A connectome-based comparison of diffusion MRI schemes.

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State: Serval
Version: author
Serval ID
serval:BIB_EF4BC92DECC4
Type
Article: article from journal or magazin.
Collection
Publications
Title
A connectome-based comparison of diffusion MRI schemes.
Journal
Plos One
Author(s)
Gigandet X., Griffa A., Kober T., Daducci A., Gilbert G., Connelly A., Hagmann P., Meuli R., Thiran J.P., Krueger G.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Publication state
Published
Issued date
2013
Peer-reviewed
Oui
Volume
8
Number
9
Pages
e75061
Language
english
Notes
Publication types: Journal Article
Abstract
Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.
Pubmed
Web of science
Open Access
Yes
Create date
22/10/2013 10:03
Last modification date
09/05/2019 3:12
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