Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy/Department of Neurosciences, San Camillo Forlanini Hospital, Rome, Italy.
Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy.
Mult Scler. 2018 Apr;24(5):653-662. doi: 10.1177/1352458517701313. Epub 2017 Mar 24.
To investigate the disease-altered structure-function relationship underlying the cognitive-postural interference (CPI) phenomenon in multiple sclerosis (MS).
We measured postural sway of 96 patients and 48 sex-/age-matched healthy controls by force platform in quiet standing (single-task (ST)) while performing the Stroop test (dual-task (DT)) to estimate the dual-task cost (DTC) of balance. In patient group, binary T2 and T1 lesion masks and their corresponding lesion volumes were obtained from magnetic resonance imaging (MRI) of brain. Normalized brain volume (NBV) was also estimated by SIENAX. Correlations between DTC and lesion location were determined by voxel-based lesion symptom mapping (VLSM) analyses.
Patients had greater DTC than controls ( p < 0.001). Among whole brain MRI metrics, only T1 lesion volume correlated with DTC ( r = -0.27; p < 0.01). However, VLSM analysis did not reveal any association with DTC using T1 lesion masks. By contrast, we found clusters of T2 lesions in distinct anatomical regions (anterior and superior corona radiata, bilaterally) to be correlated with DTC ( p < 0.01 false discovery rate (FDR)-corrected). A multivariable stepwise regression model confirmed findings from VLSM analysis. NBV did not contribute to fit the model.
Our findings suggest that the CPI phenomenon in MS can be explained by disconnection along specific areas implicated in task-switching abilities and divided attention.
探究多发性硬化症（MS）认知-姿势干扰（CPI）现象背后的疾病改变的结构-功能关系。
我们通过力台测量了 96 名患者和 48 名性别/年龄匹配的健康对照者在安静站立时的姿势摆动（单任务（ST）），同时进行 Stroop 测试（双任务（DT）），以估计平衡的双重任务成本（DTC）。在患者组中，我们从脑磁共振成像（MRI）中获得了二进制 T2 和 T1 病变掩模及其相应的病变体积。还通过 SIENAX 估计了归一化脑体积（NBV）。通过基于体素的病变症状映射（VLSM）分析确定 DTC 与病变位置之间的相关性。
患者的 DTC 大于对照组（p<0.001）。在全脑 MRI 指标中，只有 T1 病变体积与 DTC 相关（r=-0.27；p<0.01）。然而，VLSM 分析并未发现 T1 病变掩模与 DTC 之间存在任何关联。相比之下，我们发现 T2 病变簇在不同的解剖区域（双侧前和上冠状辐射区）与 DTC 相关（p<0.01 经 FDR 校正）。多元逐步回归模型证实了 VLSM 分析的结果。NBV 不能有助于拟合模型。
我们的研究结果表明，MS 中的 CPI 现象可以通过与任务转换能力和注意力分散相关的特定区域的中断来解释。
