Abstract
OBJECTIVES With an increasing aging population, it is important to gain a better understanding of biological markers of aging. Subcortical volume is known to differ with age; additionally considering shape-related characteristics may provide a better index of age-related differences in subcortical structure. Recently fractal dimensionality has been shown to be more sensitive to age-related differences, but this measure is borne out of mathematical principles, rather than quantifying a neurobiologically relevant characteristic directly. We considered four distinct measures of shape and how they relate to aging and fractal dimensionality: surface-to-volume ratio, sphericity, long-axis curvature, and surface texture.
METHODS Structural MRIs from two samples, with a combined sample size of over 600 healthy adults across the adult lifespan, were used to measure age-related differences in the structure of the thalamus, putamen, caudate, and hippocampus. For each structure, volume and fractal dimensionality were calculated, as well as each of the four distinct shape measures. These measures were then examined in their utility in explaining age-related variability in brain structure.
RESULTS The four shape measures were able to account for 80-90% of the variance in fractal dimensionality, indicating that these measures were sensitive to the same shape characteristics. Of the distinct shape measures, surface-to-volume ratio was the most sensitive aging biomarker.
CONCLUSION Though volume is often used to characterize inter-individual differences in subcortical structures, our results demonstrate that additional measures can be useful complements to volumetry. Our results indicate that shape characteristics of subcortical structures are useful biological markers of healthy aging.
