Characteristics and clinical association of dynamic functional connectivity in patients with white matter hyperintensity and gait disturbance
10.19845/j.cnki.zfysjjbzz.2025.0195
- VernacularTitle:脑白质高信号伴步态障碍患者的动态功能连接特征及临床关联研究
- Author:
Chenglu MAO
1
;
Yun XU
1
Author Information
1. Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University， Nanjing 210008，China
- Publication Type:Journal Article
- Keywords:
White matter hyperintensity;
Gait disturbance;
Dynamic functional connectivity;
Cerebral small vessel disease
- From:
Journal of Apoplexy and Nervous Diseases
2025;42(12):1069-1076
- CountryChina
- Language:Chinese
-
Abstract:
Objective White matter hyperintensity（WMH） is the core imaging marker for cerebral small vessel disease， and gait disturbance induced by WMH is a major cause of functional disability in middle-aged and elderly populations. Existing studies mostly focus on the static association between WMH and gait disturbance， while time-varying characteristics are observed in the functional connectivity of brain networks. The dynamic functional connectivity（dFC） technique can capture the real-time interaction characteristics of brain networks， providing a new perspective for analyzing the neural mechanism of WMH-related gait disturbance. This study aims to investigate the neuroimaging mechanism of patients with WMH and gait disturbance using the dFC technique and clarify the association of dynamic brain network imbalance with motor function and cognitive function. Methods Subjects were recruited in Nanjing Drum Tower Hospital from 2023 to 2025， and after screening based on inclusion and exclusion criteria， 93 subjects were enrolled in the group of WMH with gait disturbance （WMH-GD group）， 86 subjects were enrolled in the group of WMH without gait disturbance （WMH-nGD group）， and 92 subjects were enrolled in the normal control group （NC group）. Background data collection， neuropsychological assessment， gait testing， and cranial magnetic resonance imaging （MRI） scanning were performed for all subjects. The DynamicBC toolbox was used to perform the dFC analysis and extract the dynamic indicators including fractional windows（F）， mean dwell time （MDT）， number of transitions（NT）， and transition probability （TP）； network-based statistics（NBS） were used to identify differential connectivity between brain regions across groups； the correlation analysis was used to investigate the correlation between dynamic indicators and clinical parameters. Results The cluster analysis identified two brain functional connectivity states， i.e.， State Ⅰ （sparse and weak connectivity， accounting for 61.29%） and State Ⅱ （dense and strong connectivity， accounting for 38.71%）. Inter-group comparisons showed that compared with the WMH-nGD group， the WMH-GD group had significantly higher F value （72.48% vs 57.38%， P<0.05） and MDT （95.47 windows vs 54.46 windows， P<0.05） of State Ⅰ and a significantly lower value of NT （2.44 times vs 3.83 times）， as well as a significantly lower value of TP from State Ⅱ to State Ⅰ （TP Ⅱ→Ⅰ： 2.61% vs 5.84%， P<0.05） and a significantly higher value of TP from State Ⅱ to State Ⅱ （TP Ⅱ→Ⅱ：97.39% vs 94.16%， P<0.05）. The NBS analysis showed that compared with the WMH-nGD group， the WMH-GD group had a significant reduction in inter-regional connectivity between the occipital lobe， the parietal lobe， and the frontal lobe in State Ⅰ and a significant increase in connectivity within subcortical brain regions and between the limbic lobe and the subcortical region. The correlation analysis showed that in the WMH-GD group， Mini-Mental State Examination score was negatively correlated with MDT of State Ⅰ and TP Ⅱ→Ⅱ and was positively correlated with TP Ⅱ→Ⅰ and NT， and gait speed was positively correlated with NT. Conclusion Dynamic brain network imbalance is observed in patients with WMH and gait disturbance， which manifests as rigidity of the sparse and weak connectivity state， a reduction in transition flexibility， and reorganization of cortex-subcortex connectivity. These abnormalities are closely associated with cognitive and gait functions， suggesting that disruption of brain network metastability may be one of the core neural mechanisms underlying WMH-related gait disturbance.
- Full text:2026012215403044271脑白质高信号伴步态障碍患者的动态功能连接特征及临床关联研究.pdf
