脑损伤和慢性健康症状患者的结构连通性特征:一项试点研究

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Neuroinformatics Pub Date : 2024-10-01 Epub Date: 2024-07-11 DOI:10.1007/s12021-024-09681-7
Xiaojian Kang, Byung C Yoon, Emily Grossner, Maheen M Adamson
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引用次数: 0

摘要

通过弥散张量成像(DTI)获得的弥散特性对创伤性脑损伤(TBI)期间出现的白质异常非常敏感,尤其是对那些有头痛、头晕、疲劳等 TBI 后慢性症状的患者。使用 DTI 评估结构和功能连通性已成为一种很有前途的方法,可用于识别与 TBI 相关的大脑连通性的细微改变,而这些改变在传统成像中是看不到的。本研究评估了与对照组(CG)(n = 13)相比,有(n = 17)或无(n = 16)慢性症状(TBIcs/TBIncs)的 TBI 患者在半球内和半球间连接的结构连通性(SC)和平均分数各向异性(mFA)方面是否有任何变化。与对照组相比,观察到 TBIcs 的 SC 和 mFA 下降,但 TBIncs 没有下降。与 SC 的减少相比,发现有更多连接的 mFA 减少。总体而言,在对比对侧和同侧连接后,所有组别的 SC 均以同侧连接为主。与 CG 相比,TBIcs 比 TBIncs 的 mFA 减少更多。这些研究结果表明,有慢性症状的创伤性脑损伤患者不仅表现出整体和区域性 mFA 的减少,而且还表现出结构性网络连接的减少。
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Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study.

Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.

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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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