Computational models for heterogeneous media Politecnico di Milano - Fondo 5xMille

Keywords

MOX responsible:
Paolo Zunino
Start date:
End date:
Abstract:
Application to microscale analysis of tissue engineered constructs
Description:
This project aims to develop and validate suitable mathematical models and computational techniques for the interpretation and prediction of three-dimensional (3D) polymer scaffolded systems for engineered tissue growth, where a quantitative understanding of the interplay among geometry, flow perfusion, nutrient/waste mass transfer and cellular proliferation is required. The project is organized into three main workpackages, reflecting the natural subdivision into modelling, simulation and experimental validation activities. To directly compare the outcome of computational analysis with the experimental observations on realistic cellular constructs, it is mandatory that the employed numerical methods are based on realistic geometrical models, that closely represent the location where the experimental observations are addressed. Micro-CT and confocal microscopy images will be the starting point to reconstruct the geometrical models for numerical simulations. Then, one of the methodological objectives of this project is to substantially simplify the interaction between image based biomedical data and computational models based on PDEs. This will be achieved by means of the fictitious domain concept, which avoids the cumbersome task of setting up a parametric mathematical description of the domain boundaries or interfaces. Successful results in this direction could be beneficial to a wide spectrum of applications, not only to the one specific to this project, but, for instance, Geophysics, where similar difficulties are encountered. The development of mathematical models will also profitably interact with the experimental investigation coordinated by a member of the research team. This collaboration will provide the correct geometrical and physiological data relative to realistic tissue growth settings and the laboratory expertise to compare the results of the computational models with the realistic in vitro situation.