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Abstract #0285

Microstructure imaging from a dictionary of Monte Carlo signals: assessment on a rat model of Wallerian degeneration

Gaëtan Rensonnet1, Benoît Scherrer2, Simon K. Warfield2, Benoît Macq1, and Maxime Taquet1,2

1ICTEAM, Université catholique de Louvain, Louvain-la-Neuve, Belgium, 2Computational Radiology Laboratory, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States

We estimate microstructural features of the nervous tissues from diffusion-weighted MRI by using sparse optimization techniques on a dictionary of pre-computed Monte Carlo signals, which more faithfully describe the complex diffusion process in the extra-axonal space of the white matter. The method is validated on synthetic data including single and crossing fibers and on an in vivo rat spinal cord model of Wallerian degeneration. We obtain in vivo microstructural estimates that can be directly related to histological evidence whereas the traditional closed-form formula models DIAMOND and NODDI yield results that are more challenging to interpret physically.

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