Unruptured brain arteriovenous malformations causing seizures localize to one common brain network | |
Zhao, Shao-Zhi6,7; Zhao, Yu-Xin3,4,5; Liao, Xiao-Hua3,4,5; Huo, Ran6,7; Li, Hao6,7; Jiao, Yu-Ming6,7; Weng, Jian-Cong6,7; Wang, Jie6,7; Liu, Bing1,2; Cao, Yong6,7 | |
刊名 | JOURNAL OF NEUROSCIENCE RESEARCH |
2022-11-07 | |
页码 | 11 |
关键词 | brain arteriovenous malformations lesion network mapping seizures voxel-based lesion-symptom mapping |
ISSN号 | 0360-4012 |
DOI | 10.1002/jnr.25142 |
通讯作者 | Liu, Bing(bing.liu@bnu.edu.cn) ; Cao, Yong(caoyong@bjtth.org) |
英文摘要 | 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. |
资助项目 | National key research and development program of China during the 13th Five-Year Plan Period[2016YFC1301803] |
WOS关键词 | DEFAULT MODE NETWORK ; INTERNATIONAL-LEAGUE ; EPILEPSY ; ILAE ; ABNORMALITIES |
WOS研究方向 | Neurosciences & Neurology |
语种 | 英语 |
出版者 | WILEY |
WOS记录号 | WOS:000879711500001 |
资助机构 | National key research and development program of China during the 13th Five-Year Plan Period |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/50672] |
专题 | 自动化研究所_脑网络组研究中心 |
通讯作者 | Liu, Bing; Cao, Yong |
作者单位 | 1.Chinese Inst Brain Res, Beijing, Peoples R China 2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China 5.Chinese Acad Sci, Brainnetome Ctr, Beijing, Peoples R China 6.China Natl Clin Res Ctr Neurol Dis, Beijing, Peoples R China 7.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, 119 South Fourth Ring Rd West, Beijing 100070, 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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