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Abstract #2038

Nonparametric D(Ω)-distributions for model-free analysis of b(Ω)-encoded multidimensional diffusion MRI on ex vivo rat brain

Omar Narvaez1, Maxime Yon2, Alejandra Sierra1, and Daniel Topgaard3
1A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland, 2CEMHTI, French National Centre for Scientific Research, Paris, France, 3Department of Chemistry, Lund University, Lund, Sweden

Nonparametric distributions of cell sizes or diffusion tensors have recently been applied to analyze clinically relevant data acquired with advanced diffusion encoding schemes building on oscillating gradients, targeting the frequency-dependence and cell size, or more general q-vector trajectories focusing on the tensorial aspects. We introduce nonparametric D(ω)-distributions as a joint analysis framework taking both frequency-dependence and tensorial properties into account, and demonstrate the approach with ex vivo rat brain data acquired with gradient waveforms exploring the relevant dimensions of the tensor-valued encoding spectrum b(ω).

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