Gradient waveform design for tensor-valued encoding in diffusion MRI

Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of using tensor-valued diffusion encoding is its ability to isolate microscopic diffusion ani-sotropy and use it as a contrast mechanism, something that is not possible with conventional diffusion encod-ing. Methods based on tensor-valued diffusion encoding are finding an increasing number of applications, which highlights the challenge of designing gradient waveforms that are optimal for the application at hand. In this work, we review the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI, as well as limitations and confounders imposed by hardware and physiology, effects beyond the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its interac-tion with accurate measurements and interpretations of data.

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