English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Purpose: Asymmetric gradient waveforms are attractive for diffusion encodingdue to their superior efficiency, however, the asymmetry may cause a residualgradient moment at the end of the encoding. Depending on the experiment setup,this residual moment may cause significant signal bias and image artifacts. Thepurpose of this study was to develop an asymmetric gradient waveform design fortensor-valued diffusion encoding that is not affected by concomitant gradient.Methods: The Maxwell index was proposed as a scalar invariant that captures theeffect of concomitant gradients and was constrained in the numericaloptimization to 100 (mT/m)$^2$ms to yield Maxwell-compensated waveforms. Theefficacy of this design was tested in an oil phantom, and in a healthy humanbrain. For reference, waveforms from literature were included in the analysis.Simulations were performed to investigate if the design was valid for a widerange of experiments and if it could predict the signal bias. Results:Maxwell-compensated waveforms showed no signal bias in oil or in the brain. Bycontrast, several waveforms from literature showed gross signal bias. In thebrain, the bias was large enough to markedly affect both signal and parametermaps, and the bias could be accurately predicted by theory. Conclusion:Constraining the Maxwell index in the optimization of asymmetric gradientwaveforms yields efficient tensor-valued encoding with concomitant gradientsthat have a negligible effect on the signal. This waveform design is especiallyrelevant in combination with strong gradients, long encoding times, thickslices, simultaneous multi-slice acquisition and large/oblique FOVs.

Maxwell-compensated design of asymmetric gradient waveforms for tensor-valued diffusion encoding