Decoupling the Effect of Shear Stress and Stretch on Tissue Growth and Remodeling in a Vascular Graft.

The success of cardiovascular tissue engineering (TE) strategies largely depends on the mechanical environment in which cells develop a neotissue through growth and remodeling processes. This mechanical environment is defined by the local scaffold architecture to which cells adhere, that is, the microenvironment, and by external mechanical cues to which cells respond, that is, hemodynamic loading. The hemodynamic environment of early developing blood vessels consists of both shear stress (due to blood flow) and circumferential stretch (due to blood pressure). Experimental platforms that recapitulate this mechanical environment in a controlled and tunable manner are thus critical for investigating cardiovascular TE. In traditional perfusion bioreactors, however, shear stress and stretch are coupled, hampering a clear delineation of their effects on cell and tissue response. In this study, we uniquely designed a bioreactor that independently combines these two types of mechanical cues in eight parallel vascular grafts. The system is computationally and experimentally validated, through finite element analysis and culture of tissue constructs, respectively, to distinguish various levels of shear stress (up to 5 Pa) and cyclic stretch (up to 1.10). To illustrate the usefulness of the system, we investigated the relative contribution of cyclic stretch (1.05 at 0.5 Hz) and shear stress (1 Pa) to tissue development. Both types of hemodynamic loading contributed to cell alignment, but the contribution of shear stress overruled stretch-induced cell proliferation and matrix (i.e., collagen and glycosaminoglycan) production. At a macroscopic level, cyclic stretching led to the most linear stress-stretch response, which was not related to the presence of shear stress. In conclusion, we have developed a bioreactor that is particularly suited to further unravel the interplay between hemodynamics and in situ TE processes. Using the new system, this work highlights the importance of hemodynamic loading to the study of developing vascular tissues.

Application of an Adaptive Polynomial Chaos Expansion on Computationally Expensive Three-Dimensional Cardiovascular Models for Uncertainty Quantification and Sensitivity Analysis.

When applying models to patient-specific situations, the impact of model input uncertainty on the model output uncertainty has to be assessed. Proper uncertainty quantification (UQ) and sensitivity analysis (SA) techniques are indispensable for this purpose. An efficient approach for UQ and SA is the generalized polynomial chaos expansion (gPCE) method, where model response is expanded into a finite series of polynomials that depend on the model input (i.e., a meta-model). However, because of the intrinsic high computational cost of three-dimensional (3D) cardiovascular models, performing the number of model evaluations required for the gPCE is often computationally prohibitively expensive. Recently, Blatman and Sudret (2010, "An Adaptive Algorithm to Build Up Sparse Polynomial Chaos Expansions for Stochastic Finite Element Analysis," Probab. Eng. Mech., 25(2), pp. 183-197) introduced the adaptive sparse gPCE (agPCE) in the field of structural engineering. This approach reduces the computational cost with respect to the gPCE, by only including polynomials that significantly increase the meta-model's quality. In this study, we demonstrate the agPCE by applying it to a 3D abdominal aortic aneurysm (AAA) wall mechanics model and a 3D model of flow through an arteriovenous fistula (AVF). The agPCE method was indeed able to perform UQ and SA at a significantly lower computational cost than the gPCE, while still retaining accurate results. Cost reductions ranged between 70-80% and 50-90% for the AAA and AVF model, respectively.