Continued advances in the tissue engineering of vascular grafts have enabled a paradigm shift from the desire to design for adequate suture retention, burst pressure and thrombo-resistance to the goal of achieving grafts having near native properties, including growth potential. Achieving this far more ambitious outcome will require the identification of optimal, not just adequate, scaffold structure and material properties. Given the myriad possible combinations of scaffold parameters, there is a need for a new strategy for reducing the experimental search space. Toward this end, we present a new modeling framework for in vivo neovessel development that allows one to begin to assess in silico the potential consequences of different combinations of scaffold structure and material properties. To restrict the number of parameters considered, we also utilize a non-dimensionalization to identify key properties of interest. Using illustrative constitutive relations for both the evolving fibrous scaffold and the neotissue that develops in response to inflammatory and mechanobiological cues, we show that this combined non-dimensionalization computational approach predicts salient aspects of neotissue development that depend directly on two key scaffold parameters, porosity and fiber diameter. We suggest, therefore, that hypothesis-driven computational models should continue to be pursued given their potential to identify preferred combinations of scaffold parameters that have the promise of improving neovessel outcome. In this way, we can begin to move beyond a purely empirical trial-and-error search for optimal combinations of parameters and instead focus our experimental resources on those combinations that are predicted to have the most promise.
Keywords: Constrained mixture theory; Fibrous scaffold; Interposition graft; Mouse model; Poly(glycolic acid).
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