Gait and balance impairments in patients with subcortical vascular cognitive impairment

Abstract Background Subcortical vascular cognitive impairment (SVCI) is a subtype of vascular cognitive impairment associated with extensive cerebral small vessel diseases (CSVDs) imaging biomarkers. The objectives of this work were to study the existence and patterns of gait and balance impairments in patients with SVCI due to CSVDs. Methods The study was conducted on 28 newly diagnosed SVCI patients and 22 healthy control subjects (HCS) submitted to the advanced activity of daily living scale (AADLs), Berg balance test (BBT), Montreal Cognitive Assessment Scale (MoCA), computerized dynamic posturography (CDP), vision-based 3-D skeletal data gait analysis, and brain MRI volumetric assessment. Results SVCI patients showed a significant decrease in AADLs as well as total cerebral white matter volume, total cerebral cortical volume, and mean cortical thickness which were proportional to the degree of cognitive impairment as measured by the MoCA score. Regarding CDP analysis, patients with SVCI revealed prolongation of cancelation time and spectral power for mid- and high frequencies in dynamic positions. In respect to gait analysis, there were significant decreases in mean stride length and mean cadence as well as increases in mean step width and left to right step length difference in the SVCI group compared to HCS while doing a single task. These variables get highly significant during the dual-task performance with a p value < 0.001 for each one. Conclusion Patients with SVCI suffer from gait and balance impairments that are proportional to the severity of their cognitive decline and greatly impair their ADLs.

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An ALE Meta-Analysis of Specific Functional MRI Studies on Subcortical Vascular Cognitive Impairment

Frontiers in Neurology ◽

10.3389/fneur.2021.649233 ◽

2021 ◽

Vol 12 ◽

Author(s):

Wenwen Xu ◽

Yu Song ◽

Shanshan Chen ◽

Chen Xue ◽

Guanjie Hu ◽

...

Keyword(s):

Cognitive Impairment ◽

Functional Connectivity ◽

Meta Analysis ◽

Vascular Cognitive Impairment ◽

Brain Regions ◽

Angular Gyrus ◽

Imaging Biomarkers ◽

Precentral Gyrus ◽

The Brain ◽

Subcortical Vascular Cognitive Impairment

Background: Subcortical vascular cognitive impairment (sVCI), caused by cerebral small vessel disease, accounts for the majority of vascular cognitive impairment, and is characterized by an insidious onset and impaired memory and executive function. If not recognized early, it inevitably develops into vascular dementia. Several quantitative studies have reported the consistent results of brain regions in sVCI patients that can be used to predict dementia conversion. The purpose of the study was to explore the exact abnormalities within the brain in sVCI patients by combining the coordinates reported in previous studies.Methods: The PubMed, Embase, and Web of Science databases were thoroughly searched to obtain neuroimaging articles on the amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity in sVCI patients. According to the activation likelihood estimation (ALE) algorithm, a meta-analysis based on coordinate and functional connectivity modeling was conducted.Results: The quantitative meta-analysis included 20 functional imaging studies on sVCI patients. Alterations in specific brain regions were mainly concentrated in the frontal lobes including the middle frontal gyrus, superior frontal gyrus, medial frontal gyrus, and precentral gyrus; parietal lobes including the precuneus, angular gyrus, postcentral gyrus, and inferior parietal lobule; occipital lobes including the lingual gyrus and cuneus; temporal lobes including the fusiform gyrus and middle temporal gyrus; and the limbic system including the cingulate gyrus. These specific brain regions belonged to important networks known as the default mode network, the executive control network, and the visual network.Conclusion: The present study determined specific abnormal brain regions in sVCI patients, and these brain regions with specific changes were found to belong to important brain functional networks. The findings objectively present the exact abnormalities within the brain, which help further understand the pathogenesis of sVCI and identify them as potential imaging biomarkers. The results may also provide a basis for new approaches to treatment.

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P2-140: Neural network of gait disturbances in patients with subcortical vascular cognitive impairment

Alzheimer s & Dementia ◽

10.1016/j.jalz.2015.06.678 ◽

2015 ◽

Vol 11 (7S_Part_11) ◽

pp. P539-P539

Author(s):

Yeo Jin Kim ◽

Hun Ki Kwon ◽

Hanna Cho ◽

Hee Jin Kim ◽

Hee Kyung Park ◽

...

Keyword(s):

Neural Network ◽

Cognitive Impairment ◽

Vascular Cognitive Impairment ◽

Gait Disturbances ◽

Subcortical Vascular Cognitive Impairment

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Abstract TP442: Periventricular Not Deep White Matter Hyperintensities Are Associated With Vascular Cognitive Impairment

Stroke ◽

10.1161/str.48.suppl_1.tp442 ◽

2017 ◽

Vol 48 (suppl_1) ◽

Author(s):

Yan Chen ◽

Renyuan Liu ◽

Shuwei Qiu ◽

Yun Xu

Keyword(s):

Regression Analysis ◽

Cognitive Impairment ◽

White Matter ◽

Linear Regression ◽

Cognitive Performance ◽

White Matter Hyperintensities ◽

Rating Scale ◽

Linear Regression Analysis ◽

Vascular Cognitive Impairment ◽

Cerebral White Matter

Introduction: Cerebral White matter hyperintensities(WMH) are frequent findings on MRI scan. They are well known to correlate with vascular cognitive impairment(VCI). However, controversies still remain about the relationship between WMH locations and cognitive function across studies. Hypothesis: Periventricular WMHs(PWH) rather than deep WMHs(DWH) are associated with cognitive decline in VCI. Methods: Fifty-nine subjects with WMHs on MRI were divided into three groups, normal control(NC), mild cognitive impairment(MCI) and vascular dementia(VaD), according to clinical manifestation and neuropsychological performance. WMH volumes were evaluated by Fazekas rating scale and segmental volumetric. Correlations between cognitive performance and WMH volumes were determined in virtue of Spearman correlation analysis. Receiver operator characteristic (ROC) curves were generated to define the classification cut-off value of WMH volumes for distinguishing VCI versus normal controls. Multiple linear regression analysis was used to predict cognitive performance with WMH volumes and locations after adjusting for sex ,age and education level. Results: Cognitive capacities were gradually declined from NC through MCI to VaD patients while WMH volumes and Fazekas scores altered oppositely. Both PWH and DWH volumes and Fazekas scores were correlated with cognitive performance, and moreover, WMH volumes were correlated with Fazekas scores. ROC analysis showed a cut-off value of PWH rather than DWH to distinguish VCI from NC(AUC=0.745 and 0.635, p =0.001 and 0.076, respectively). Linear regression analysis demonstrated that only PWH volumes were associated with cognitive performance( p < 0.001). Conclusion: Our study demonstrate that PWHs are independent predictors for vascular contribution in white matter lesions and suggest clinicians that PWH should be emphasized on evaluating vascular cognitive impairment related with white matter load.

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