Ax<scp>T</scp>ract: Toward microstructure informed tractography

  • Gabriel Girard
    Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science Université de Sherbrooke Sherbrooke Canada
  • Alessandro Daducci
    Signal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne Lausanne Switzerland
  • Laurent Petit
    Groupe d'Imagie Neurofonctionnelle, Institut des Maladies Neurodégénératives ‐ UMR 5293, CNRS, CEA University of Bordeaux Bordeaux France
  • Jean‐Philippe Thiran
    Signal Processing Lab (LTS5), School of Engineering, École Polytechnique Fédérale de Lausanne Lausanne Switzerland
  • Kevin Whittingstall
    Department of Diagnostic Radiology, Faculty of Medicine and Health Science Université de Sherbrooke Sherbrooke Canada
  • Rachid Deriche
    Project Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur Sophia Antipolis France
  • Demian Wassermann
    Project Team Athena, Inria Sophia Antipolis Méditerranée, Université Côte d'Azur Sophia Antipolis France
  • Maxime Descoteaux
    Sherbrooke Connectivity Imaging Lab, Computer Science Department, Faculty of Science Université de Sherbrooke Sherbrooke Canada

説明

<jats:title>Abstract</jats:title><jats:p>Diffusion‐weighted (DW) magnetic resonance imaging (MRI) tractography has become the tool of choice to probe the human brain's white matter in vivo. However, tractography algorithms produce a large number of erroneous streamlines (false positives), largely due to complex ambiguous tissue configurations. Moreover, the relationship between the resulting streamlines and the underlying white matter microstructure characteristics remains poorly understood. In this work, we introduce a new approach to simultaneously reconstruct white matter fascicles and characterize the apparent distribution of axon diameters within fascicles. To achieve this, our method, <jats:italic>AxTract</jats:italic>, takes full advantage of the recent development DW‐MRI microstructure acquisition, modeling, and reconstruction techniques. This enables <jats:italic>AxTract</jats:italic> to separate parallel fascicles with different microstructure characteristics, hence reducing ambiguities in areas of complex tissue configuration. We report a decrease in the incidence of erroneous streamlines compared to the conventional deterministic tractography algorithms on simulated data. We also report an average increase in streamline density over 15 known fascicles of the 34 healthy subjects. Our results suggest that microstructure information improves tractography in crossing areas of the white matter. Moreover, <jats:italic>AxTract</jats:italic> provides additional microstructure information along the fascicle that can be studied alongside other streamline‐based indices. Overall, <jats:italic>AxTract</jats:italic> provides the means to distinguish and follow white matter fascicles using their microstructure characteristics, bringing new insights into the white matter organization. This is a step forward in microstructure informed tractography, paving the way to a new generation of algorithms able to deal with intricate configurations of white matter fibers and providing quantitative brain connectivity analysis. <jats:italic>Hum Brain Mapp 38:5485–5500, 2017</jats:italic>. © <jats:bold>2017 Wiley Periodicals, Inc.</jats:bold></jats:p>

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