Abstract
The biochemical dynamics involved in tumor growth can be broadly classified into three distinct spatial scales: the tumor scale, the cell-ECM interactions and the sub-cellular processes. This work presents the tumor scale investigations, which are expected to eventually lead to a system-level understanding of the progression of cancer. Many of the macroscopic phenomena of physiological relevance, such as tumor size and shape, formation of necrotic core and vascularization, proliferation and metastasis of cell populations, external mechanical interactions, etc., can be treated within a continuum framework by modeling the evolution of various species involved by transport equations coupled with mechanics. This framework is an extension of earlier work (Garikipati et al. in J. Mech. Phys. Solids 52:1595–1625, 2004; Narayanan et al. in Biomech. Model. Mechanobiol. 8:167–181, 2009, J. Phys. Condens. Matter. 22:194122, 2010) based on the continuum theory of mixtures for modeling biological growth. Specifically, the focus is on demonstrating the effectiveness of mechano-transport coupling in simulating tumor growth dynamics and explaining some in vitro observations like mechanics-induced ellipsoidal tumor shapes. Additionally, this work also seeks to demonstrate the effectiveness of tools like adaptive mesh refinement and automatic differentiation in handling highly nonlinear, coupled multiphysics systems.
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Notes
- 1.
Automatic differentiation, also referred to as algorithmic differentiation, calculates derivatives of functions up to any order to within machine precision by reducing complex functions to elementary arithmetic operations and elementary functions by repeated application of the chain rule. It can result in significant speedup of multiphysics implementations by computing the Jacobian of finite element residuals. For variational problems, even greater ease of implementation is possible: only the energy functional needs to be coded, and the system of residual equations and the Jacobian can be computed by taking variational derivatives of the functional and residual equations, respectively.
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Rudraraju, S., Mills, K.L., Kemkemer, R., Garikipati, K. (2013). Multiphysics Modeling of Reactions, Mass Transport and Mechanics of Tumor Growth. In: Holzapfel, G., Kuhl, E. (eds) Computer Models in Biomechanics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5464-5_21
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DOI: https://doi.org/10.1007/978-94-007-5464-5_21
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