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@ARTICLE{Grinberg:837814,
      author       = {Grinberg, Farida and Maximov, Ivan I. and Farrher, Ezequiel
                      and Shah, N. J.},
      title        = {{M}icrostructure-informed slow diffusion tractography in
                      humans enhances visualisation of fibre pathways},
      journal      = {Magnetic resonance imaging},
      volume       = {45},
      issn         = {0730-725X},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2017-06603},
      pages        = {7 - 17},
      year         = {2018},
      abstract     = {Conventional fibre tractography methods based on diffusion
                      tensor imaging exploit diffusion anisotropy and
                      directionality in the range of low diffusion weightings
                      (b-values). High b-value Biexponential Diffusion Tensor
                      Analysis reported previously has demonstrated that
                      fractional anisotropy of the slow diffusion component is
                      essentially higher than that of conventional diffusion
                      tensor imaging whereas popular compartment models associate
                      this slow diffusion component with axonal water fraction.
                      One of the primary aims of this study is to elucidate the
                      feasibility and potential benefits of
                      “microstructure-informed” whole-brain slow-diffusion
                      fibre tracking (SDIFT) in humans. In vivo diffusion-weighted
                      images in humans were acquired in the extended range of
                      diffusion weightings ≤ 6000 s mm− 2 at 3 T. Fast and
                      slow diffusion tensors were reconstructed using the
                      bi-exponential tensor decomposition, and a detailed
                      statistical analysis of the relevant whole-brain tensor
                      metrics was performed. We visualised three-dimensional fibre
                      tracts in in vivo human brains using deterministic
                      streamlining via the major eigenvector of the slow diffusion
                      tensor. In particular, we demonstrated that slow-diffusion
                      fibre tracking provided considerably higher fibre counts of
                      long association fibres and allowed one to reconstruct more
                      short association fibres than conventional diffusion tensor
                      imaging. SDIFT is suggested to be useful as a complimentary
                      method capable to enhance reliability and visualisation of
                      the evaluated fibre pathways. It is especially informative
                      in precortical areas where the uncertainty of the
                      mono-exponential tensor evaluation becomes too high due to
                      decreased anisotropy of low b-value diffusion in these
                      areas. Benefits can be expected in assessment of the
                      residual axonal integrity in tissues affected by various
                      pathological conditions, in surgical planning, and in
                      evaluation of cortical connectivity, in particular, between
                      Brodmann's areas.},
      cin          = {INM-4 / INM-11 / JARA-BRAIN},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-4-20090406 / I:(DE-Juel1)INM-11-20170113 /
                      $I:(DE-82)080010_20140620$},
      pnm          = {573 - Neuroimaging (POF3-573)},
      pid          = {G:(DE-HGF)POF3-573},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000417772500002},
      doi          = {10.1016/j.mri.2017.08.007},
      url          = {https://juser.fz-juelich.de/record/837814},
}