A mathematical model to predict growth and treatment for UPS cancer

TL;DR

This paper develops a comprehensive mathematical model for UPS cancer growth and treatment, integrating tumor dynamics, immune response, and radiation therapy, providing insights into optimal treatment strategies.

Contribution

It introduces a novel nonlinear differential equation model combining tumor growth, immune interaction, and treatment, with analysis of stability and optimal control for radiation therapy.

Findings

Tumor growth exhibits a threshold below which it cannot be sustained.

Postoperative dynamics show transient behavior before recovery.

Optimal radiation treatment follows a bang-bang control strategy.

Abstract

We propose a mathematical model for the growth and treatment dynamics of Undifferentiated Pleomorphic Sarcoma (UPS) based on a system of nonlinear differential equations. The model integrates Gompertz-type tumor growth with surface-area dependent necrotic loss, surgical resection with residual disease, postoperative recovery, tumor-immune interaction, and an optimal radiation treatment component. We analyze the resulting dynamical system and obtain several properties of the model. The growth equation exhibits a threshold below which tumor volume cannot be sustained. The postoperative phase shows transient dynamics prior to proliferative recovery. For the tumor-immune subsystem, equilibrium states and local stability conditions are identified. The radiation treatment problem is formulated as an optimal control problem, and the optimal strategy is shown to be of bang-bang type. Numerical simulations illustrate the influence of biological and treatment parameters on tumor evolution, and the results are qualitatively consistent with clinical patterns reported for UPS.