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Reproducibility of structural brain connectivity and network metrics using probabilistic diffusion tractography.


ABSTRACT: The structural connectivity network constructed using probabilistic diffusion tractography can be characterized by the network metrics. In this study, short-term test-retest reproducibility of structural networks and network metrics were evaluated on 30 subjects in terms of within- and between-subject coefficient of variance (CVws, CVbs), and intra class coefficient (ICC) using various connectivity thresholds. The short-term reproducibility under various connectivity thresholds were also investigated when subject groups have same or different sparsity. In summary, connectivity threshold of 0.01 can exclude around 80% of the edges with CVws?=?73.2?±?37.7%, CVbs?=?119.3?±?44.0% and ICC?=?0.62?±?0.19. The rest 20% edges have CVws?bs?

SUBMITTER: Tsai SY 

PROVIDER: S-EPMC6070542 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Reproducibility of structural brain connectivity and network metrics using probabilistic diffusion tractography.

Tsai Shang-Yueh SY  

Scientific reports 20180801 1


The structural connectivity network constructed using probabilistic diffusion tractography can be characterized by the network metrics. In this study, short-term test-retest reproducibility of structural networks and network metrics were evaluated on 30 subjects in terms of within- and between-subject coefficient of variance (CV<sub>ws</sub>, CV<sub>bs</sub>), and intra class coefficient (ICC) using various connectivity thresholds. The short-term reproducibility under various connectivity thresh  ...[more]

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