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Affiliation(s)

Department of Engineering Mathematics and Physics, Faculty of Engineering, Cairo University, Giza 12613, Egypt

ABSTRACT

The bio-mechanism of the spread of tumor cells in a biological tissue is highly complicated and a potent source of controversy. The study of this mechanism is considered partially as a diffusion process for both normal and tumor cells. A 3D computer model is introduced to simulate the stochastic growth of living cells in a homogeneous nutrient medium. The model follows the cytokinetic rules of living cell division. Cell-cell interactions have been formulated and developed for both types. The term BDC (biological diffusion coefficient) is introduced as a new measure to assess the tumor progression in a normal tissue. The BDC of normal and tumor cells is calculated as a function of time and loss factor. The results show that the existence of normal cells acts as a stochastic resistance to the malignant growth. Moreover, the biological diffusion coefficient of tumor cell increases with time explaining the apparent acceleration and penetration of tumor cells through a normal tissue.

KEYWORDS

Stochastic modelling, tumor growth, biological diffusion coefficient

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References
[1] Düchting, W., and Vogelsaenger, T. 1981. “3-D Tumor Growth: Modelling and Simulation.” In Proceedings of the Annual Symposium on Computer Application in Medical Care, 586-90.
[2] Vogelsaenger, W., and Düchting, T. 1982. “Simulation of Tumor Growth as a Tool for Determining the Optimal Moment of Administering Chemotherapeutic Agents.”
[3] Düchting, W., and Vogelsaenger, T. 1987. “An Approach of Modelling and Simulating the Spread of Heterogeneous Tumor Cells in a Three-Dimensional Tissue Segment.” Computers & Mathematics with Applications 14 (9-12): 783-92.
[4] Düchting, W. 1990. “Cancer Models and Advances in Simulating Radiation Therapy.” Mathematical and Computer Modelling 14: 623-8.
[5] Dutching, W., Ginsberg, T., and Ulmer, W. 1996. “Computer Simulation Applied to Radiation Therapy in Cancer Research.” Applied Mathematics and Computation 74: 191-207.
[6] Torquato, A. R., Harsh Iv, S., Chiocca, G. R., Deisboeck, E. A., and Kansal, T. S. 2000. “Cellular Automaton of Idealized Brain Tumor Growth Dynamics.” Biosystems 55 (1): 119-27.
[7] Torquato, A. R., Harsh, S., Chiocca, G. R., Deisboeck, E. A., and Kansal, T. S. 2000. “Simulated Brain Tumor Growth Dynamics Using a Three-Dimensional Cellular Automaton.” Journal of Theoretical Biology 203 (4): 367-82.
[8] Anderson, A. R. A., Weaver, A. M., Cummings, P. T., and Quaranta, V. 2006. “Tumor Morphology and Phenotypic Evolution Driven by Selective Pressure from the Microenvironment.” Cell 127: 905-15.
[9] Anderson, A. R. A., Rejniak, K. A., Gerlee, P., and Quaranta, V. 2007. “Modelling of Cancer Growth, Evolution and Invasion: Bridging Scales and Models.” Mathematical Modelling of Natural Phenomena 2 (3): 1-29.
[10] Anderson, A. R. A., Rejniak, K. A., Gerlee, P., and Quaranta, V. 2009. “Microenvironment Driven Invasion: A Multiscale Multimodel Investigation.” J. Mathematical Biology 58 (4): 579-624.
[11] Drasdo, D., Hoehme, S., and Block, M. 2007. “On the Role of Physics in the Growthand Pattern Formation of Multi-cellular Systems: What Can We Learn from Individual-Cell Based Models.” Journal of Statistical Physics 128 (1/2): 287-345.
[12] Kim, Y., Stolarska, M. A., and Othmer, H. G. 2007. “A Hybrid Model for Tumor Spheroid Growth in vitro I: Theoretical Development and Early Results.” Mathematical Models and Methods in Applied Sciences 17: 1773-98.
[13] El-Messiery, M. A. 1990. “Spatial and Vacancy Effects on the Stabilising Mechanisms of Two Dimensional Free Growth.” Biosystems 24: 193-207.
[14] Tuckwell, W., Bezak, E., Yeoh, E., and Marcu, L. 2008. “Efficient Monte Carlo Modelling of Individual Tumour Cell Propagation for Hypoxic Head and Neck Cancer.” Physics in Medicine and Biology 53 (17): 4489-507.
[15] Boondirek, A., et al. 2006. “A Stochastic Model of Cancer Growth with Immune Response.” Journal of the Korean Physical Society 49 (4): 1652-66.
[16] Shirinifard, A., et al. 2009. “3D Multi-cell Simulation of Tumor Growth and Angiogenesis.” PloS One 4 (10): e7190.
[17] El Messiery, M. A., and El Tawil, M. A. 1984. “New Hypotheses on the Mechanism of Cancer Growth and Regression (Computer Simulation Study).” Medical and Biological Engineering and Computing 22 (5): 448-52. 
[18] Paul Shewmon. 2016. Diffusion in Solids. New York: Springer. 

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