Quantification of brain connectivity using Diffusion Weighted MRI


Diffusion Weighted (DW) MRI is a unique and noninvasive method to characterize tissue microstructure, based on the random thermal motion of water molecules. Of particular interest is its potential for inferring the orientation of the coherently oriented fiber bundles within brain white matter tissue, as this opens up the possibility of investigating brain connectivity in vivo using so-called fiber-tracking algorithms. This relatively new technique is becoming a valuable diagnostic tool for a large number of neuropathological diseases.

Currently, diffusion tensor imaging (DTI) is widely used to extract white matter fiber orientations from diffusion-weighted (DW) MR data of the brain. In regions of fiber crossings, however, DTI has been shown to be inadequate. Recent acquisition methods featuring high angular resolution and strong diffusion weighting (HARDI-acquisitions) and new reconstruction techniques make it possible to extract multiple fiber orientations from a single voxel.

The main goals of this research topic are:

  • to use clinically relevant acquisitions (< 15 minutes)
  • to estimate fiber orientations in each voxel as accurate as possible
  • to estimate global brain connectivity in a quantitative / probabilistic way by means of tractography
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