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脑膜瘤与低级别胶质瘤基于小波变换运动功能网络动态连接的差异 被引量:1

Differences of dynamic connectivity of motor function network between meningioma and low-grade glioma based on wavelet transform
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摘要 目的观察脑膜瘤与低级别胶质瘤基于小波变换的运动功能网络动态连接的差异。方法选取脑膜瘤(脑膜瘤组)及低级别胶质瘤(胶质瘤组)患者各14例及正常对照者(对照组)14名,采用小波变换一致性(WTC)方法分析3组运动功能网络动态连接情况。结果基于双手运动任务刺激及广义线性模型分析确定3组运动功能网络节点分别为左右侧主要运动皮层激活区(LPMC、RPMC)及辅助运动皮层激活区(SMA)。在运动网络LPMC、RPMC、SMA感兴趣区(ROI)内,脑膜瘤组、胶质瘤组LPMC-SMA、RPMC-SMA、LPMC-RPMC的WTC均低于对照组(P均<0.05),胶质瘤组均低于脑膜瘤组(P均<0.05)。结论利用WTC方法能够敏感观察脑膜瘤与低级别胶质瘤运动功能网络连接的低频振荡改变。 Objective To observe the differences of dynamic connectivity in motor function networks between meningioma and low-grade glioma.Methods Totally 14 patients with meningioma(meningioma group),14 patients with low grade gliomas(gliomas group)and 14 healthy controls(control group)were enrolled.The wavelet transform coherence(WTC)was used to analyze the dynamic connectivity in motor function networks of 3 groups.Results The motor function networks nodes were determined by hands movement task stimulus and the generalized linear model analysis,which located at the left and right side of the primary motor cortex(LPMC and RPMC)and the supplementary motor area(SMA).The values of WTC in LPMC-SMA,RPMC-SMA and LPMC-RPMC in meningioma group and gliomas group were lower than those in control group,and in gliomas group were lower than those in meningioma group(all P<0.05).Conclusion Low frequency fluctuation alteration of connectivity in motor function networks in patients with meningioma and low grade gliomas can be sensitively detected using WTC.
作者 牛晨 任雨寒 刘翔 温鑫 王茂德 郭建新 张明 NIU Chen;REN Yuhan;LIU Xiang;WEN Xin;WANG Maode;GUO Jianxin;ZHANG Ming(Department of Medical Imaging,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;Department of Neurosurgery,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China)
出处 《中国医学影像技术》 CSCD 北大核心 2020年第6期813-817,共5页 Chinese Journal of Medical Imaging Technology
基金 陕西省重点研发计划项目(2018SF-113) 中央高校基本科研基金(1191320118)。
关键词 胶质瘤 脑膜瘤 磁共振成像 小波变换 动态连接 运动功能网络 glioma meningioma magnetic resonance imaging wavelet transformation dynamic connection motor function networks
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