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Assessment of localized brain regions correlated with MMSE using VBM analysis of structural MRI in a Japanese sample
Yoichi Sawada1, Toru Satoh2, Hideaki Saba3
1Department of Contemporary Welfare, Faculty of Health and Welfare, Okayama Prefectural University, Japan.
Abstract:
The global aging population has led to a significant rise in dementia and cognitive decline, with Alzheimer's disease as the primary cause. Early detection of mild cognitive impairment (MCI), a prodromal stage of dementia, is critical for timely intervention. The Mini-Mental State Examination (MMSE) is commonly used for cognitive screening, yet its limitations-such as ceiling effects and educational biases-may hinder the early identification of subtle cognitive impairments. This cross-sectional study employed voxel-based morphometry (VBM) analysis of structural magnetic resonance imaging (MRI) to explore brain regions positively correlated with MMSE scores in a cohort of 510 participants. Significant gray matter volume (GMV) reductions were observed in the bilateral lateral frontal lobes, left medial frontal lobe, left hippocampus, left anterior cingulate cortex (ACC), and bilateral inferior temporal gyri in association with lower MMSE scores. Participants were classified into three groups-Normal Cognition (NC), MCI, and Dementia (D)-based on MMSE cutoff values. Compared to the NC group, the MCI group exhibited significant GMV reductions in the left hippocampus, left parahippocampal gyrus, left ACC, and right ventromedial prefrontal cortex (vmPFC). The D group showed further GMV reductions in the bilateral hippocampus and left inferior temporal gyrus compared to the MCI group. These findings highlight the clinical utility of VBM-based structural MRI in assessing localized brain atrophy associated with cognitive decline, supporting its potential role in early diagnosis and intervention for MCI. Further research integrating longitudinal studies and multimodal biomarkers is warranted to enhance diagnostic accuracy.
Insights
Early detection of cognitive decline is crucial. Voxel-based morphometry (VBM) of MRI scans reveals gray matter reductions in brain regions like the hippocampus and frontal lobes, aiding in identifying mild cognitive impairment (MCI).
Area of Science:
- Neuroscience
- Radiology
- Gerontology
Background:
- The aging global population faces increasing rates of dementia and cognitive decline, primarily driven by Alzheimer's disease.
- Early identification of mild cognitive impairment (MCI), a precursor to dementia, is vital for effective intervention.
- The Mini-Mental State Examination (MMSE) is a common screening tool, but its limitations may impede early detection of subtle cognitive changes.
Purpose of the Study:
- To investigate the relationship between brain gray matter volume (GMV) and cognitive function using voxel-based morphometry (VBM) on structural MRI.
- To identify specific brain regions associated with cognitive decline and differentiate between normal cognition, MCI, and dementia.
Main Methods:
- A cross-sectional study involving 510 participants.
- Voxel-based morphometry (VBM) analysis of structural magnetic resonance imaging (MRI) data.
- Classification of participants into Normal Cognition (NC), MCI, and Dementia (D) groups based on MMSE scores.
Main Results:
- Lower MMSE scores correlated with reduced GMV in the bilateral lateral frontal lobes, left medial frontal lobe, left hippocampus, left anterior cingulate cortex (ACC), and bilateral inferior temporal gyri.
- The MCI group showed significant GMV reductions in the left hippocampus, left parahippocampal gyrus, left ACC, and right ventromedial prefrontal cortex (vmPFC) compared to the NC group.
- The Dementia group exhibited further GMV reductions in the bilateral hippocampus and left inferior temporal gyrus compared to the MCI group.
Conclusions:
- VBM-based structural MRI is a valuable tool for assessing localized brain atrophy linked to cognitive decline.
- These findings support the potential of VBM-MRI in the early diagnosis and intervention strategies for MCI.
- Further longitudinal studies integrating multimodal biomarkers are recommended to improve diagnostic accuracy for cognitive impairment.
