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3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

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Mapping human brain charts cross-sectionally and longitudinally.

Maria A Di Biase^1,2,3, Ye Ella Tian¹, Richard A I Bethlehem⁴

¹Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3000, Australia.

Proceedings of the National Academy of Sciences of the United States of America

|May 8, 2023

Summary

Cross-sectional brain aging charts may underestimate actual brain changes. Longitudinal data reveal significant individual variations in brain aging, highlighting the need for direct measurement over time.

Keywords:

brain trajectory cross-sectional individual prediction longitudinal normative models

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Area of Science:

Neuroscience
Gerontology
Medical Imaging

Background:

Normative brain aging charts are increasingly established using large, age-diverse cohorts.
Cross-sectional studies provide a snapshot but may not capture true developmental trajectories.
Understanding the accuracy of cross-sectional data versus longitudinal data is crucial for brain aging research.

Purpose of the Study:

To compare age-related brain changes estimated from cross-sectional data with those measured longitudinally.
To assess the predictability of individual brain aging trajectories using population-level cross-sectional trends.
To identify factors influencing prediction errors in brain aging.

Main Methods:

Analysis of brain scans from large, age-diverse cohorts.
Comparison of cross-sectional brain aging charts with longitudinal brain measurements.
Statistical modeling to assess prediction errors and influencing factors.

Main Results:

Cross-sectional estimates of brain aging substantially underestimate actual longitudinal changes.
Individual brain aging trajectories exhibit significant variability and are poorly predicted by cross-sectional data.
Prediction errors show modest correlations with neuroimaging confounds and lifestyle factors.

Conclusions:

Longitudinal measurements are essential for accurately ascertaining brain development and aging trajectories.
Cross-sectional brain aging charts may not fully represent individual aging processes.
Further research should focus on longitudinal studies to capture the heterogeneity of brain aging.