Abstract
We investigate the long-time dynamics and optimal control problem of a thermodynamically consistent 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 mass source and prove the convergence of any global solution to a single equilibrium as \(t\rightarrow +\infty \). Second, we consider the “finite-time treatment” that corresponds to an optimal control problem. Here we 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 show 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.
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Acknowledgements
The authors would like to thank the anonymous referees for their careful reading and helpful comments. C. Cavaterra and E. Rocca were partially supported by GNAMPA (Gruppo Nazionale per l’Analisi Matematica, la Probabilità e le loro Applicazioni) of INdAM (Istituto Nazionale di Alta Matematica). This research has been performed in the framework of the project Fondazione Cariplo-Regione Lombardia MEGAsTAR “Matematica d’Eccellenza in biologia ed ingegneria come acceleratore di una nuova strateGia per l’ATtRattività dell’ateneo pavese”. This research was also supported by the Italian Ministry of Education, University and Research (MIUR): Dipartimenti di Eccellenza Program (2018–2022) - Dept. of Mathematics “F. Casorati”, University of Pavia. H. Wu was partially supported by NNSFC Grant No. 11631011 and the Shanghai Center for Mathematical Sciences.
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Appendix
Appendix
Let \(m\in {\mathbb {R}}\) be a given constant. We consider the following nonlocal elliptic boundary value problem
Problem (6.1) can be associated with the following functional
The following result has been obtained in [63, Lemma 3.1, Lemma 3.2].
Lemma 6.1
Let assumption (F1) be satisfied.
-
(1)
Suppose that \(\psi \in H^2_N(\Omega )\) is a (strong) solution to problem (6.1). Then \(\psi \) is a critical point of the functional \(\Upsilon (\phi )\) in \(H^1(\Omega )\). Conversely, if \(\psi \) is a critical point of the functional \(\Upsilon (\phi )\) in \(H^1(\Omega )\), then \(\psi \in H^2_N(\Omega )\) and it is a strong solution to problem (6.1).
-
(2)
The functional \(\Upsilon (\phi )\) has at least one minimizer \(\psi \in H^1(\Omega )\) such that
$$\begin{aligned} \Upsilon (\psi )= \displaystyle {\inf _{\phi \in H^1(\Omega )}}\Upsilon (\phi ). \end{aligned}$$(6.3)
Remark 6.1
By the elliptic regularity theory and a bootstrap argument, the minimizer \(\psi \) is indeed a classical solution such that \(\psi \in C^\infty ({\overline{\Omega }})\), provided that the domain boundary \(\partial \Omega \) and the function F are smooth.
Associated with problem (6.1), the following Łojasiewicz–Simon type inequality has been proven in [63, Lemma 4.1] (see [65, Lemma 2.2] for a slightly weaker version).
Lemma 6.2
Let (F1) and (F2) be satisfied. Suppose that \(\psi \) is a critical point of \(\Upsilon (\phi )\) in \(H^1(\Omega )\). Then there exist constants \(\theta \in (0,\frac{1}{2})\) and \(\beta >0\), depending on \(\psi \), m and \(\Omega \), such that, for any \(\phi \in H^1(\Omega )\) with \(\Vert \phi -\psi \Vert _{H^1(\Omega )}< \beta \), it holds
Now we are in a position to prove the Łojasiewicz–Simon type inequality (3.38) stated in Lemma 3.1, which plays a crucial role in the study of long-time behavior of problem (1.1)–(1.5).
Proof of Lemma 3.1
In Lemma 6.2, we take \(m=m_\infty \) (see (3.35)) and \(\psi =\phi _\infty \). Then it follows from (3.3)–(3.5) and (3.35) that \(\phi _\infty \) satisfies the reduced elliptic problem (6.1). Hence, according to Lemma 6.1, we see that it is a critical point of \(\Upsilon (\phi )\) (cf. (6.2) with \(m=m_\infty \)). As a consequence, Lemma 6.2 applies with constants \(\theta \in (0, \frac{1}{2})\), \(\beta >0\) depending on \(\phi _\infty \), \(m_\infty \) and \(\Omega \). On the other hand, for any \(\phi \in H^2_N(\Omega )\) we set
and then using integration by parts, we get
From the Łojasiewicz–Simon inequality (6.4) (applying to \(\psi =\phi _\infty )\), Poincaré’s inequality and (3.37), we deduce that
By the Sobolev embedding \(H^2(\Omega )\hookrightarrow C({\overline{\Omega }})\) (\(n=2,3\)), the continuity as well as the strictly positivity of P(s), then it holds
where the constant \(C>0\) depends on \(\Omega \), \(\Vert \phi \Vert _{H^2(\Omega )}\) and P.
On the other hand, on account of (1.6), (3.37), (6.2) and Poincaré’s inequality, since \(\theta \in (0,\frac{1}{2})\) and \(\sigma \in H^1(\Omega )\), we infer that
Finally, since \(\Upsilon (\phi _\infty )={\mathcal {E}}(\phi _\infty ,\sigma _\infty )\) (recalling that \(\sigma _\infty \) is a constant satisfying (3.37)), we deduce from inequalities (6.5) and (6.6) that
The proof of Lemma 3.1 is complete. \(\square \)
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Cavaterra, C., Rocca, E. & Wu, H. Long-Time Dynamics and Optimal Control of a Diffuse Interface Model for Tumor Growth. Appl Math Optim 83, 739–787 (2021). https://doi.org/10.1007/s00245-019-09562-5
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DOI: https://doi.org/10.1007/s00245-019-09562-5
Keywords
- Tumor growth
- Cahn–Hilliard equation
- Reaction–diffusion equation
- Optimal control
- Long-time behavior
- Lyapunov stability