Chua Alicia S, Egorova Svetlana, Anderson Mark C, Polgar-Turcsanyi Mariann, Chitnis Tanuja, Weiner Howard L, Guttmann Charles R G, Bakshi Rohit, Healy Brian C
Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA.
Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Boston, MA, USA ; Department of Neurology, Harvard Medical School, Boston, MA, USA.
Neuroimage Clin. 2015 Jul 2;8:606-10. doi: 10.1016/j.nicl.2015.06.009. eCollection 2015.
Magnetic resonance imaging (MRI) of the brain provides important outcome measures in the longitudinal evaluation of disease activity and progression in MS subjects. Two common measures derived from brain MRI scans are the brain parenchymal fraction (BPF) and T2 hyperintense lesion volume (T2LV), and these measures are routinely assessed longitudinally in clinical trials and observational studies. When measuring each outcome longitudinally, observed changes may be potentially confounded by variability in MRI acquisition parameters between scans. In order to accurately model longitudinal change, the acquisition parameters should thus be considered in statistical models. In this paper, several models for including protocol as well as individual MRI acquisition parameters in linear mixed models were compared using a large dataset of 3453 longitudinal MRI scans from 1341 subjects enrolled in the CLIMB study, and model fit indices were compared across the models. The model that best explained the variance in BPF data was a random intercept and random slope with protocol specific residual variance along with the following fixed-effects: baseline age, baseline disease duration, protocol and study time. The model that best explained the variance in T2LV was a random intercept and random slope along with the following fixed-effects: baseline age, baseline disease duration, protocol and study time. In light of these findings, future studies pertaining to BPF and T2LV outcomes should carefully account for the protocol factors within longitudinal models to ensure that the disease trajectory of MS subjects can be assessed more accurately.
脑部磁共振成像(MRI)为纵向评估多发性硬化症(MS)患者的疾病活动和进展提供了重要的结果指标。从脑部MRI扫描中得出的两个常见指标是脑实质分数(BPF)和T2高信号病变体积(T2LV),并且这些指标在临床试验和观察性研究中会定期进行纵向评估。在纵向测量每个结果时,观察到的变化可能会因各次扫描之间MRI采集参数的变异性而受到潜在混淆。因此,为了准确地对纵向变化进行建模,统计模型中应考虑采集参数。在本文中,使用来自CLIMB研究的1341名受试者的3453次纵向MRI扫描的大型数据集,比较了几种将协议以及个体MRI采集参数纳入线性混合模型的模型,并比较了各模型的拟合指数。最能解释BPF数据方差的模型是具有协议特定残差方差的随机截距和随机斜率,以及以下固定效应:基线年龄、基线病程、协议和研究时间。最能解释T2LV方差的模型是随机截距和随机斜率,以及以下固定效应:基线年龄、基线病程、协议和研究时间。鉴于这些发现,未来有关BPF和T2LV结果的研究应在纵向模型中仔细考虑协议因素,以确保能更准确地评估MS患者的疾病轨迹。