2 March 2018 Hubs defined with participation coefficient metric altered following acute mTBI
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Patients with mild traumatic brain injury (mTBI) may suffer from a widespread spectrum of symptoms that arise from the damage of long-distance white matter connections in distributed brain networks. In brain networks, an increasing attention has been devoted to assessing the functional roles of regions by estimating the spatial layout of their connections among different modules, using the participation coefficient. In the present study, we aimed to investigate the role of hubs in inter-subnetwork information coordination and integration by using participation coefficients after mTBI. 74 patients after mTBI within 7 days post-injury and 51 matched healthy controls enrolled in this study. Our results presented that hubs for mTBI patients distributed in more extensive networks such as the default mode network (DMN), ventral attention network (VAN) and frontoparietal network (FPN), somatomotor network (SMN) and visual network (VN), compared with healthy controls limited to the first three. Participation coefficients for mTBI presented significantly decreased in the DMN (P=0.015) and FPN (P=0.02), while increased in the VN (P=0.035). SVM trained with participation coefficient metrics were able to identify mTBI patients from controls with 78% accuracy, providing for its diagnose potential in clinical settings. From our point of view, difference between two groups could be related with functional network reorganization in mTBI groups.
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Xiaocui Wang, Xiaocui Wang, Chuanzhu Sun, Chuanzhu Sun, Shan Wang, Shan Wang, Jieli Cao, Jieli Cao, Hui Xu, Hui Xu, Shuoqiu Gan, Shuoqiu Gan, Zhen Chen, Zhen Chen, Bo Yin, Bo Yin, Guanghui Bai, Guanghui Bai, Meihua Shao, Meihua Shao, Chenghui Gu, Chenghui Gu, Liuxun Hu, Liuxun Hu, Limei Ye, Limei Ye, Dandong Li, Dandong Li, Zhihan Yan, Zhihan Yan, Lijun Bai, Lijun Bai, } "Hubs defined with participation coefficient metric altered following acute mTBI", Proc. SPIE 10574, Medical Imaging 2018: Image Processing, 105742C (2 March 2018); doi: 10.1117/12.2293313; https://doi.org/10.1117/12.2293313

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