title: A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains.
abstract: Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner.
authors.affiliation: College of Inter-faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, Warsaw Poland.
authors.forename: Jan
authors.initials: J
authors.lastname: Poleszczuk
authors.affiliation: Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
authors.forename: Heiko
authors.initials: H
authors.lastname: Enderling
keywords: cancer stem cells; cellular automaton; dynamic boundaries; sensitivity analysis; tumor model