  The study of associations between an individual's age and imaging and
non-imaging data is an active research area that attempts to aid understanding
of the effects and patterns of aging. In this work we have conducted a
supervoxel-wise association study between both volumetric and tissue density
features in coronary computed tomography angiograms and the chronological age
of a subject, to understand the localized changes in morphology and tissue
density with age. To enable a supervoxel-wise study of volume and tissue
density, we developed a novel method based on image segmentation, inter-subject
image registration, and robust supervoxel-based correlation analysis, to
achieve a statistical association study between the images and age. We evaluate
the registration methodology in terms of the Dice coefficient for the heart
chambers and myocardium, and the inverse consistency of the transformations,
showing that the method works well in most cases with high overlap and inverse
consistency. In a sex-stratified study conducted on a subset of $n=1388$ images
from the SCAPIS study, the supervoxel-wise analysis was able to find localized
associations with age outside of the commonly segmented and analyzed
sub-regions, and several substantial differences between the sexes in
association of age and volume.
