Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
BrainNow Research Institute, Shenzhen, Guangdong Province, China.
Neuroimage Clin. 2019;22:101682. doi: 10.1016/j.nicl.2019.101682. Epub 2019 Jan 22.
A network-level investigation of the volumetric changes of subcortical stroke patients is still lacking. Here, we explored the alterations of structural covariance caused by subcortical stroke with automated brain volumetry. T1-weighed brain MRI scans were obtained from 63 normal controls (NC), 46 stroke patients with infarct in left internal capsule (CI_L), 33 stroke patients with infarct in right internal capsule (CI_R). We performed automatic anatomical segmentation of the T1-weighted brain images with AccuBrain. Volumetric structural covariance analyses were first performed within the basal ganglia structures that were both identified by voxel-based morphometry with AAL atlas and AccuBrain. Subsequently, we additionally included the infratentorial regions that were particularly quantified by AccuBrain for the structural covariance analyses and investigated the alterations of anatomical connections within these subcortical regions in CI_L and CI_R compared with NC. The association between the regional brain volumetry and motor function was also evaluated in stroke groups. There were significant and extensive volumetric differences in stroke patients. These significant regions were generally symmetric for CI_L and CI_R group depending on the side of stroke, involving both regions close to lesions and remote regions. The structural covariance analyses revealed the synergy volume alteration in subcortical regions both in CI_L and CI_R group. In addition, the alterations of volumetric structural covariance were more extensive in CI_L group than CI_R group. Moreover, we found that the subcortical regions with atrophy contributed to the deficits of motor function in CI_R group but not CI_L group, indicating a lesion-side effect of brain volumetric changes after stroke. These findings indicated that the chronic subcortical stroke patients have extensive disordered anatomical connections involving the whole-brain level network, and the connections patterns depend on the lesion-side.
目前仍缺乏针对皮质下卒中患者脑容积变化的网络水平研究。在此,我们利用自动化脑容量分析技术,探讨了皮质下卒中引起的结构协变改变。共纳入 63 名正常对照者(NC)、46 名左侧内囊梗死(CI_L)卒中患者和 33 名右侧内囊梗死(CI_R)卒中患者。我们采用 AccuBrain 对 T1 加权脑 MRI 扫描进行自动解剖分割。首先在基于体素形态测量学的 AAL 图谱和 AccuBrain 同时识别的基底节结构内进行容积结构协变分析。随后,我们还纳入了 AccuBrain 特别定量的小脑下区域进行结构协变分析,并比较了 CI_L 和 CI_R 与 NC 之间这些皮质下区域解剖连接的改变。还评估了卒中组中区域脑容量与运动功能之间的相关性。卒中患者的脑容量存在显著且广泛的差异。这些显著区域在 CI_L 和 CI_R 组中一般与卒中的侧别相对称,涉及到靠近病变的区域和远隔区域。结构协变分析显示,CI_L 和 CI_R 组的皮质下区域存在协同的容积改变。此外,CI_L 组的容积结构协变改变比 CI_R 组更为广泛。此外,我们发现,在 CI_R 组中,与萎缩相关的皮质下区域与运动功能缺陷有关,而在 CI_L 组中则没有,这表明卒中后脑容积变化存在病灶侧效应。这些发现表明,慢性皮质下卒中患者存在广泛的全脑水平网络的解剖连接紊乱,连接模式取决于病灶侧。