Performance Enhancement and Equivalence Criteria for Cellular Automaton-Based Tumor Simulations

This paper describes a performance enhancement to a cellular automaton-based simulation of tumor growth. A cellular automaton is a grid-based data structure whose elements are updated according to specific rules. Elements represent small areas of simulated tissue and contain local cell population and nutrient concentration data for those areas. The simulation’s computational efficiency is enhanced by suppressing updates to steady-state tissue locations, areas with little change in nutrient concentration or cell population. This modification produces different tissue development from the original, canonical method in which all tissue areas are updated on every timestep. This paper defines several criteria by which a modified, efficient simulation can be considered equivalent to an original, canonical method; these criteria are applied to determine whether or not the performance enhancement can be considered equivalent to the original simulation.