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Eddy current nulled constrained optimization of isotropic diffusion encoding gradient waveforms
Author(s) -
Yang Grant,
McNab Jennifer A.
Publication year - 2019
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.27539
Subject(s) - eddy current , waveform , isotropy , distortion (music) , physics , diffusion , signal (programming language) , acoustics , optics , nuclear magnetic resonance , computer science , voltage , amplifier , optoelectronics , cmos , quantum mechanics , thermodynamics , programming language
Purpose Isotropic diffusion encoding efficiently encodes additional microstructural information in combination with conventional linear diffusion encoding. However, the gradient‐intensive isotropic diffusion waveforms generate significant eddy currents, which cause image distortions. The purpose of this study is to present a method for designing isotropic diffusion encoding waveforms with intrinsic eddy current nulling. Methods Eddy current nulled gradient waveforms were designed using a constrained optimization waveform for a 3T GE Premier MRI system. Encoding waveforms were designed for a variety of eddy current null times and sequence timings to evaluate the achievable b‐value. Waveforms were also tested with both eddy current nulling and concomitant field compensation. Distortion reduction was tested in both phantoms and the in vivo human brain. Results The feasibility of isotropic diffusion encoding with intrinsic correction of eddy current distortion and signal bias from concomitant fields was demonstrated. The constrained optimization algorithm produced gradient waveforms with the specified eddy current null times. The reduction in the achievable diffusion weighting was dependent on the number of eddy current null times. A reduction in the eddy current–induced image distortions was observed in both phantoms and in vivo human subjects. Conclusion The proposed framework allows the design of isotropic diffusion‐encoding sequences with reduced image distortion.