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A multimodal Neuroimaging-Based risk score for mild cognitive impairment.
Elaheh Zendehrouh1, Mohammad S E Sendi2, Anees Abrol3
1Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, United States; Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, United States.
A new Brain-wide Risk Score (BRS) using neuroimaging effectively identifies mild cognitive impairment (MCI) risk. This multimodal approach aids in early Alzheimer's disease detection and risk stratification.
Area of Science:
- Neuroimaging
- Neurology
- Biomarkers
Background:
- Alzheimer's disease (AD) is a leading cause of age-related dementia.
- Genetic and neuroimaging factors are known AD risks.
- A neuroimaging-based metric for AD risk assessment is needed.
Purpose of the Study:
- Introduce the Brain-wide Risk Score (BRS), a novel neuroimaging metric.
- Assess the risk of mild cognitive impairment (MCI), a precursor to AD.
- Utilize multimodal neuroimaging data for risk assessment.
Main Methods:
- Utilized OASIS-3 and UK Biobank cohorts (N=1,389 and N=37,780).
- Extracted gray matter (GM) from structural MRI (sMRI) and functional network connectivity (FNC) from resting-state fMRI.
- Calculated BRS by comparing individual features to control (CN) and MCI group differences.
Main Results:
- Unimodal analysis showed sMRI outperformed fMRI in differentiation.
- The multimodal BRS identified distinct high and low MCI risk groups.
- AD patients exhibited FNC and GM patterns similar to the high-risk group.
Conclusions:
- The BRS effectively differentiates MCI from CN individuals.
- Validated BRS using the ADNI cohort (N=729).
- BRS shows potential for early Alzheimer's disease detection.
