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脑小血管病患者的认知损害:MRI总体负担与基于纤维束空间统计的弥散张量成像的比较 被引量:1

Cognitive impairment in patients with cerebral small vessel disease:comparison of MRI total burden and diffusion tensor tract-based spatial statistics
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摘要 目的比较MRI总体负担和弥散张量纤维束示踪空间统计分析(tract-based spatial statistics,TBSS)识别脑小血管病(cerebral small vessel disease,CSVD)患者认知损害的价值。方法连续纳入2018年1月至2019年6月期间南京医科大学附属苏州医院确诊的CSVD患者,分为认知损害组与认知正常组。完善头颅MRI检查,评估MRI总体负担,同时进行TBSS分析得到弥散参数存在组间差异的区域。应用多变量logistic回归分析确定认知损害的独立危险因素。通过受试者工作特征(receiver operating characteristic,ROC)曲线判断MRI总体负担和TBSS分析对CSVD患者认知损害的识别能力。结果共纳入71例CSVD患者,其中认知损害组41例(57.75%),认知正常组30例(42.25%)。2组之间脑白质高信号患者的构成比存在统计学差异,但MRI总体负担差异无统计学意义。在校正年龄、性别等混杂因素后,多变量logistic回归分析显示脑白质高信号为CSVD患者认知损害的独立危险因素(优势比3.459,95%可信区间1.196~10.007;P=0.022)。认知损害组胼胝体膝部、丘脑前辐射、上纵束、额枕束等白质区域的弥散参数与认知正常组差异有统计学意义(P均<0.05),且左侧丘脑前辐射各向异性分数(r=0.252,P=0.036)以及胼胝体膝部径向扩散系数(r=-0.246;P=0.042)与认知评分显著相关。ROC分析显示,MRI总体负担、左侧丘脑前辐射各向异性分数和胼胝体膝部径向扩散系数识别认知损害的曲线下面积分别为0.61、0.56和0.57。结论脑白质高信号为CSVD患者认知损害的独立危险因素。TBSS分析在CSVD患者认知损害的特异性识别方面可能优于MRI总体负担评估,并且部分弥散参数与整体认知状况存在一定相关性,有可能作为早期识别CSVD患者认知损害的影像学标志。 Objective To compare the value of MRI total burden and diffusion tensor tract-based spatial statistics(TBSS)for identifying cognitive impairment in patients with cerebral small vascular disease(CSVD).Methods Consecutive patients with CSVD diagnosed in Suzhou Hospital Affiliated to Nanjing Medical University from January 2018 to June 2019 were enrolled.They were divided into cognitive impairment group and cognitive normal group.The MRI overall burden was evaluated,and TBSS analysis was performed to obtain regions with differences in diffusion parameters between the two groups.Multivariate logistic regression analysis was used to determine the independent risk factors for cognitive impairment.The receiver operating characteristic(ROC)curve was used to identify the recognition ability of the MRI overall burden and TBSS analysis for cognitive impairment in patients with CSVD.Results A total of 71 patients with CSVD were enrolled,including 41(57.75%)in the cognitive impairment group and 30(42.25%)in the cognitive normal group.There was a statistically significant difference in the proportion of patients with white matter hyperintensities between the two groups,but the MRI overall burden was not statistically significant difference.After adjusting for the confounding factors such as age and gender,multivariate logistic regression analysis showed that white matter hyperintensities was an independent risk factor for cognitive impairment in patients with CSVD(odds ratio 3.459,95%confidence interval 1.196-10.007;P=0.022).Diffuse parameters of the white matter area,such as the genu of corpus callosum,anterior thalamic radiation,fasciculus longitudinalis superior,and frontal-occipital fasciculus in the cognitive impairment group were significantly different from those in the cognitive normal group(all P<0.05).The fractional anisotropy of left anterior thalamic radiation(r=0.252,P=0.036)and the radial diffusivity of the genu of corpus callosum(r=-0.246,P=0.042)were significantly correlated with cognitive scores.ROC analysis showed that the areas under the curve of the MRI total burden,the fractional anisotropy of left anterior thalamic radiation,and the radial diffusivity of the genu of corpus callosum for identifying cognitive impairment were 0.61,0.56 and 0.57,respectively.Conclusion White matter hyperintensities is an independent risk factor for cognitive impairment in patients with CSVD.TBSS analysis may be superior to MRI overall burden assessment in the specific recognition of cognitive impairment in patients with CSVD.Some diffuse parameters have a certain correlation with the overall cognitive status,and may be used as early imaging markers for cognitive impairment in patients with CSVD.
作者 李一帆 赵中 Li Yifan;Zhao Zhong(Department of Neurology,Suzhou Hospital Affiliated to Nanjing Medical University,Suzhou 215000,China)
出处 《国际脑血管病杂志》 2019年第10期736-742,共7页 International Journal of Cerebrovascular Diseases
关键词 脑小血管疾病 认知障碍 磁共振成像 弥散张量成像 白质 危险因素 Cerebral small vessel diseases Cognition disorders Magnetic resonance imaging Diffusion tensor imaging White matter Risk factors
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