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題名 Reproducibility of structural brain connectivity and network metrics using probabilistic diffusion tractography
作者 蔡尚岳
Tsai, Shang-Yueh
貢獻者 應物所
日期 2018
上傳時間 11-Sep-2018 18:24:51 (UTC+8)
摘要 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 < 45%, CVbs < 90%, ICC = 0.75 ± 0.12. The presence of 1% difference in the sparsity can cause additional within-subject variations on network metrics. In conclusion, applying connectivity thresholds on structural network to exclude spurious connections for the network analysis should be considered as necessities. Our findings suggest that a connectivity threshold over 0.01 can be applied without significant effect on the short-term when network metrics are evaluated at the same sparsity in subject group. When the sparsity is not the same, the procedure of integration over various connectivity thresholds can provide reliable estimation of network metrics.
關聯 Scientific Reportsvolume 8, Article number: 11562
資料類型 article
DOI https://doi.org/10.1038/s41598-018-29943-0
dc.contributor 應物所
dc.creator (作者) 蔡尚岳zh_TW
dc.creator (作者) Tsai, Shang-Yuehen_US
dc.date (日期) 2018
dc.date.accessioned 11-Sep-2018 18:24:51 (UTC+8)-
dc.date.available 11-Sep-2018 18:24:51 (UTC+8)-
dc.date.issued (上傳時間) 11-Sep-2018 18:24:51 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/120067-
dc.description.abstract (摘要) 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 < 45%, CVbs < 90%, ICC = 0.75 ± 0.12. The presence of 1% difference in the sparsity can cause additional within-subject variations on network metrics. In conclusion, applying connectivity thresholds on structural network to exclude spurious connections for the network analysis should be considered as necessities. Our findings suggest that a connectivity threshold over 0.01 can be applied without significant effect on the short-term when network metrics are evaluated at the same sparsity in subject group. When the sparsity is not the same, the procedure of integration over various connectivity thresholds can provide reliable estimation of network metrics.en_US
dc.format.extent 4670702 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Scientific Reportsvolume 8, Article number: 11562
dc.title (題名) Reproducibility of structural brain connectivity and network metrics using probabilistic diffusion tractographyen_US
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1038/s41598-018-29943-0
dc.doi.uri (DOI) https://doi.org/10.1038/s41598-018-29943-0