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.

翻译：个体年龄与影像及非影像数据之间的关联研究是当前活跃的研究领域，旨在揭示衰老的影响与模式。本研究基于冠状动脉CT血管造影中的体积和组织密度特征，开展超体素级别的关联分析，探索个体实际年龄与形态学及组织密度的局部变化规律。为实现体积与组织密度的超体素分析，我们提出了一种新方法，融合图像分割、个体间图像配准及鲁棒超体素相关性分析，构建影像与年龄的统计关联模型。采用心脏腔室与心肌的Dice系数及变换逆一致性对配准方法进行评估，结果表明该方法在多数情况下具有较高的重叠度和逆一致性。基于SCAPIS研究子集（n=1388例图像）的性别分层分析显示，该超体素方法在常规分割与分析区域外发现了与年龄相关的局部关联，并揭示了性别间在年龄与体积关联模式上的显著差异。