Related Experiment Video
Updated: May 3, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on
Weiqi Liao1, Xiaojing Long1, Chunxiang Jiang1
1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Ave., Shenzhen, Guangdong Province 518055, China.
Rationale And Objectives:
Differentiating mild cognitive impairment (MCI) and Alzheimer Disease (AD) from healthy aging remains challenging. This study aimed to explore the cerebral structural alterations of subjects with MCI or AD as compared to healthy elderly based on the individual and collective effects of cerebral morphologic indices using univariate and multivariate analyses.
Materials And Methods:
T1-weighted images (T1WIs) were retrieved from Alzheimer Disease Neuroimaging Initiative database for 116 subjects who were categorized into groups of healthy aging, MCI, and AD. Analysis of covariance (ANCOVA) and multivariate analysis of covariance (MANCOVA) were performed to explore the intergroup morphologic alterations indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume with age and sex controlled as covariates, in 34 parcellated gyri regions of interest (ROIs) for both cerebral hemispheres based on the T1WI. Statistical parameters were mapped on the anatomic images to facilitate visual inspection.
Results:
Global rather than region-specific structural alterations were revealed in groups of MCI and AD relative to healthy elderly using MANCOVA. ANCOVA revealed that the cortical thickness decreased more prominently in entorhinal, temporal, and cingulate cortices and was positively correlated with patients' cognitive performance in AD group but not in MCI. The temporal lobe features marked atrophy of white matter during the disease dynamics. Significant intercorrelations were observed among the morphologic indices with univariate analysis for given ROIs.
Conclusions:
Significant global structural alterations were identified in MCI and AD based on MANCOVA model with improved sensitivity. The intercorrelation among the morphologic indices may dampen the use of individual morphological parameter in featuring cerebral structural alterations. Decrease in cortical thickness is not reflective of the cognitive performance at the early stage of AD.
Insights
Alzheimer
Area of Science:
- Neuroimaging
- Neurology
- Gerontology
Background:
- Distinguishing mild cognitive impairment (MCI) and Alzheimer Disease (AD) from healthy aging is crucial for early intervention.
- Cerebral structural changes are key indicators of neurodegenerative diseases.
Purpose of the Study:
- To investigate global and regional cerebral structural alterations in MCI and AD compared to healthy aging.
- To explore the relationship between morphologic indices and cognitive performance.
Main Methods:
- Utilized T1-weighted MRI from the Alzheimer Disease Neuroimaging Initiative database (116 subjects).
- Employed univariate (ANCOVA) and multivariate (MANCOVA) analyses on cortical thickness, surface area, curvature, and white matter volume.
- Controlled for age and sex in 34 brain regions of interest.
Main Results:
- Multivariate analysis revealed global structural alterations in MCI and AD groups.
- Cortical thickness reduction was prominent in entorhinal, temporal, and cingulate cortices, correlating with cognitive performance in AD.
- White matter atrophy was observed in the temporal lobe, and significant intercorrelations existed among morphologic indices.
Conclusions:
- MANCOVA identified significant global structural changes in MCI and AD, enhancing diagnostic sensitivity.
- Intercorrelations among morphologic indices may limit the utility of single parameters.
- Cortical thickness decrease does not consistently reflect cognitive status in early Alzheimer Disease.
Related Concept Videos
Dementia l: Introduction
Alzheimer Disease l: Introduction
Alzheimer Disease ll: Pathophysiology
Alzheimer's Disease: Overview
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
Dementia
The progression of dementia is generally gradual....

