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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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BundleAGE: Predicting White Matter Age using Along-Tract Microstructural Profiles from Diffusion MRI.

Yixue Feng¹, Julio E Villalón-Reina¹, Talia M Nir¹

¹Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States.

Biorxiv : the Preprint Server for Biology

|September 4, 2024

Summary

This summary is machine-generated.

This study introduces Bundle Age Gap Estimation (BundleAGE), a new biomarker using along-tract brain microstructure to estimate biological brain age. BundleAGE reveals differential aging across white matter, aiding neurodegenerative disease risk assessment.

Keywords:

BrainAGE diffusion MRI diffusion tensor imaging machine learning tractometry

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Area of Science:

Neuroimaging
Biomarkers
Aging Research

Background:

Brain Age Gap Estimation (BrainAGE) uses brain scans to estimate biological brain age versus chronological age.
BrainAGE is a potential marker for accelerated aging and neurodegenerative disease risk.
Previous studies primarily used voxel-based or functional MRI, not along-tract microstructure.

Purpose of the Study:

To evaluate along-tract microstructural profiles from diffusion tensor imaging for BrainAGE computation.
To develop a novel biomarker, Bundle Age Gap Estimation (BundleAGE), for assessing brain aging.

Main Methods:

Machine learning models were trained to predict chronological age using along-tract microstructural data from diffusion tensor imaging.
Analysis focused on differential aging patterns within specific white matter bundles.

Main Results:

The study successfully trained models to predict age from along-tract microstructural profiles.
Differential aging patterns were observed across various white matter bundles and microstructural measures.
The developed BundleAGE biomarker demonstrated potential for quantifying aging and neurodegenerative disease risk.

Conclusions:

Along-tract microstructural analysis is a viable method for BrainAGE computation.
BundleAGE offers a novel, detailed approach to quantifying brain aging.
BundleAGE shows promise as a biomarker for neurodegenerative disease risk and aging processes.