title: Simulated brain tumor growth dynamics using a three-dimensional cellular automaton.
abstract: We have developed a novel and versatile three-dimensional cellular automaton model of brain tumor growth. We show that macroscopic tumor behavior can be realistically modeled using microscopic parameters. Using only four parameters, this model simulates Gompertzian growth for a tumor growing over nearly three orders of magnitude in radius. It also predicts the composition and dynamics of the tumor at selected time points in agreement with medical literature. We also demonstrate the flexibility of the model by showing the emergence, and eventual dominance, of a second tumor clone with a different genotype. The model incorporates several important and novel features, both in the rules governing the model and in the underlying structure of the model. Among these are a new definition of how to model proliferative and non-proliferative cells, an isotropic lattice, and an adaptive grid lattice.
authors.affiliation: Department of Chemical Engineering, Princeton Materials Institute, Princeton, NJ 08544, USA.
authors.forename: A R
authors.initials: AR
authors.lastname: Kansal
authors.forename: S
authors.initials: S
authors.lastname: Torquato
authors.forename: I V
authors.initials: IV
authors.lastname: Harsh GR
authors.forename: E A
authors.initials: EA
authors.lastname: Chiocca
authors.forename: T S
authors.initials: TS
authors.lastname: Deisboeck
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000473:pathology*; D002455:Cell Division; D005909:Glioblastoma / Q000473:pathology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D008954:Models, Biological; D009336:Necrosis; D014411:Neoplastic Stem Cells / Q000473:pathology