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Diffusion MRI with concurrent magnetic field monitoring
Author(s) -
Wilm Bertram J.,
Nagy Zoltan,
Barmet Christoph,
Vannesjo S. Johanna,
Kasper Lars,
Haeberlin Max,
Gross Simon,
Dietrich Benjamin E.,
Brunner David O.,
Schmid Thomas,
Pruessmann Klaas P.
Publication year - 2015
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25827
Subject(s) - diffusion mri , image quality , magnetic field , diffusion , computer science , computer vision , artifact (error) , iterative reconstruction , artificial intelligence , nuclear magnetic resonance , physics , algorithm , magnetic resonance imaging , image (mathematics) , medicine , quantum mechanics , radiology , thermodynamics
Purpose Diffusion MRI is compromised by unknown field perturbation during image encoding. The purpose of this study was to address this problem using the recently described approach of concurrent magnetic field monitoring. Methods Magnetic field dynamics were monitored during the echo planar imaging readout of a common diffusion‐weighted MRI sequence using an integrated magnetic field camera setup. The image encoding including encoding changes over the duration of entire scans were quantified and analyzed. Field perturbations were corrected by accounting for them in generalized image reconstruction. The impact on image quality along with geometrical congruence among different diffusion‐weighted images was assessed both qualitatively and quantitatively. Results The most significant field perturbations were found to be related to higher‐order eddy currents from diffusion‐weighting gradients and B 0 field drift as well as gradual changes of short‐term eddy current behavior and mechanical oscillations during the scan. All artifacts relating to dynamic field perturbations were eliminated by incorporating the measured encoding in image reconstruction. Conclusion Concurrent field monitoring combined with generalized reconstruction enhances depiction fidelity in diffusion imaging. In addition to artifact reduction, it improves geometric congruence and thus facilitates image combination for quantitative diffusion analysis. Magn Reson Med 74:925–933, 2015. © 2015 Wiley Periodicals, Inc.