Evaluating reproducibility and subject-specificity of microstructure-informed connectivity.
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State: Public
Version: Final published version
License: CC BY-NC-ND 4.0
State: Public
Version: Final published version
License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_DCC78ACF3E8F
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Evaluating reproducibility and subject-specificity of microstructure-informed connectivity.
Journal
NeuroImage
ISSN
1095-9572 (Electronic)
ISSN-L
1053-8119
Publication state
Published
Issued date
09/2022
Peer-reviewed
Oui
Volume
258
Pages
119356
Language
english
Notes
Publication types: Comparative Study ; Journal Article
Publication Status: ppublish
Publication Status: ppublish
Abstract
Tractography enables identifying and evaluating the healthy and diseased brain's white matter pathways from diffusion-weighted magnetic resonance imaging data. As previous evaluation studies have reported significant false-positive estimation biases, recent microstructure-informed tractography algorithms have been introduced to improve the trade-off between specificity and sensitivity. However, a major limitation for characterizing the performance of these techniques is the lack of ground truth brain data. In this study, we compared the performance of two relevant microstructure-informed tractography methods, SIFT2 and COMMIT, by assessing the subject specificity and reproducibility of their derived white matter pathways. Specifically, twenty healthy young subjects were scanned at eight different time points at two different sites. Subject specificity and reproducibility were evaluated using the whole-brain connectomes and a subset of 29 white matter bundles. Our results indicate that although the raw tractograms are more vulnerable to the presence of false-positive connections, they are highly reproducible, suggesting that the estimation bias is subject-specific. This high reproducibility was preserved when microstructure-informed tractography algorithms were used to filter the raw tractograms. Moreover, the resulting track-density images depicted a more uniform coverage of streamlines throughout the white matter, suggesting that these techniques could increase the biological meaning of the estimated fascicles. Notably, we observed an increased subject specificity by employing connectivity pre-processing techniques to reduce the underlaying noise and the data dimensionality (using principal component analysis), highlighting the importance of these tools for future studies. Finally, no strong bias from the scanner site or time between measurements was found. The largest intraindividual variance originated from the sole repetition of data measurements (inter-run).
Keywords
Adult, Connectome, Diffusion Tensor Imaging, False Positive Reactions, Female, Humans, Male, Reproducibility of Results, White Matter/anatomy & histology, White Matter/diagnostic imaging, White Matter/physiology, Young Adult, Brain Connectivity, Diffusion-Weighted MRI, Microstructure Informed Tractography, Reproducibility, Structural Connectome, Subject Specificity, White Matter Fascicles
Pubmed
Web of science
Open Access
Yes
Create date
20/07/2022 9:06
Last modification date
10/10/2023 6:16