Background/Objectives: Age-related structural changes in the human brain provide essential insights into cognitive aging and the onset of neurodegenerative diseases. This study aimed to comprehensively characterize age-related volumetric changes across multiple brain regions in a large, diverse, cognitively healthy cohort spanning adulthood (ages 21–90), integrating Korean, Information eXtraction from Images (IXI), and Alzheimer’s Disease Neuroimaging Initiative (ADNI) MRI datasets of cognitively healthy participants to characterize normative volumetric changes across adulthood using demographically diverse datasets. Methods: High resolution 3T T1-weighted MRI images from three distinct cohorts (totaling 1833 subjects) were processed through an optimized neuroimaging pipeline, combining advanced preprocessing with neural network-based segmentation. Volumetric data for 95 brain structures were segmented and analyzed across seven age bins (21–30 through 81–90). Pipeline reliability was validated against FreeSurfer using intraclass correlation coefficients (ICC) and coefficients of variation (CoV). Regression-based correction was used to correct for sex and cohort effects on brain region volume. Then, percentage change in each mean bilateral volumes of regions across the lifespan were computed to describe volumetric changes across life spans. Results: The segmentation pipeline demonstrated excellent agreement with FreeSurfer (mean ICC: 0.9965). Drastic volumetric expansions were observed in white matter hypointensities (122.6%), lateral ventricles (115.9%), and inferior lateral ventricles (116.8%). Moderate-to-notable shrinkage was found predominantly in the frontal lobe (pars triangularis: 21.5%), parietal lobe (inferior parietal: 20.4%), temporal lobe (transverse temporal: 21.6%), and cingulate cortex (caudal anterior cingulate: 16.1%). Minimal volume changes occurred in regions such as the insula (3.7%) and pallidum (2.6%). Conclusions: This study presents a comprehensive reference of normative regional brain volume changes across adulthood, highlighting substantial inter-regional variability. The findings can provide an essential foundation for differentiating normal aging patterns from early pathological alterations.
Shim et al. (2025) studied this question.