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Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players

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Computational Diffusion MRI

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

We present the concept of fiber-flux density for locally quantifying white matter (WM) fiber bundles. By combining scalar diffusivity measures (e.g., fractional anisotropy) with fiber-flux measurements, we define new local descriptors called Fiber-Flux Diffusion Density (FFDD) vectors. Applying each descriptor throughout fiber bundles allows along-tract coupling of a specific diffusion measure with geometrical properties, such as fiber orientation and coherence. A key step in the proposed framework is the construction of an FFDD dissimilarity measure for sub-voxel alignment of fiber bundles, based on the fast marching method (FMM). The obtained aligned WM tract-profiles enable meaningful inter-subject comparisons and group-wise statistical analysis. We demonstrate our method using two different datasets of contact sports players . Along-tract pairwise comparison as well as group-wise analysis, with respect to non-player healthy controls, reveal significant and spatially-consistent FFDD anomalies. Comparing our method with along-tract FA analysis shows improved sensitivity to subtle structural anomalies in football players over standard FA measurements.

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Notes

  1. 1.

    The FMM was proposed by Sethian [23] for solving boundary value problems of the Eikonal equation.

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Acknowledgements

This research is partially supported by the Israel Science Foundation (T.R.R. 1638/16) and the IDF Medical Corps (T.R.R.).

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Itay Benou & Tammy Riklin Raviv

  2. The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Itay Benou, Ronel Veksler, Alon Friedman & Tammy Riklin Raviv

  3. Department of Physiology and Cell Biology, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Ronel Veksler & Alon Friedman

  4. Faculty of Medicine, Department of Medical Neuroscience and Brain Repair Centre, Dalhousie University, Halifax, NS, Canada

    Alon Friedman

Authors
  1. Itay Benou
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  2. Ronel Veksler
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  3. Alon Friedman
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  4. Tammy Riklin Raviv
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Editor information

Editors and Affiliations

  1. Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom

    Enrico Kaden

  2. Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom

    Francesco Grussu

  3. Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

    Lipeng Ning

  4. Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom

    Chantal M. W. Tax

  5. Center for Biomedical Imaging, New York University School of Medicine, New York, New York, USA

    Jelle Veraart

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Benou, I., Veksler, R., Friedman, A., Raviv, T.R. (2018). Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players. In: Kaden, E., Grussu, F., Ning, L., Tax, C., Veraart, J. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-73839-0_15

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