Computational modeling of multicellular constructs with the material point method.

Computational modeling of the mechanics of cells and multicellular constructs with standard numerical discretization techniques such as the finite element (FE) method is complicated by the complex geometry, material properties and boundary conditions that are associated with such systems. The objectives of this research were to apply the material point method (MPM), a meshless method, to the modeling of vascularized constructs by adapting the algorithm to accurately handle quasi-static, large deformation mechanics, and to apply the modified MPM algorithm to large-scale simulations using a discretization that was obtained directly from volumetric confocal image data. The standard implicit time integration algorithm for MPM was modified to allow the background computational grid to remain fixed with respect to the spatial distribution of material points during the analysis. This algorithm was used to simulate the 3D mechanics of a vascularized scaffold under tension, consisting of growing microvascular fragments embedded in a collagen gel, by discretizing the construct with over 13.6 million material points. Baseline 3D simulations demonstrated that the modified MPM algorithm was both more accurate and more robust than the standard MPM algorithm. Scaling studies demonstrated the ability of the parallel code to scale to 200 processors. Optimal discretization was established for the simulations of the mechanics of vascularized scaffolds by examining stress distributions and reaction forces. Sensitivity studies demonstrated that the reaction force during simulated extension was highly sensitive to the modulus of the microvessels, despite the fact that they comprised only 10.4% of the volume of the total sample. In contrast, the reaction force was relatively insensitive to the effective Poisson's ratio of the entire sample. These results suggest that the MPM simulations could form the basis for estimating the modulus of the embedded microvessels through a parameter estimation scheme. Because of the generality and robustness of the modified MPM algorithm, the relative ease of generating spatial discretizations from volumetric image data, and the ability of the parallel computational implementation to scale to large processor counts, it is anticipated that this modeling approach may be extended to many other applications, including the analysis of other multicellular constructs and investigations of cell mechanics.