimage.2021.118430
pmc: PMC8456751
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
118430Subventions
Organisme : NIBIB NIH HHS
ID : P41 EB031771
Pays : United States
Organisme : NIA NIH HHS
ID : R00 AG062230
Pays : United States
Organisme : NIAAA NIH HHS
ID : K01 AA025306
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB023963
Pays : United States
Organisme : NICHD NIH HHS
ID : P50 HD105354
Pays : United States
Organisme : NIBIB NIH HHS
ID : K99 EB028828
Pays : United States
Organisme : NIAAA NIH HHS
ID : R01 AA025365
Pays : United States
Organisme : NIA NIH HHS
ID : K99 AG062230
Pays : United States
Organisme : NIH HHS
ID : S10 OD021726
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA054275
Pays : United States
Organisme : NIBIB NIH HHS
ID : P41 EB015909
Pays : United States
Organisme : NIH HHS
ID : S10 OD021648
Pays : United States
Organisme : NIH HHS
ID : S10 OD012336
Pays : United States
Organisme : NIDCD NIH HHS
ID : R01 DC008871
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG066519
Pays : United States
Organisme : NIDA NIH HHS
ID : K99 DA051315
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG060245
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH110270
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB016089
Pays : United States
Informations de copyright
Copyright © 2021. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest Jack J. Miller would like to acknowledge the support of a Novo Nordisk Research Fellowship run in conjunction with the University of Oxford. Francisco Reyes-Madrigal has served as a speaker for Janssen (Johnson & Johnson) and AstraZeneca. Marc Thioux and Pim van Dijk were supported by The Netherlands Organization for Health Research and Development (ZonMW) and the Dorhout Mees Foundation. All other authors have no conflict of interest to declare.
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