title: Estimating the confidence level of white matter connections obtained with MRI tractography.
abstract: BACKGROUND
  Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics.
  
  
  RESULTS
  In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix.
  
  
  CONCLUSIONS
  Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.
authors.affiliation: Signal Processing Laboratory, LTS5, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. xavier.gigandet@epfl.ch
authors.forename: Xavier
authors.initials: X
authors.lastname: Gigandet
authors.forename: Patric
authors.initials: P
authors.lastname: Hagmann
authors.forename: Maciej
authors.initials: M
authors.lastname: Kurant
authors.forename: Leila
authors.initials: L
authors.lastname: Cammoun
authors.forename: Reto
authors.initials: R
authors.lastname: Meuli
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Thiran
mesh_terms: D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008954:Models, Biological; D009434:Neural Pathways / Q000033:anatomy & histology / Q000000981:diagnostic imaging* / Q000502:physiology; D011859:Radiography; D012680:Sensitivity and Specificity