Brain structural volume changes and gait disorders in patients with cerebral small vessel disease: a principal component and logistic regression analysis

AIMS: To investigate the relationship between the relative volume changes of brain structures and gait disorders in patients with cerebral small vessel disease (CSVD), and to identify key brain volume indicators that influence gait disorders (GD) through principal component analysis (PCA) combined with logistic regression analysis. METHODS: A total of 90 patients with CSVD were included and divided into two groups based on their Timed Up and Go Test (TUG) results: the CSVD gait disorder group (GD group, N = 50, TUG ≥ 11.5 s) and the CSVD non-gait disorder group (NGD group, N = 40, TUG < 11.5 s). Brain structural volumes and associated imaging markers were calculated using a 3.0T superconducting magnetic resonance imaging (MRI) system combined with an intelligent image analysis platform. The relative volume data of brain structures were subjected to PCA for dimensionality reduction. Regression analysis of the principal components was performed to identify key predictive indicators for gait disorders. RESULTS: Principal components 2 and 3 exhibited significant predictive power for gait disorders. Component 2 primarily represented cerebrospinal fluid, the temporal lobe, and the frontal lobe, while Component 3 primarily represented the third ventricle, lateral ventricle, and corpus callosum. Analysis of component loadings indicated that the expansion of cerebrospinal fluid-related structures was positively correlated with the severity of gait disorders, while atrophy of brain tissue structures showed a negative correlation. No significant difference was observed in the total CSVD burden score between the GD and NGD groups. CONCLUSION: The enlargement of the cerebrospinal fluid spaces and the ventricular system are key factors contributing to gait disorders in CSVD patients. Additionally, atrophy in cortical areas such as the temporal and frontal lobes, as well as the corpus callosum, plays a predictive role in the severity of gait disturbances. The total CSVD burden score does not adequately reflect the degree of gait impairment and requires further refinement for clinical application.

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Journal
BMC Medical Imaging
Published
2026-05-22
DOI
https://doi.org/10.1186/s12880-026-02428-7
Primary Topic
Traumatic Brain Injury and Neurovascular Disturbances
Type
article
Field-Weighted Citation Impact
0.00

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article

Brain structural volume changes and gait disorders in patients with cerebral small vessel disease: a principal component and logistic regression analysis

Bing-Wei Zhang, Bingbing Gao, Yan-wei Miao, Jia-Jing Tian et al.
BMC Medical Imaging
Traumatic Brain Injury and Neurovascular Disturbances
article

Brain structural volume changes and gait disorders in patients with cerebral small vessel disease: a principal component and logistic regression analysis

Bing-Wei Zhang, Bingbing Gao, Yan-wei Miao, Jia-Jing Tian, Hua-Wei Chen, Xiao-Ying Zhao, Hong-Bo Wang
article en

Abstract

AIMS: To investigate the relationship between the relative volume changes of brain structures and gait disorders in patients with cerebral small vessel disease (CSVD), and to identify key brain volume indicators that influence gait disorders (GD) through principal component analysis (PCA) combined with logistic regression analysis. METHODS: A total of 90 patients with CSVD were included and divided into two groups based on their Timed Up and Go Test (TUG) results: the CSVD gait disorder group (GD group, N = 50, TUG ≥ 11.5 s) and the CSVD non-gait disorder group (NGD group, N = 40, TUG < 11.5 s). Brain structural volumes and associated imaging markers were calculated using a 3.0T superconducting magnetic resonance imaging (MRI) system combined with an intelligent image analysis platform. The relative volume data of brain structures were subjected to PCA for dimensionality reduction. Regression analysis of the principal components was performed to identify key predictive indicators for gait disorders. RESULTS: Principal components 2 and 3 exhibited significant predictive power for gait disorders. Component 2 primarily represented cerebrospinal fluid, the temporal lobe, and the frontal lobe, while Component 3 primarily represented the third ventricle, lateral ventricle, and corpus callosum. Analysis of component loadings indicated that the expansion of cerebrospinal fluid-related structures was positively correlated with the severity of gait disorders, while atrophy of brain tissue structures showed a negative correlation. No significant difference was observed in the total CSVD burden score between the GD and NGD groups. CONCLUSION: The enlargement of the cerebrospinal fluid spaces and the ventricular system are key factors contributing to gait disorders in CSVD patients. Additionally, atrophy in cortical areas such as the temporal and frontal lobes, as well as the corpus callosum, plays a predictive role in the severity of gait disturbances. The total CSVD burden score does not adequately reflect the degree of gait impairment and requires further refinement for clinical application.

BMC Medical Imaging
Dalian Medical University (CN), Dalian University of Technology (CN), First Affiliated Hospital of Dalian Medical University (CN)
Department of Science and Technology of Liaoning Province
Openalex Percentile: Top 5%
Traumatic Brain Injury and Neurovascular Disturbances
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