Longitudinal Resting-State Functional Magnetic Resonance Imaging Study: A Seed-Based Connectivity Biomarker in Patients with Ischemic and Intracerebral Hemorrhage Stroke.

Brain connectivity(2022)

引用 0|浏览9
暂无评分
摘要
The primary aim of the research was to compare the impact of postischemic and hemorrhagic stroke on brain connectivity and recovery using resting-state functional magnetic resonance imaging. We serially imaged 20 stroke patients, 10 with ischemic stroke (IS) and 10 with intracerebral hemorrhage (ICH), at 1, 3, and 12 months (1M, 3M, and 12M) after ictus. Data from 10 healthy volunteers were obtained from a publically available imaging data set. All functional and structural images underwent standard processing for brain extraction, realignment, serial registration, unwrapping, and denoising using SPM12. A seed-based group analysis using CONN software was used to evaluate the default mode network and the sensorimotor network connections by applying bivariate correlation and hemodynamic response function weighting. In comparison with healthy controls, both IS and ICH exhibited disrupted interactions (decreased connectivity) between these two networks at 1M. Interactions then increased by 12M in each group. Temporally, each group exhibited a minimal increase in connectivity at 3M compared with 12M. Overall, the ICH patients exhibited a greater magnitude of connectivity disruption compared with IS patients, despite a significant intrasubject reduction in hematoma volume. We did not observe any significant correlation between change in connectivity and recovery as measured on the National Institutes of Health Stroke Scale (NIHSS) at any time point. These findings demonstrate that the largest changes in functional connectivity occur earlier (3M) rather than later (12M) and show subtle differences between IS and ICH during recovery and should be explored further in larger samples.
更多
查看译文
关键词
intracerebral hemorrhage,ischemic stroke,resting-state functional magnetic resonance imaging,serial neuroimaging study
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要