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Automated quantification of small vessel disease brain changes on MRI predicts cognitive and functional decline
- Publication Year :
- 2019
- Publisher :
- Cold Spring Harbor Laboratory, 2019.
-
Abstract
- Background and purposeCerebral small vessel disease (SVD) is characterized by a wide range of focal and global brain changes. We used automated MRI segmentation to quantify multiple types of SVD brain changes and examined their individual and combined predictive value on cognitive and functional abilities.MethodsMRI scans of 560 subjects of the Leukoaraiosis and Disability Study (LADIS) were analyzed using automated atlas- and convolutional neural network-based segmentation methods yielding volumetric measures of white matter hyperintensities (WMH), lacunes, cortical infarcts, enlarged perivascular spaces and regional brain atrophy. The subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years.ResultsThe strongest predictors of cognitive performance and functional outcome over time were total volumes of WMH, grey matter (GM) and hippocampi (pConclusionsGlobal burden of SVD-related brain changes as quantified by automated image segmentation is a powerful predictor of long-term cognitive decline and functional disability. A combined measure of WMH, lacunar, GM and hippocampal volumes could be used as an imaging identification model of vascular cognitive impairment.
- Subjects :
- medicine.medical_specialty
business.industry
Neuropsychology
Leukoaraiosis
Cognition
030204 cardiovascular system & hematology
Grey matter
Executive functions
Hyperintensity
03 medical and health sciences
0302 clinical medicine
medicine.anatomical_structure
Internal medicine
medicine
Cardiology
Effects of sleep deprivation on cognitive performance
Cognitive decline
business
030217 neurology & neurosurgery
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....dc5c6c7ee90ea7fc5115fbd0013adf2e