Mapping gradient nonlinearity and miscalibration using diffusion-weighted MR images of a uniform isotropic phantom.


Journal

Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245

Informations de publication

Date de publication:
12 2021
Historique:
revised: 26 05 2021
received: 24 11 2020
accepted: 27 05 2021
pubmed: 6 8 2021
medline: 1 2 2022
entrez: 5 8 2021
Statut: ppublish

Résumé

To use diffusion measurements to map the spatial dependence of the magnetic field produced by the gradient coils of an MRI scanner with sufficient accuracy to correct errors in quantitative diffusion MRI (DMRI) caused by gradient nonlinearity and gradient amplifier miscalibration. The field produced by the gradient coils is expanded in regular solid harmonics. The expansion coefficients are found by fitting a model to a minimum set of diffusion-weighted images of an isotropic diffusion phantom. The accuracy of the resulting gradient coil field maps is evaluated by using them to compute corrected b-matrices that are then used to process a multi-shell diffusion tensor imaging (DTI) dataset with 32 diffusion directions per shell. The method substantially reduces both the spatial inhomogeneity of the computed mean diffusivities (MD) and the computed values of the fractional anisotropy (FA), as well as virtually eliminating any artifactual directional bias in the tensor field secondary to gradient nonlinearity. When a small scaling miscalibration was purposely introduced in the x, y, and z, the method accurately detected the amount of miscalibration on each gradient axis. The method presented detects and corrects the effects of gradient nonlinearity and gradient gain miscalibration using a simple isotropic diffusion phantom. The correction would improve the accuracy of DMRI measurements in the brain and other organs for both DTI and higher order diffusion analysis. In particular, it would allow calibration of MRI systems, improving data harmony in multicenter studies.

Identifiants

pubmed: 34351007
doi: 10.1002/mrm.28890
pmc: PMC8596767
doi:

Types de publication

Journal Article Research Support, N.I.H., Intramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

3259-3273

Informations de copyright

© 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

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Auteurs

Alan Seth Barnett (AS)

Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA.

M Okan Irfanoglu (MO)

Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA.

Bennett Landman (B)

Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.
Department of Biomedical Engineering, Vanderbilt Brain Institute, Nashville, TN, USA.
Vanderbilt Kennedy Center, School of Engineering, Vanderbilt University, Nashville, TN, USA.
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.
Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.

Baxter Rogers (B)

Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.

Carlo Pierpaoli (C)

Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA.

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Classifications MeSH