Long-time Dynamics and Optimal Control of a Diffuse Interface Model for Tumor Growth

TL;DR

This paper studies the long-term behavior and optimal control of a tumor growth model using diffuse interface methods, proving convergence to equilibrium and establishing optimal treatment strategies with stability analysis.

Contribution

It introduces a novel analysis of long-time dynamics and optimal control for a tumor growth model involving Cahn-Hilliard and reaction-diffusion equations, including treatment time optimization.

Findings

Solutions converge to a single equilibrium over time.

Existence of an optimal control for finite-time tumor treatment.

Stability of tumor configurations under certain conditions.

Abstract

We investigate the long-time dynamics and optimal control problem of a diffuse interface model that describes the growth of a tumor in presence of a nutrient and surrounded by host tissues. The state system consists of a Cahn-Hilliard type equation for the tumor cell fraction and a reaction-diffusion equation for the nutrient. The possible medication that serves to eliminate tumor cells is in terms of drugs and is introduced into the system through the nutrient. In this setting, the control variable acts as an external source in the nutrient equation. First, we consider the problem of `long-time treatment' under a suitable given source and prove the convergence of any global solution to a single equilibrium as $t\to+\infty$. Then we consider the `finite-time treatment' of a tumor, which corresponds to an optimal control problem. Here we also allow the objective cost functional to depend on a free time variable, which represents the unknown treatment time to be optimized. We prove the existence of an optimal control and obtain first order necessary optimality conditions for both the drug concentration and the treatment time. One of the main aim of the control problem is to realize in the best possible way a desired final distribution of the tumor cells, which is expressed by the target function $\phi_\Omega$. By establishing the Lyapunov stability of certain equilibria of the state system (without external source), we see that $\phi_{\Omega}$ can be taken as a stable configuration, so that the tumor will not grow again once the finite-time treatment is completed.