Document Type : Full Research Paper


1 Ph.D. Student, Research Laboratory of Biomedical Signals and Sensors, Biomedical Engineering Department, Iran University of Science and Technology (I.U.S.T), Tehran, Iran

2 Assistant Professor, Biomedical Engineering Department, Iran University of Science and Technology (I.U.S.T), Tehran, Iran


Cancer is a leading cause of death in the world. Mathematical and computer models may help scientists to better understand it, and improve current treatments. They may also introduce new aspects of therapy. In this paper, a Cellular Automata model of tumor by emphasizing on immune system is presented. Considering the spetio-temporal heterogeneity that is not considered in most mathematical models, is one of the novelity of this work. In presented model each tumor cell in a square lattice can interact with both immune and normal cells in its Moore neighborhood. The rules for updating the states of the model are stochastic. Modeling tumor cells scaping from immune system and their survivance and considering immune system recurrement into the studied tissue is another innovation of this model. The results of our simulations are presented with/without considering immune system. The growth fraction and necrotic fraction are considered as output parameters of model as well as a 2-D graphical growth presentation. Results show that considering the heterogeneity will improve the compatibility of the model with biological reality and experimental studies. It can be seen that the number of immune cells increases during the tumor growth and follows the same dynamics as tumor cells. In this paper, we have innovatively focused on the effect of model parameters on different steps of tumor growth from the cancer therapy viewpoint. 


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