Abstract:
Cancer is a complex disease that is comprised of many different cellular and tissue level organizations. Tumor growth simulation is vital in predicting the way tumors grow. Tumor modelling is used to shed light on cancer biology and is considered a promising method for developing more effective cancer therapies. In this study, the biological inputs and their respective outputs using the simulation approaches were systematically reviewed. A comparison table was produced that shows in detail the biological inputs for each simulation code. This is in contrast to the current agentbased model reviews that mostly focus on computer efficiency. Physicell was selected among the reviewed open-source software due to its integrated basic cell functions and microenvironment simulation capabilities. Tumor growth has been simulated in the Physicell v1.6.1 tumor simulation software. The A549 cell specific parameters have been used during the simulation and the effects of the initial oxygen concentration in the microenvironment were examined on outcome images. Growth rate of tumor cells increases with the increasing oxygen concentration in the microenvironment. Formation rate of necrotic core in the tumor structure reduces with the increasing oxygen concentration due to small number of hypoxic cells in the tumor structure. Based on our findings in the simulation, physicians can predict the hypoxic regions in tumor structure to plan a chemotherapy treatment dependent localized peripheral tissue considering the correlation between oxygen concentration and tumor growth rate.|Keywords : Cancer, Tumor Growth, Agent-Based Model Simulations.
