Xie Bingyong, Ni Haoyu, Wang Ying, Yao Jiyuan, Xu Zhibin, Zhu Kun, Bian Sicheng, Song Peiwen, Wu Yuanyuan, Yu Yongqiang, Dong Fulong
Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
World Neurosurg. 2024 Nov;191:e505-e519. doi: 10.1016/j.wneu.2024.08.160. Epub 2024 Sep 5.
Dynamic functional network connectivity (dFNC) captures temporal variations in functional connectivity during magnetic resonance imaging acquisition. However, the neural mechanisms driving dFNC alterations in the brain networks of patients with acute incomplete cervical cord injury (AICCI) remain unclear.
This study included 16 AICCI patients and 16 healthy controls. Initially, independent component analysis was employed to extract whole-brain independent components from resting-state functional magnetic resonance imaging data. Subsequently, a sliding time window approach, combined with k-means clustering, was used to estimate dFNC states for each participant. Finally, a correlation analysis was conducted to examine the association between sensorimotor dysfunction scores in AICCI patients and the temporal characteristics of dFNC.
Independent component analysis was employed to extract 26 whole-brain independent components. Subsequent dynamic analysis identified 4 distinct connectivity states across the entire cohort. Notably, AICCI patients demonstrated a significant preference for State 3 compared to healthy controls, as evidenced by a higher frequency and longer duration spent in this state. Conversely, State 4 exhibited a reduced frequency and shorter dwell time in AICCI patients. Moreover, correlation analysis revealed a positive association between sensorimotor dysfunction and both the mean dwell time and the fraction of time spent in State 3.
Patients with AICCI demonstrate abnormal connectivity within dFNC states, and the temporal characteristics of dFNC are associated with sensorimotor dysfunction scores. These findings highlight the potential of dFNC as a sensitive biomarker for detecting network functional changes in AICCI patients, providing valuable insights into the dynamic alterations in brain connectivity related to sensorimotor dysfunction in this population.
动态功能网络连接性(dFNC)可捕捉磁共振成像采集过程中功能连接性的时间变化。然而,急性不完全颈髓损伤(AICCI)患者脑网络中驱动dFNC改变的神经机制仍不清楚。
本研究纳入了16例AICCI患者和16名健康对照者。首先,采用独立成分分析从静息态功能磁共振成像数据中提取全脑独立成分。随后,采用滑动时间窗方法结合k均值聚类来估计每位参与者的dFNC状态。最后,进行相关性分析以检验AICCI患者的感觉运动功能障碍评分与dFNC时间特征之间的关联。
采用独立成分分析提取了26个全脑独立成分。随后的动态分析在整个队列中确定了4种不同的连接状态。值得注意的是,与健康对照者相比,AICCI患者对状态3有明显偏好,表现为处于该状态的频率更高、持续时间更长。相反,状态4在AICCI患者中的出现频率降低且停留时间缩短。此外,相关性分析显示感觉运动功能障碍与状态3的平均停留时间和所花费时间的比例均呈正相关。
AICCI患者在dFNC状态内表现出异常连接,且dFNC的时间特征与感觉运动功能障碍评分相关。这些发现凸显了dFNC作为检测AICCI患者网络功能变化的敏感生物标志物的潜力,为该人群中与感觉运动功能障碍相关的脑连接动态改变提供了有价值的见解。