Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury:predictors of patient prognosis  被引量:1

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作  者:Sihong Huang Jungong Han Hairong Zheng Mengjun Li Chuxin Huang Xiaoyan Kui Jun Liu 

机构地区:[1]Department of Radiology,The Second Xiangya Hospital,Central South University,Changsha,Hunan Province,China [2]Department of Computer Science,Aberystwyth University,Aberystwyth,Ceredigion,UK [3]Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,Guangdong Province,China [4]School of Computer Science and Engineering,Central South University,Changsha,Hunan Province,China [5]Department of Radiology,Quality Control Center of Hunan Province,Changsha,Hunan Province,China [6]Clinical Research Center for Medical Imaging of Hunan Province,Changsha,Hunan Province,China

出  处:《Neural Regeneration Research》2024年第7期1553-1558,共6页中国神经再生研究(英文版)

基  金:supported by the National Natural Science Foundation of China,Nos.81671671(to JL),61971451(to JL),U22A2034(to XK),62177047(to XK);the National Defense Science and Technology Collaborative Innovation Major Project of Central South University,No.2021gfcx05(to JL);Clinical Research Cen terfor Medical Imaging of Hunan Province,No.2020SK4001(to JL);Key Emergency Project of Pneumonia Epidemic of Novel Coronavirus Infection of Hu nan Province,No.2020SK3006(to JL);Innovative Special Construction Foundation of Hunan Province,No.2019SK2131(to JL);the Science and Technology lnnovation Program of Hunan Province,Nos.2021RC4016(to JL),2021SK53503(to ML);Scientific Research Program of Hunan Commission of Health,No.202209044797(to JL);Central South University Research Program of Advanced Interdisciplinary Studies,No.2023Q YJC020(to XK);the Natural Science Foundation of Hunan Province,No.2022JJ30814(to ML)。

摘  要:Patients with mild traumatic brain injury have a diverse clinical presentation,and the underlying pathophysiology remains poorly understood.Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neuro biological markers after mild traumatic brain injury.This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury.G raph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function.However,most previous mild traumatic brain injury studies using graph theory have focused on specific populations,with limited exploration of simultaneous abnormalities in structural and functional connectivity.Given that mild traumatic brain injury is the most common type of traumatic brain injury encounte red in clinical practice,further investigation of the patient characteristics and evolution of structural and functional connectivity is critical.In the present study,we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury.In this longitudinal study,we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 wee ks of injury,as well as 36 healthy controls.Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis.In the acute phase,patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network.More than 3 months of followup data revealed signs of recovery in structural and functional connectivity,as well as cognitive function,in 22 out of the 46 patients.Furthermore,better cognitive function was associated with more efficient networks.Finally,our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal ch

关 键 词:cognitive function CROSS-SECTION FOLLOW-UP functional connectivity graph theory longitudinal study mild traumatic brain injury prediction small-worldness structural connectivity subnetworks whole brain network 

分 类 号:R651.15[医药卫生—外科学]

 

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