Eddy current nulled constrained optimization of isotropic diffusion encoding gradient waveforms

Abstract

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.

Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems

“…Specific applications can also benefit substantially from adapting the image quality and scan time to the expected level of variance in the studied population [72]. Tensor-valued diffusion encoding can be accelerated by simultaneous multi-slice imaging [73] and interleaving techniques [36] that reduce acquisition times and improve duty cycle constraints, as well as improvement in terms of reducing eddy-current effects [74, 75].…”

Optimization methods for magnetic resonance imaging gradient waveform design

“…Concomitant fields can be mitigated by using a design constraint in the optimization, [18][19][20] at the expense of several milliseconds in waveform duration and increased compute time, while the impact from non-zero gradient moments can be mitigated by selecting appropriate constraint tolerances on the desired moments. 35 During the design of optimal gradient waveforms there is a trade-off between accuracy (i.e.…”

“…Time-optimal diffusion encoding gradients [13][14][15] were developed to reduce the minimum achievable TE, for a fixed b-value, while also adding the flexibility to null the n th gradient moment, thereby mitigating bulk motion artifacts with a smaller TE penalty compared to conventional diffusion encoding methods. Subsequent developments in diffusion have yielded additional constraints to permit time-optimal encoding gradients that mitigate eddy current induced image distortion [16][17][18] or concomitant magnetic fields 19,20 while increasing the TE by only several milliseconds. The code to generate the gradient waveforms for some of the aforementioned methods can be downloaded from GitHub as follows:…”

“…9 Subsequently, quadratic programming has been used for designing diffusion and velocity encoding gradients. 10,13,18,19 These methods are reliable, but oftentimes require on the order of 10 seconds to 10 minutes to solve, requiring gradient waveforms to be pre-computed before use. Newer optimization strategies, such as primal dual methods described by Chambolle-Pock, 27 separate the constraints and objective function into individual sub-problems with efficient solutions.…”

Center‐out EPI (COEPI): A fast single‐shot imaging technique with a short TE

“…COEPI may be more prone to the eddy current with short time constants because the acquisition of the center k‐space line is right after the end of the diffusion gradients. Optimizations of diffusion‐encoding gradient waveforms have shown to effectively reduce eddy current effects and must be considered for more robust DWI‐COEPI applications in the future.…”