CASIA OpenIR  > 脑图谱与类脑智能实验室  > 脑网络组研究
Unruptured brain arteriovenous malformations causing seizures localize to one common brain network
Zhao, Shao-Zhi1,2; Zhao, Yu-Xin3,4,5; Liao, Xiao-Hua3,4,5; Huo, Ran1,2; Li, Hao1,2; Jiao, Yu-Ming1,2; Weng, Jian-Cong1,2; Wang, Jie1,2; Liu, Bing6,7; Cao, Yong1,2
发表期刊JOURNAL OF NEUROSCIENCE RESEARCH
ISSN0360-4012
2022-11-07
页码11
摘要

Seizures are a frequent symptom of unruptured brain arteriovenous malformations (bAVMs). However, the brain regions responsible for these seizures remain unclear. To identify the brain regions causally involved in bAVM-related seizures, we retrospectively reviewed 220 patients with unruptured bAVMs. Using voxel-based lesion-symptom mapping (VLSM) analyses, we tested whether individual brain regions were associated with unruptured bAVM-related seizures. The result revealed that unruptured bAVMs causing seizures are anatomically heterogeneous at the voxel level. Subsequently, lesion network mapping (LNM) analyses was performed to determine whether bAVMs causing seizures belonged to a distributed brain network. LNM analyses indicated that these lesions were located in a functional network characterized by connectivity to the left caudate and precuneus. Moreover, the discrimination performance of the identified seizure network was evaluated in discovery set by calculating the individualized network damage score and was tested in validation set. Based on the calculated network damage scores, patients were divided into low-, medium-, and high-risk groups. The prevalence of seizures significantly differed among the three risk categories in both discovery (p = .003) and validation set (p = .004). Finally, we calculated the percentage of voxels in the canonical resting-state networks that overlapped with the seizure-susceptible brain regions to investigate the involvement of resting-state networks. With an involvement percentage over 50%, the frontoparietal control (82.9%), limbic function (76.7%), and default mode network (69.3%) were considered to be impacted in bAVM-related seizures. Our study identified the seizure-susceptible brain regions for unruptured bAVMs, which could be a plausible neuroimaging biomarker in predicting possible seizures.

关键词brain arteriovenous malformations lesion network mapping seizures voxel-based lesion-symptom mapping
DOI10.1002/jnr.25142
关键词[WOS]DEFAULT MODE NETWORK ; INTERNATIONAL-LEAGUE ; EPILEPSY ; ILAE ; ABNORMALITIES
收录类别SCI
语种英语
资助项目National key research and development program of China during the 13th Five-Year Plan Period[2016YFC1301803]
项目资助者National key research and development program of China during the 13th Five-Year Plan Period
WOS研究方向Neurosciences & Neurology
WOS类目Neurosciences
WOS记录号WOS:000879711500001
出版者WILEY
是否为代表性论文
七大方向——子方向分类脑网络分析
国重实验室规划方向分类认知机理与类脑学习
是否有论文关联数据集需要存交
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/50673
专题脑图谱与类脑智能实验室_脑网络组研究
通讯作者Liu, Bing; Cao, Yong
作者单位1.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, 119 South Fourth Ring Rd West, Beijing 100070, Peoples R China
2.China Natl Clin Res Ctr Neurol Dis, Beijing, Peoples R China
3.Chinese Acad Sci, Brainnetome Ctr, Beijing, Peoples R China
4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China
5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
6.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
7.Chinese Inst Brain Res, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Zhao, Shao-Zhi,Zhao, Yu-Xin,Liao, Xiao-Hua,et al. Unruptured brain arteriovenous malformations causing seizures localize to one common brain network[J]. JOURNAL OF NEUROSCIENCE RESEARCH,2022:11.
APA Zhao, Shao-Zhi.,Zhao, Yu-Xin.,Liao, Xiao-Hua.,Huo, Ran.,Li, Hao.,...&Cao, Yong.(2022).Unruptured brain arteriovenous malformations causing seizures localize to one common brain network.JOURNAL OF NEUROSCIENCE RESEARCH,11.
MLA Zhao, Shao-Zhi,et al."Unruptured brain arteriovenous malformations causing seizures localize to one common brain network".JOURNAL OF NEUROSCIENCE RESEARCH (2022):11.
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