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Global and regional annual brain volume loss rates in physiological aging
Global and regional annual brain volume loss rates in physiological aging
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Global and regional annual brain volume loss rates in physiological aging
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Global and regional annual brain volume loss rates in physiological aging
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Global and regional annual brain volume loss rates in physiological aging
Global and regional annual brain volume loss rates in physiological aging
Journal Article

Global and regional annual brain volume loss rates in physiological aging

2017
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Overview
The objective is to estimate average global and regional percentage brain volume loss per year (BVL/year) of the physiologically ageing brain. Two independent, cross-sectional single scanner cohorts of healthy subjects were included. The first cohort ( n  = 248) was acquired at the Medical Prevention Center (MPCH) in Hamburg, Germany. The second cohort ( n  = 316) was taken from the Open Access Series of Imaging Studies (OASIS). Brain parenchyma (BP), grey matter (GM), white matter (WM), corpus callosum (CC), and thalamus volumes were calculated. A non-parametric technique was applied to fit the resulting age–volume data. For each age, the BVL/year was derived from the age–volume curves. The resulting BVL/year curves were compared between the two cohorts. For the MPCH cohort, the BVL/year curve of the BP was an increasing function starting from 0.20% at the age of 35 years increasing to 0.52% at 70 years (corresponding values for GM ranged from 0.32 to 0.55%, WM from 0.02 to 0.47%, CC from 0.07 to 0.48%, and thalamus from 0.25 to 0.54%). Mean absolute difference between BVL/year trajectories across the age range of 35–70 years was 0.02% for BP, 0.04% for GM, 0.04% for WM, 0.11% for CC, and 0.02% for the thalamus. Physiological BVL/year rates were remarkably consistent between the two cohorts and independent from the scanner applied. Average BVL/year was clearly age and compartment dependent. These results need to be taken into account when defining cut-off values for pathological annual brain volume loss in disease models, such as multiple sclerosis.