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arXiv 1901.07500math.AP
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肿瘤生长扩散界面模型的长时间动力学与最优控制

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

Cecilia Cavaterra, Elisabetta Rocca, Hao Wu

AI总结:

研究肿瘤生长扩散界面模型的长时间动力学与最优控制,通过 Cahn-Hilliard 型方程与反应扩散方程描述肿瘤与营养,证明了长时间治疗的全局解收敛性及有限时间治疗的最优控制存在性与一阶必要条件,并利用 Lyapunov 稳定性确保治疗后肿瘤不再生长。

摘要:

我们研究了一个扩散界面模型的长时间动力学与最优控制问题,该模型描述了在存在营养物质且被宿主组织包围的情况下肿瘤的生长。状态系统由描述肿瘤细胞分数的 Cahn-Hilliard 型方程和描述营养物质的反应扩散方程组成。用于消除肿瘤细胞的可能药物治疗以药物形式体现,并通过营养物质引入系统。在此设定下,控制变量在营养物质方程中作为外部源项。首先,我们在合适的给定源项下考虑“长时间治疗”问题,并证明当 $t\to+\infty$ 时,任意全局解收敛至单一平衡态。然后,我们考虑肿瘤的“有限时间治疗”,这对应于一个最优控制问题。在此,我们还允许目标成本泛函依赖于一个自由时间变量,该变量代表需要优化的未知治疗时间。我们证明了最优控制的存在性,并获得了药物浓度和治疗时间的一阶必要最优性条件。控制问题的主要目标之一是以最佳方式实现肿瘤细胞的期望最终分布,该分布由目标函数 $ϕ_Ω$ 表示。通过建立状态系统(无外部源项)某些平衡态的 Lyapunov 稳定性,我们发现 $ϕ_Ω$ 可被视为一种稳定构型,从而使得肿瘤在有限时间治疗完成后不会再次生长。

英文摘要:

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 $ϕ_Ω$. By establishing the Lyapunov stability of certain equilibria of the state system (without external source), we see that $ϕ_Ω$ can be taken as a stable configuration, so that the tumor will not grow again once the finite-time treatment is completed.

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