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Abstract #1605

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

Jan Martin1, Andreas Wetscherek2, Lars Müller3,4, 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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