Abstract #1605

Diffusion gradient performance optimization for B-tensor encoded q-space trajectory imaging of the human brain

Jan Martin¹, Andreas Wetscherek², Lars Müller^3,4, Tristan Anselm Kuder³, Michael Uder¹, Bernhard Hensel⁵, and Frederik Bernd Laun¹

¹Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, ²Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom, ³Department Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ⁴CUBRIC, School of Psychology, University of Cardiff, Cardiff, United Kingdom, ⁵Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany

q-Space trajectory imaging is a recently introduced approach for determining microscopic diffusion tensor properties like μFA and orientation coherence. To create the necessary higher order B-tensors special gradient trajectories are needed. The initial implementation of q-space trajectory imaging was based on magic-angle-spinning of the q-vector, and required echo times of 160 ms for b-values of 2000 s/mm². In the current abstract, numerically optimized gradient trajectories were implemented, which reduced the required echo time to 115 ms. The resulting parameter maps benefited from the increase in signal-to-noise ratio.

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