Aging is a primary risk factor for increased central arterial stiffness which is both an initiator and indicator of cardiovascular, neurovascular and renovascular disease. It is hypothesized that an insidious positive feedback loop exists between arterial stiffness and systemic blood pressure. The clinical measurement to assess arterial stiffness non-invasively is carotid to femoral Pulse Wave Velocity (cf-PWV), yet controversy still remains. There exists a need to evaluate cf-PWV as an early diagnostic of progressive vascular stiffening and to better assess the potential effects of regional variations in central mechanical properties on blood hemodynamics that adversely affect microcirculation in the heart, brain and kidneys.



Computational modeling is a powerful tool to understand the complexity of central arterial function. In this work we used a robust, data-driven computational framework that combines 3D geometric vascular models, Fluid-Structure Interaction (FSI) analyses, Windkessel models to represent the distal vasculature and an external tissue boundary condition to represent perivascular support. FSI methods allowed to account for the deformability of the central vessels and included spatially variable anisotropic tissue properties.



We first introduced a data-driven FSI computational model of the human aorta to simulate effects of aging-related changes in regional wall properties and geometry on several metrics of arterial stiffness. Using the best available biomechanical data, our results for PWV compared well to findings reported for large population studies while rendering a higher resolution description of evolving metrics of aortic stiffening. Our results revealed similar spatio-temporal trends between stiffness and its surrogate metrics, except PWV, thus indicating a complex dependency of the latter on geometry. Furthermore, our analysis highlighted the importance of the tethering exerted by external tissues.



Due to difficulty in obtaining detailed information on evolving regional mechanical properties in humans, we focused on mouse models of vascular aging, which offer the advantage of easier longitudinal studies and data accessibility. We developed a workflow to combine in vivo and in vitro biomechanical data to build mouse-specific computational models of the central vasculature. These FSI models are informed by micro-CT imaging, in vitro mechanical characterization of the arterial wall, and in vivo ultrasound and pressure measurements. We reproduced central artery biomechanics in adult wild-type, fibulin-5 deficient mice, a model of early vascular aging, and naturally aged wild type mice. Findings were also examined as a function of sex. Computational results compared well with data available in the literature and suggested that PWV does not well reflect the presence of regional differences in stiffening and it is affected by vascular wall stiffness heterogeneities. Modeling is also useful for evaluating quantities that are difficult to measure experimentally, including local pulse pressures at the renal arteries and characteristics of the peripheral vascular bed that may be altered by disease.



Notwithstanding the many advantages of animal models, it is important to consider that invasive experimental procedures may alter the quantity of interest. Advanced computational models offer a unique method to evaluate these measurements. Herein we evaluated the effects of commercially available catheters on the very parameters that they are designed to measure, namely murine blood pressure and PWV. We investigated two different setups and observed that both alter the measured values of PWV.



Lastly, we showed preliminary results involving automatic parameter estimation and expansion of the FSI framework to account for the large motions imposed by the heart on the aorta.

Chair: Alberto Figueroa