Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases

Resting-state functional magnetic resonance imaging in patients with leukoaraiosis-associated subcortical vascular cognitive impairment: a cross-sectional study.

First author:Yu Chen

Corresponding author:Yumei Zhang

Subcortical vascular cognitive impairment Leukoar

essential_information

  • Person in charge:Yu Chen
  • Data Sources: OTHERS
  • Number of papers:OTHERS20190423
  • Published time:2016-06-01

2016-06-01

Published articles

Journal:Neurological Research

Publication type: Research Article

IF(IF): 2.448

PMID: 27320245 Link To Pubmed Full text Download

Background And Purpose

Method

All subjects (n = 58) were divided into two groups based on their clinical diagnosis: a LA-associated SVCI group (n = 31, 14 males) and a control group (n = 27, 14 males). Demographic information and resting-state functional MRI (rs-fMRI) data were obtained. These subjects were assessed using the Hamilton Anxiety Depression Scale, Clinical Dementia Rating, Mini Mental State Exam, and Montreal Cognitive Assessment. Experimental data and confounding factors were described with a General Liner Model. Independent components of fMRI data were analyzed with an fMRI toolbox.

Conclusion

The present study provides neuroimaging evidence for the recognition of LA-associated SVCI. Moreover, the differences in the functional alterations of the resting-state DMN might be a distinguishing featurebetween SVCI and amnestic mild cognitive impairment patients.

Main results

All subjects (n = 58) were divided into two groups based on their clinical diagnosis: a LA-associated SVCI group (n = 31, 14 males) and a control group (n = 27, 14 males). Demographic information and resting-state functional MRI (rs-fMRI) data were obtained. These subjects were assessed using the Hamilton Anxiety Depression Scale, Clinical Dementia Rating, Mini Mental State Exam, and Montreal Cognitive Assessment. Experimental data and confounding factors were described with a General Liner Model. Independent components of fMRI data were analyzed with an fMRI toolbox.