长期吸烟人群静息态脑网络异常的功能磁共振评价
Resting-state network evaluation of chronic smokers by functional magnetic resonance imaging
摘要目的 应用独立成分分析方法评价长期吸烟人群静息态脑网络功能连接异常.方法 2014年8月至2015年8月期间通过网络宣传招募45例长期吸烟者和34名年龄和教育程度相匹配的不吸烟志愿者,采用3.0T磁共振进行静息态下磁共振扫描,使用基于Matlab平台的SPM 8软件分析静息态脑网络的功能连接差异.结果 内侧视觉网络:右侧楔叶(t=4.17,P<0.05)与左侧距状区(t =3.08,P<0.05)功能连接减弱.外侧视觉网络:左侧枕上回功能连接增强减弱(f=3.42,P<0.05).枕极视觉网络:右侧枕中回与左侧枕中回功能连接减弱(=3.58,P<0.05).背侧注意网络:右侧枕上回功能连接增强(t =3.42,P<0.05).左额顶网络:左侧顶下小叶功能连接减弱(t=3.77,P<0.05).右额顶网络:右侧额上回功能连接增强(t=3.42,P<0.05).结论 长期吸烟人群存在多个静息态脑网络异常,并可导致多个脑区的连接异常.
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abstractsObjective To explore the neuromechanism of nicotine smoking,we use independent component analysis (ICA) of resting-state functional magnetic resonance imaging (fMRI) to investigate the differences of functional connectivity of resting-state networks (RSN) in chronic smokers.Methods Fortyfive chronic smokers and thirty-four age and gender matched normal nonsmoking controls experienced restingstate fMRI scanning in 3.0T MRI scanner.Differences of the function connection in each RSN between chronic smokers group and nonsmoking controls group were analyzed by SPM software which was based on Matlab platform.Results Compared with normal nonsmoking controls,changes of functional connectivity within each RSN in chronic smokers:(1) medial visual network:functional connectivity decreased in right cuneus (t =4.17,P < 0.05) and left calcarine (t =3.08,P < 0.05);(2) lateral visual network:decreased in left gyrus occipital superior (t =3.42,P < 0.05);(3) occipital pole visual network:decreased in right gyrus occipital medins and left gyrus occipital medius (t =3.58,P < 0.05);(4) dorsal attention network (DAN):increased in right gyrus occipital superior (t =3.42,P < 0.05);(5) left frontoparietal network:decreased in left inferior parietal lobe (t =3.77,P < 0.05);(6) right frontoparietal network:increased in right gyrus fiontalis medius (t =3.42,P < 0.05).Conclusion There are some RSNs changes of chronic smokers compared with normal nonsmoking controls,with multiple brain regions functional connectivity abnormalities.
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