Simulation Of Tumor Growth Dynamic Based On Cellular Automaton

Substantial progress has been made in the various specialized areas of cancer research. Yet the complexity of the disease on both the single cell level as well as the multicellular tumor stage has led to the first attempts to describe tumors as complex, dynamic, self-organizing biosysterns, rather than merely focusing on single features. This thesis take up with tumor growth modelling and has developed a novel and versatile cellular automaton for simulating tumor growth ( CASTG). As a visual and medically realistic computer model, CASTG mainly considers high-grade glioblastoma multiforme ( GBM). The study of CASTG leads to several significative results: First, we designed a one-dimensional cellular automaton for simulating tumor growth ( 1D-CASTG), which define the transition between normal cells and proliferating cells within CA cell extended Moore neighborhood. Representing body cells with CA cells, 1D-CASTG can simulate tumor growth and shifting in a thin blood vessel. Experimental result of tumor growth dynamic process is accordant with the tumor growth curve mathematically described by Gompertz model. 2D-CASTG has also been studied to simulate the growth dynamic process of ideal complanate tumor. The model represent tumor configuration with two-dimensional CA cells and also achieve a unexceptionable result comparing with Gompertz model. Finally, we studied a three-dimensional cellular automaton for simulating real tumor growth ( 3D-CASTG) . CA cells distribute in a limited 3D lattice, and each CA cell represent i03 real cells. Basing on 3D extended Moore neighborhood, The prolife- ration algorithm runs on each CA cell at each cycle of simulation. The simulation of 3D-CASTG model has been compared with available experimental data for an untreated GBM tumor from medical literature. The parameters compared were cell number, growth fraction, necrotic fraction and volume-doubling time. On the whole, the simulation data reproduce the test case very well. This simulation study suggests that macroscopic tumor behavior can be realistically modelled using microscopic parameters. Using only several parameters, this model simulates Gompertzian growth for a tumor growing over nearly three orders of magnitude in radius.