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Auteur principal: Roy, Sumit
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2512.21620
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author Roy, Sumit
author_facet Roy, Sumit
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2512_21620
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A mathematical model to predict growth and treatment for UPS cancer
Roy, Sumit
Optimization and Control
92B05, 92C50, 34H05, 49N90
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.
title A mathematical model to predict growth and treatment for UPS cancer
topic Optimization and Control
92B05, 92C50, 34H05, 49N90
url https://arxiv.org/abs/2512.21620