Simulation of 3D tumor cell growth using nonlinear finite element method

Area of Science:

• Computational biology
• Biomedical engineering
• Mathematical modeling

Background:

• Avascular tumor growth simulation requires robust computational models.
• Nonlinear finite element methods (FEM) offer a powerful approach for complex biological simulations.
• Challenges include managing element distortion and computational efficiency as simulations progress.

Purpose of the Study:

• To introduce a novel parallel computing framework for nonlinear FEM-based cell models.
• To apply this framework to simulate avascular tumor growth.
• To enhance the accuracy and efficiency of tumor growth simulations.

Main Methods:

• Development of a nonlinear finite element method (FEM) cell model.
• Derivation of simplified computation formulas and algorithm design.
• Implementation of remesh and refinement processing for distorted elements.
• Parallel implementation using Message Passing Interface (MPI).

Main Results:

• The proposed framework effectively simulates early avascular tumor growth.
• Remeshing and refinement strategies successfully addressed element distortion.
• Parallelization significantly improved simulation accuracy and efficiency.
• Demonstrated feasibility and effectiveness of the FEM model and parallelization.

Conclusions:

• The novel parallel FEM framework is effective for simulating avascular tumor growth.
• The developed methods improve computational efficiency and accuracy.
• This approach provides a valuable tool for studying early tumor development.