摘要
目的 利用静息态功能磁共振成像(fMRI)数据探讨慢性单侧感音神经性耳聋(USNHL)患者全脑功能网络的改变情况.方法 收集2012年6月至2013年6月经东南大学附属中大医院耳鼻喉门诊接待或广告招募重度右侧USNHL患者19例及31例听力正常的志愿者的静息态磁共振BOLD数据,构建受试者的全脑功能网络,计算网络相关参数:全局效率(Eglobal)、局部效率(Elocal)、小世界属性(Cp、Lp、γ、λ、σ).比较组间参数差异,并将Eglobal、Lp与耳聋持续时间及严重程度进行偏相关分析.结果 在稀疏度阈值范围为0.1 ~0.2时,两组均符合小世界属性(σ>1);大部分阈值下耳聋组Lp、λ高于正常对照组,差异有统计学意义,Eglobal低于正常对照组,差异有统计学意义(P<0.05);而Cp、Elocal、γ、σ差异无统计学意义(P>0.05).Eglobal、Lp与耳聋持续时间及严重程度无相关性(P>0.05).结论 右侧USNHL患者脑功能网络虽仍具有小世界属性,但患者全脑功能网络的某些属性已发生改变,这些改变对于从大尺度脑网络角度研究USNHL病理机制具有重要意义.
Objective To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients.Methods In this study,we acquired resting-state BOLD-fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks.Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls.Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables.Results Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0.1-0.2 of sparsity.Compared to the controls,USNHL patients showed significant increase in characteristic path length and normalized characteristic path length,but significant decrease in global efficiency.Clustering coefficient,local efficiency and normalized clustering coefficient demonstrated no significant difference.Furthermore,USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss.Conclusion Our results indicated the altered topological properties of whole brain functional networks in USNHL patients,which may help us to understand pathophysiologic mechanism of USNHL patients.
出处
《中华医学杂志》
CAS
CSCD
北大核心
2015年第5期349-352,共4页
National Medical Journal of China
基金
国家自然科学基金面上项目(30970808)
关键词
听觉丧失
感音神经性
磁共振成像
功能网络
Hearing loss,sensorineural
Magnetic resonance imaging
Functional network