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Network Biology, 2023, 13(4): 213-229
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Article

Monte Carlo sampling and computational analysis of a three component tumor radiotherapy mathematical model

Md. Kamrujjaman1, Sayeda Irin Akter2, Asma Akter Akhi1, Shohel Ahmed3, Mahadee Al Mobin1
1Department of Mathematics, University of Dhaka, Dhaka-1000, Bangladesh
2Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
3Department of Applied Mathematics, University of Alberta, AB, Canada

Received 10 July 2023;Accepted 5 September 2023;Published online 20 September 2023;Published 1 December 2023
IAEES

Abstract
Cancer is commonly acknowledged to be among the leading causes of death, and mathematical modeling has the potential to dramatically improve experimental cancer research. To investigate the impact of quiescent cells, we present a 3-C tumor growth model that extends the conventional Gompertz model. We used the Monte Carlo sampling technique, namely the Latin Hypercube Sampling (LHS), to determine the most critical parameters in the model dynamics. Our findings suggest that radiation therapy can be influenced by a variety of factors, including the volume of quiescent cells and the radiation sensitivity coefficient. Furthermore, in some situations, quiescent cells might transform into dividing cells, which can have a significant impact on tumor progression.

Keywords Gompertz growth;anti-angiogenetic;tumor radiotherapy;tumor volume.


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