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Abstract #4073

Optimized Maxwell Compensation in Asymmetric Diffusion Encoding Gradient Waveform Design for Tensor‐Valued Diffusion Encoding

Erpeng Dai1, Guanhua Wang2, Gaohong Wu3, and Jennifer A McNab1
1Radiology, Stanford University, Stanford, CA, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 3General Electrical Healthcare, Waukesha, WI, United States

Synopsis

Keywords: Diffusion Acquisition, Pulse Sequence Design

Motivation: Asymmetric diffusion encoding gradient waveforms are critical in tensor-valued diffusion encoding for higher diffusion encoding efficiency but can cause non-negligible concomitant gradients. The concomitant gradients can be mitigated by modeling and constraining the Maxwell term (Mindex) in a predefined numerical optimization framework.

Goal(s): To improve Maxwell compensation's accuracy by refining the Mindex estimation model.

Approach: The Mindex estimation model is refined by incorporating the influence of linear interpolation between the initially optimized waveforms and the final diffusion encoding waveforms.

Results: The new Mindex estimation model shows more accurate Mindex estimation and better Maxwell compensation for the final diffusion gradient waveforms.

Impact: A new estimation model of the Maxwell term has been proposed to better compensate for the concomitant gradients in the final asymmetric diffusion encoding gradient waveform, which is promising to further improve the accuracy of diffusion measures.

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Keywords