Abstract
Aortic mechanical and structural characteristics have profound effects on pathophysiology, but many aspects of physiologic stress-stretch state and intramural changes due to aging remain poorly understood in human tissues. While difficult to assess in vivo due to residual stresses and pre-stretch, physiologic stress-stretch characteristics can be calculated using experimentally-measured mechanical properties and constitutive modeling. Mechanical properties of 76 human descending thoracic aortas (TA) from 13 to 78-year-old donors (mean age 51±18 years) were measured using multi-ratio planar biaxial extension. Constitutive parameters were derived for aortas in 7 age groups, and the physiologic stress-stretch state was calculated. Intramural characteristics were quantified from histological images and related to aortic morphometry and mechanics. TA stiffness increased with age, and aortas became more nonlinear and anisotropic. Systolic and diastolic elastic energy available for pulsation decreased with age from 30 to 8 kPa and from 18 to 5 kPa, respectively. Cardiac cycle circumferential stretch dropped from 1.14 to 1.04, and circumferential and longitudinal physiologic stresses decreased with age from 90 to 72 kPa and from 90 to 17 kPa, respectively. Aortic wall thickness and radii increased with age, while the density of elastin in the tunica media decreased. The number of elastic lamellae and circumferential physiologic stress per lamellae unit remained constant with age at 102±10 and 0.85±0.04 kPa, respectively. Characterization of mechanical, physiological, and structural features in human aortas of different ages can help understand aortic pathology, inform the development of animal models that simulate human aging, and assist with designing devices for open and endovascular aortic repairs. Statement of significanceThis manuscript describes mechanical and structural changes occurring in human thoracic aortas with age, and presents material parameters for 4 commonly used constitutive models. Presented data can help better understand aortic pathology, inform the development of animal models that simulate human aging, and assist with designing devices for open and endovascular aortic repairs.
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