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Abstract #3562

Estimating mixtures of 6D diffusion tensor distributions with "Magic DIAMOND": are b-plates better than b-spheres?

Alexis Reymbaut1, Alex Valcourt Caron1, Guillaume Gilbert2, Simon K. Warfield3, Maxime Descoteaux1, and Benoit Scherrer3

1Université de Sherbrooke, Sherbrooke, QC, Canada, 2MR Clinical Science, Philips Healthcare Canada, Markham, ON, Canada, 3Dept. of Radiology, Boston Children’s Hospital, Boston, MA, United States

Tensor-valued diffusion encoding enables disentangling isotropic and anisotropic diffusion components. However, its impact on estimating brain microstructural features has only been studied in a handful of parametric models. In this work, we evaluate the Magic DIAMOND model, that allows characterization of crossing fascicles and assessment of diffusivities for each, using combinations of linear, planar and spherical encodings in vivo. Building statistics through stratified bootstrap, we show that spherical encoding substantially increases the variance in estimated parameters and should be avoided. Planar encoding, on the other hand, did not offer clear improvement or worsening within our current acquisition scheme and setup.

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