多发性硬化症中的运动网络效率与残疾状况
Motor network efficiency and disability in multiple sclerosis.
作者信息
Pardini Matteo, Yaldizli Özgür, Sethi Varun, Muhlert Nils, Liu Zheng, Samson Rebecca S, Altmann Daniel R, Ron Maria A, Wheeler-Kingshott Claudia A M, Miller David H, Chard Declan T
机构信息
From the NMR Research Unit (M.P., Ö.Y., V.S., N.M., Z.L., R.S.S., D.R.A., M.A.R., C.A.M.W.-K., D.H.M., D.T.C.), Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Queen Square, London, UK; the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (M.P.), University of Genoa, Italy; the Department of Neurology (Ö.Y.), University Hospital Basel, Switzerland; the Department of Psychology (N.M.), Cardiff University, UK; the Department of Neurology (Z.L.), Xuanwu Hospital of Capital Medical University, Beijing, China; the Medical Statistics Department (D.R.A.), London School of Hygiene and Tropical Medicine, UK; and the National Institute for Health Research (NIHR) (D.T.C.), University College London Hospitals (UCLH) Biomedical Research Centre, UK.
出版信息
Neurology. 2015 Sep 29;85(13):1115-22. doi: 10.1212/WNL.0000000000001970. Epub 2015 Aug 28.
OBJECTIVE
To develop a composite MRI-based measure of motor network integrity, and determine if it explains disability better than conventional MRI measures in patients with multiple sclerosis (MS).
METHODS
Tract density imaging and constrained spherical deconvolution tractography were used to identify motor network connections in 22 controls. Fractional anisotropy (FA), magnetization transfer ratio (MTR), and normalized volume were computed in each tract in 71 people with relapse onset MS. Principal component analysis was used to distill the FA, MTR, and tract volume data into a single metric for each tract, which in turn was used to compute a composite measure of motor network efficiency (composite NE) using graph theory. Associations were investigated between the Expanded Disability Status Scale (EDSS) and the following MRI measures: composite motor NE, NE calculated using FA alone, FA averaged in the combined motor network tracts, brain T2 lesion volume, brain parenchymal fraction, normal-appearing white matter MTR, and cervical cord cross-sectional area.
RESULTS
In univariable analysis, composite motor NE explained 58% of the variation in EDSS in the whole MS group, more than twice that of the other MRI measures investigated. In a multivariable regression model, only composite NE and disease duration were independently associated with EDSS.
CONCLUSIONS
A composite MRI measure of motor NE was able to predict disability substantially better than conventional non-network-based MRI measures.
目的
开发一种基于磁共振成像（MRI）的运动网络完整性综合测量方法，并确定在多发性硬化症（MS）患者中，该方法是否比传统MRI测量方法能更好地解释残疾情况。
方法
采用纤维束密度成像和约束球面反卷积纤维束成像技术，在22名对照者中识别运动网络连接。对71例复发型MS患者的每条纤维束计算分数各向异性（FA）、磁化传递率（MTR）和标准化体积。主成分分析用于将FA、MTR和纤维束体积数据提炼为每条纤维束的单一指标，进而使用图论计算运动网络效率的综合测量值（综合NE）。研究扩展残疾状态量表（EDSS）与以下MRI测量指标之间的相关性：综合运动NE、仅使用FA计算的NE、联合运动网络纤维束中的平均FA、脑T2病变体积、脑实质分数、正常外观白质MTR和颈髓横截面积。
结果
在单变量分析中，综合运动NE解释了整个MS组中EDSS变异的58%，是所研究的其他MRI测量指标解释变异的两倍多。在多变量回归模型中，只有综合NE和病程与EDSS独立相关。
结论
运动NE的MRI综合测量方法在预测残疾方面比传统的基于非网络的MRI测量方法显著更好。
Zotero 插件