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Abstract #3567

Non-parametric axon diameter distribution mapping with PGSE: reconstruction of uni- and multimodal distributions

David Romascano1,2, Jonathan Rafael-Patino1, Muhamed Barakovic1, Alessandro Daducci3, Jean-Philippe Thiran1,4, and Tim B. Dyrby2,5

1Signal Processing Lab (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2Danish Research Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 3Department of Computer Science, University of Verona, Verona, Italy, 4Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland, 5Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark

White matter diffusion MRI enables non-invasive estimation of the axon diameter distribution, which is of interest as it modulates communication speed and delays between brain regions, and changes during development and pathology. Distribution mapping is challenging: current methods simplify it by either estimating the mean diameter, imposing parametric distributions, or combining non-parametric approaches with Double Diffusion Encoding. We present a non-parametric framework based on a PGSE protocol. Simulations show robust reconstruction of unimodal and bimodal distributions. The method is sensitive to population specific changes within bimodal distributions, as long as the underlying populations are separated by a minimum distance.

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