An increasing number of intermediate risk asymptomatic subjects benefit from measures of atherosclerosis burden like coronary artery calcification studies with non-contrast heart computed tomography (CT). However, additional information can be derived from these studies, looking beyond the coronary arteries and without exposing the patients to further radiation. We report a semi-automatic method that objectively assesses ascending, arch and descending aorta dimension and shape from non-contrast CT datasets to investigate the effect of aging on thoracic aorta geometry. First, the segmentation process identifies the vessel centerline coordinates following a toroidal path for the curvilinear portion and axial planes for descending aorta. Then, reconstructing oblique planes orthogonal to the centerline direction, it iteratively fits circles inside the vessel cross-section. Finally, regional thoracic aorta dimensions (diameter, volume and length) and shape (vessel curvature and tortuosity) are calculated. A population of 200 normotensive men was recruited. Length, mean diameter and volume differed by 1.2 cm, 0.13 cm and 21 cm(3) per decade of life, respectively. Aortic shape uncoiled with aging, reducing its tortuosity and increasing its radius of curvature. The arch was the most affected segment. In conclusion, non-contrast cardiac CT imaging can be successfully employed to assess thoracic aorta 3D morphometry.