Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Academic Center for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze and Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 19, Eindhoven, the Netherlands.
Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.
Neuroimage Clin. 2018;20:861-867. doi: 10.1016/j.nicl.2018.09.023. Epub 2018 Sep 26.
The brains of patients with epilepsy may exhibit various morphological abnormalities, which are often not directly visible on structural MR images, as they may be focally subtle or related to a more large-scale inconspicuous disorganization of brain structures. To explore the relation between structural brain organization and epilepsy characteristics, including severity and cognitive co-morbidity, we determined structural covariance networks (SCNs). SCNs represent interregional correlations of morphologic measures, for instance in terms of cortical thickness, between various large-scale distributed brain regions.
Thirty-eight patients with focal seizures of all subtypes and 21 healthy controls underwent structural MRI, neurological, and IQ assessment. Cortical thickness was derived from the structural MRIs using FreeSurfer. Subsequently, SCNs were constructed on a group-level based on correlations of the cortical thicknesses between various brain regions. Individual SCNs for the epilepsy patients were extracted by adding the respective patient to the control group prior to the SCN construction (i.e. add-one-patient approach). Calculated network measures, i.e. path length, clustering coefficient and betweenness centrality were correlated with characteristics related to the severity of epilepsy, including seizure history and age at onset of epilepsy, and cognitive performance.
Stronger clustering in the individual SCN was associated with a higher number of focal to bilateral tonic-clonic seizures during life time, a younger age at onset, and lower cognitive performance. The path length of the individual SCN was not related to the severity of epilepsy or cognitive performance. Higher betweenness centrality of the left cuneus and lower betweenness centrality of the right rostral middle frontal gyrus were associated with increased drug load and younger age at onset, respectively.
These results indicate that the correlations between interregional variations of cortical thickness reflect disease characteristics or responses to the disease and deficits in patients with epilepsy with focal seizures.
癫痫患者的大脑可能表现出各种形态异常,这些异常在结构磁共振成像(MRI)上通常无法直接看到,因为它们可能是局部细微的,或者与大脑结构更广泛的不明显的紊乱有关。为了探讨结构脑组织与癫痫特征之间的关系,包括严重程度和认知合并症,我们确定了结构协变网络(SCN)。SCN 代表了不同大尺度分布脑区之间形态学测量值(例如皮质厚度)的区域间相关性。
38 名局灶性发作的癫痫患者(包括所有亚型)和 21 名健康对照者接受了结构 MRI、神经学和智商评估。皮质厚度使用 FreeSurfer 从结构 MRI 中得出。随后,基于不同脑区皮质厚度之间的相关性,在组水平上构建 SCN。通过将每位患者添加到对照组之前构建 SCN(即加一患者方法)来提取癫痫患者的个体 SCN。计算网络度量,如路径长度、聚类系数和中间中心性,与与癫痫严重程度相关的特征(包括发作史和癫痫发作的发病年龄)和认知表现相关。
个体 SCN 中的聚类系数越强,一生中双侧强直阵挛发作的次数越多,发病年龄越小,认知表现越差。个体 SCN 的路径长度与癫痫的严重程度或认知表现无关。左侧楔前叶的中间中心性较高和右侧额中回的中间中心性较低分别与药物负荷增加和发病年龄较小有关。
这些结果表明,皮质厚度区域间变化的相关性反映了疾病特征或对疾病的反应以及局灶性癫痫患者的缺陷。