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

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