Fiber-flux diffusion density for white matter tracts analysis: Application to mild anomalies localization in contact sports players

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageAmerican English
Title of host publicationComputational Diffusion MRI - MICCAI Workshop, 2017
EditorsEnrico Kaden, Francesco Grussu, Lipeng Ning, Chantal M.W. Tax, Jelle Veraart
PublisherSpringer
Pages191-204
Number of pages14
ISBN (Print)9783319738383
DOIs
StatePublished - 1 Jan 2018
EventMICCAI Workshop on Computational Diffusion MRI, CDMRI 2017 - Quebec, Canada
Duration: 10 Sep 201710 Sep 2017

Publication series

NameMathematics and Visualization

Conference

ConferenceMICCAI Workshop on Computational Diffusion MRI, CDMRI 2017
Country/TerritoryCanada
CityQuebec
Period10/09/1710/09/17

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Geometry and Topology
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics

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