Estimating the confidence level of white matter connections obtained with MRI tractography.

Détails

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Etat: Public
Version: de l'auteur
ID Serval
serval:BIB_BA38C7E05E95
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Estimating the confidence level of white matter connections obtained with MRI tractography.
Périodique
PLoS ONE
Auteur(s)
Gigandet X., Hagmann P., Kurant M., Cammoun L., Meuli R., Thiran J.P.
ISSN
1932-6203
Statut éditorial
Publié
Date de publication
2008
Peer-reviewed
Oui
Volume
3
Numéro
12
Pages
e4006
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't ; Validation Studies
Gigandet, Xavier Hagmann, Patric Kurant, Maciej Cammoun, Leila Meuli, Reto Thiran, Jean-Philippe
Résumé
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. METHODOLOGY/PRINCIPAL FINDINGS: 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/SIGNIFICANCE: 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.
Mots-clé
Brain, Brain Mapping, Diffusion Magnetic Resonance Imaging, Humans, Image Processing, Computer-Assisted, Models, Biological, Neural Pathways, Sensitivity and Specificity
Pubmed
Web of science
Open Access
Oui
Création de la notice
19/02/2009 16:13
Dernière modification de la notice
20/08/2019 15:28
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