title: Simulation of 3D tumor cell growth using nonlinear finite element method.
abstract: We propose a novel parallel computing framework for a nonlinear finite element method (FEM)-based cell model and apply it to simulate avascular tumor growth. We derive computation formulas to simplify the simulation and design the basic algorithms. With the increment of the proliferation generations of tumor cells, the FEM elements may become larger and more distorted. Then, we describe a remesh and refinement processing of the distorted or over large finite elements and the parallel implementation based on Message Passing Interface to improve the accuracy and efficiency of the simulation. We demonstrate the feasibility and effectiveness of the FEM model and the parallelization methods in simulations of early tumor growth.
authors.affiliation: a School of Computer Science & Engineering , South China University of Technology , Guangzhou , China.
authors.forename: Shoubing
authors.initials: S
authors.lastname: Dong
authors.affiliation: a School of Computer Science & Engineering , South China University of Technology , Guangzhou , China.
authors.forename: Yannan
authors.initials: Y
authors.lastname: Yan
authors.affiliation: b School of Civil Engineering & Transportation , South China University of Technology , Guangzhou , China.
authors.forename: Liqun
authors.initials: L
authors.lastname: Tang
authors.affiliation: a School of Computer Science & Engineering , South China University of Technology , Guangzhou , China.
authors.forename: Junping
authors.initials: J
authors.lastname: Meng
authors.affiliation: c Department of Mathematics & Statistics , Georgia State University , Atlanta , GA , USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Jiang
mesh_terms: D000465:Algorithms; D002455:Cell Division; D049109:Cell Proliferation; D003198:Computer Simulation; D020342:Finite Element Analysis; D006801:Humans; D008962:Models, Theoretical; D009369:Neoplasms / Q000473:pathology*; D017711:Nonlinear Dynamics
keywords: Avascular tumor growth; finite element method; parallel computing