A fully-decoupled discontinuous Galerkin approximation of the Cahn–Hilliard–Brinkman–Ohta–Kawasaki tumor growth model
ESAIM: Mathematical Modelling and Numerical Analysis , Tome 56 (2022) no. 6, pp. 2141-2180

In this article, we consider the Cahn–Hilliard–Brinkman–Ohta–Kawasaki tumor growth system, which couples the Brinkman flow equations in the porous medium and the Cahn–Hilliard type equation with the nonlocal Ohta–Kawasaki term. We first construct a fully-decoupled discontinuous Galerkin method based on a decoupled, stabilized energy factorization approach and implicit-explicit Euler method in the time discretization, and strictly prove its unconditional energy stability. The optimal error estimate for the tumor interstitial fluid pressure is further obtained. Numerical results are also carried out to demonstrate the effectiveness of the proposed numerical scheme and verify the theoretical results. Finally, we apply the scheme to simulate the evolution of brain tumors based on patient-specific magnetic resonance imaging, and the obtained computational results show that the proposed numerical model and scheme can provide realistic calculations and predictions, thus providing an in-depth understanding of the mechanism of brain tumor growth.

DOI : 10.1051/m2an/2022064
Classification : 65M12, 35Q30, 35J05, 76D05
Keywords: Cahn–Hilliard–Brinkman, fully-decoupled, discontinuous Galerkin method, error estimates, brain tumor growth
@article{M2AN_2022__56_6_2141_0,
     author = {Zou, Guang-an and Wang, Bo and Yang, Xiaofeng},
     title = {A fully-decoupled discontinuous {Galerkin} approximation of the {Cahn{\textendash}Hilliard{\textendash}Brinkman{\textendash}Ohta{\textendash}Kawasaki} tumor growth model},
     journal = {ESAIM: Mathematical Modelling and Numerical Analysis },
     pages = {2141--2180},
     year = {2022},
     publisher = {EDP-Sciences},
     volume = {56},
     number = {6},
     doi = {10.1051/m2an/2022064},
     mrnumber = {4516168},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/m2an/2022064/}
}
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Zou, Guang-an; Wang, Bo; Yang, Xiaofeng. A fully-decoupled discontinuous Galerkin approximation of the Cahn–Hilliard–Brinkman–Ohta–Kawasaki tumor growth model. ESAIM: Mathematical Modelling and Numerical Analysis , Tome 56 (2022) no. 6, pp. 2141-2180. doi: 10.1051/m2an/2022064

[1] J. Belmonte-Beitia, G. F. Calvo and V. M. Pérez-García, Effective particle methods for Fisher-Kolmogorov equations: theory and applications to brain tumor dynamics. Commun. Nonlinear Sci. Numer. Simul. 19 (2014) 3267–3283. | MR | DOI

[2] H. Hatzikirou, A. Deutsch, C. Schaller, M. Simon and K. Swanson, Mathematical modelling of glioblastoma tumour development: a review. Math. Models Methods Appl. Sci. 15 (2005) 1779–1794. | MR | Zbl | DOI

[3] V. M. Pérez-García, O. León-Triana, M. Rosa and A. Pérez-Martnez, CAR T cells for T-cell leukemias: insights from mathematical models. Commun. Nonlinear Sci. Numer. Simul. 96 (2021) 105684. | MR | DOI

[4] K. Swanson, Mathematical modeling of the growth and control of tumors. Ph.D. thesis. University of Washington (1999). | MR

[5] D. Bresch, T. Colin, E. Grenier, B. Ribba and O. Saut, Computational modeling of solid tumor growth: the avascular stage. SIAM J. Sci. Comput. 32 (2010) 2321–2344. | MR | Zbl | DOI

[6] B. Ribba, O. Saut, T. Colin, D. Bresch, E. Grenier and J. P. Boissel, A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents. J. Theor. Biol. 243 (2006) 532–541. | MR | DOI

[7] A. Collin, T. Kritter, C. Poignard and O. Saut, Joint state-parameter estimation for tumor growth model. SIAM J. Appl. Math. 81 (2021) 355–377. | MR | DOI

[8] T. Michel, J. Fehrenbach, V. Lobjois, J. Laurent, A. Gomes, T. Colin and C. Poignard, Mathematical modeling of the proliferation gradient in multicellular tumor spheroids. J. Theoret. Biol. 458 (2018) 133–147. | MR | DOI

[9] J. Sherratt and M. Chaplain, A new mathematical model for avascular tumor growth. J. Math. Biol. 43 (2019) 291–312. | MR | Zbl | DOI

[10] Y. Jiang, J. Pjesivac-Grbovic, C. Cantrell and J. Freyer, A multiscale model for avascular tumor growth. Biophys. J. 89 (2005) 3884–3894. | DOI

[11] T. Roose, S. J. Chapman and P. K. Maini, Mathematical models of avascular tumor growth. SIAM Rev. 49 (2007) 179–208. | MR | Zbl | DOI

[12] S. Sanga, J. Sinek, H. Frieboes, M. Ferrari, J. Fruehauf and V. Cristini, Mathematical modeling of cancer progression and response to chemotherapy. Expert Rev. Anticancer Ther. 6 (2006) 1361–1376. | DOI

[13] J. Sinek, H. Frieboes, X. Zheng and V. Cristini, Two-dimensional chemotherapy simulations demonstrate fundamental transport and tumor response limitations involving nanoparticles. Biomed. Microdevices 6 (2004) 297–309. | DOI

[14] M. Dai, E. Feireisl, E. Rocca, G. Schimperna and M. Schonbek, Analysis of a diffuse interface model for multispecies tumor growth. Nonlinearity 30 (2007) 1639–1658. | MR | DOI

[15] S. Frigeri, M. Grasselli and E. Rocca, On a diffuse interface model of tumor growth. Eur. J. Appl. Math. 26 (2015) 215–243. | MR | DOI

[16] S. Frigeri, K. F. Lam, E. Rocca and G. Schimperna, On a multi-species Cahn–Hilliard–Darcy tumor growth model with singular potentials. Commun. Math. Sci. 16 (2018) 821–856. | MR | DOI

[17] H. Garcke, K. F. Lam, E. Sitka and V. Styles, A Cahn–Hilliard–Darcy model for tumour growth with chemotaxis and active transport. Math. Models Methods Appl. Sci. 26 (2016) 1095–1148. | MR | DOI

[18] M. Ebenbeck and H. Garcke, Analysis of a Cahn–Hilliard–Brinkman model for tumour growth with chemotaxis. J. Differ. Equ. 266 (2019) 5998–6036. | MR | DOI

[19] J. Jiang, H. Wu and S. Zheng, Well-posedness and long-time behavior of a non-autonomous Cahn–Hilliard–Darcy system with mass source modeling tumor growth. J. Differ. Equ. 259 (2015) 3032–3077. | MR | DOI

[20] H. Garcke, K. F. Lam, R. Nürnberg and E. Sitka, A multiphase Cahn–Hilliard–Darcy model for tumour growth with necrosis. Math. Models Methods Appl. Sci. 28 (2018) 525–577. | MR | DOI

[21] J. T. Oden, A. Hawkins and S. Prudhomme, General diffuse-interface theories and an approach to predictive tumor growth modeling. Math. Models Methods Appl. Sci. 20 (2010) 477–517. | MR | Zbl | DOI

[22] E. Rocca and R. Scala, A rigorous sharp interface limit of a diffuse interface model related to tumor growth. J. Nonlinear Sci. 27 (2017) 847–872. | MR | DOI

[23] D. Hilhorst, J. Kampmann, T. N. Nguyen and K. G. Van Der Zee, Formal asymptotic limit of a diffuse-interface tumor-growth model, Math. Models Methods Appl. Sci. 25 (2015) 1550026. | MR | DOI

[24] Z. Xu, X. Yang and H. Zhang, Error analysis of a decoupled, linear stabilization scheme for the Cahn-Hilliard model of two-phase incompressible flows. J. Sci. Comput. 83 (2020) 57. | MR | DOI

[25] L. Tang, A. L. Van De Ven, D. Guo, V. Andasari, V. Cristini, K. C. Li and X. Zhou, Computational modeling of 3D tumor growth and angiogenesis for chemotherapy evaluation. PLoS One 9 (2014) e83962. | DOI

[26] V. Mohammadi and M. Dehghan, Simulation of the phase field Cahn-Hilliard and tumor growth models via a numerical scheme: element-free Galerkin method. Comput. Methods Appl. Mech. Eng. 345 (2019) 919–950. | MR | DOI

[27] D. Ambrosi and F. Mollica, On the mechanics of a growing tumor. Int. J. Eng. Sci. 40 (2002) 1297–1316. | MR | Zbl | DOI

[28] L. Liu and M. Schlesinger, Interstitial hydraulic conductivity and interstitial fluid pressure for avascular or poorly vascularized tumors. J. Theor. Biol. 380 (2015) 1–8. | MR | DOI

[29] Y. Zheng, Y. X. Jiang and Y. P. Cao, Effects of interstitial fluid pressure on shear wave elastography of solid tumors. Extreme Mech. Lett. 47 (2021) 101366. | DOI

[30] L. Baxter and R. Jain, Transport of fluid and macro molecules in tumors 1. Role of interstitial pressure and convection. Microvasc. Res. 12 (1989) 77–104. | DOI

[31] P. A. Netti, D. A. Berk, M. A. Swartz, A. J. Grodzinsky and R. K. Jain, Role of extracellular matrix assembly in interstitial transport in solid tumors. Cancer Res. 60 (2000) 2497–2503.

[32] S. J. Lunt, T. M. Kalliomaki, A. Brown, V. X. Yang, M. Milosevic and R. P. Hill, Interstitial fluid pressure, vascularity and metastasis in ectopic, orthotopic and spontaneous tumours. BMC Cancer 8 (2008) 1–14.

[33] L. J. Liu, S. L. Brown, J. R. Ewing and M. Schlesinger, Phenomenological model of interstitial fluid pressure in a solid tumor. Phys. Rev. E 84 (2011) 021919. | DOI

[34] M. Milosevic, A. Fyles, D. Hedley, M. Pintilie, W. Levin, L. Manchul and R. Hill, Interstitial fluid pressure predicts survival in patients with cervix cancer independent of clinical prognostic factors and tumor oxygen measurements. Cancer Res. 61 (2001) 6400–6405.

[35] M. Sarntinoranont, F. Rooney and M. Ferrari, Interstitial stress and fluid pressure within a growing tumor. Ann. Biomed. Eng. 31 (2003) 327–335. | DOI

[36] S. Evje and J. O. Waldeland, How tumor cells can make use of interstitial fluid flow in a strategy for metastasis. Cell. Mol. Bioeng. 12 (2019) 227–254. | DOI

[37] M. Conti and A. Giorgini, Well-posedness for the Brinkman–Cahn–Hilliard system with unmatched viscosities. J. Differ. Equ. 268 (2020) 6350–6384. | MR | DOI

[38] F. Della Porta and M. Grasselli, On the nonlocal Cahn–Hilliard–Brinkman and Cahn–Hilliard–Hele–Shaw systems. Commun. Pure Appl. Anal. 15 (2016) 299–317. | MR | DOI

[39] J. Shen and X. Yang, Decoupled energy stable schemes for phase-field models of two-phase complex fluids. SIAM J. Sci. Comput. 36 (2014) B122–B145. | MR | Zbl | DOI

[40] J. Shen and X. Yang, Decoupled energy stable schemes for phase-field models of two-phase incompressible flows. SIAM J. Numer. Anal. 53 (2015) 279–296. | MR | DOI

[41] Y. Chen and J. Shen, Efficient, adaptive energy stable schemes for the incompressible Cahn-Hilliard Navier–Stokes phase-field models. J. Comput. Phys. 308 (2016) 40–56. | MR | DOI

[42] S. Minjeaud, An unconditionally stable uncoupled scheme for a triphasic Cahn–Hilliard/Navier–Stokes model. Numer. Methods Partial Differ. Equ. 29 (2013) 584–618. | MR | Zbl | DOI

[43] J. Zhao, H. Li, Q. Wang and X. Yang, Decoupled energy stable schemes for a phase field model of three-phase incompressible viscous fluid flow. J. Sci. Comput. 70 (2017) 1367–1389. | MR | DOI

[44] X. Yang, A new efficient fully-decoupled and second-order time-accurate scheme for Cahn-Hilliard phase-field model of three-phase incompressible flow. Comput. Methods Appl. Mech. Eng. 376 (2021) 113589. | MR | DOI

[45] X. Yang, On a novel fully-decoupled, linear and second-order accurate numerical scheme for the Cahn–Hilliard–Darcy system of two-phase Hele-Shaw flow. Comput. Phys. Commun. 263 (2021) 107868. | MR | DOI

[46] C. Collins, J. Shen and S. M. Wise, An efficient, energy stable scheme for the Cahn–Hilliard–Brinkman system. Commun. Comput. Phys. 13 (2013) 929–957. | MR | DOI

[47] A. Diegel, X. Feng and S. M. Wise, Analysis of a mixed finite element method for a Cahn–Hilliard–Darcy–Stokes system. SIAM J. Numer. Anal. 53 (2015) 127–152. | MR | DOI

[48] X. Feng and S. M. Wise, Analysis of a Darcy–Cahn–Hilliard diffuse interface model for the Hele-Shaw flow and its fully discrete finite element approximation. SIAM J. Numer. Anal. 50 (2012) 1320–1343. | MR | Zbl | DOI

[49] Y. Liu, W. B. Chen, C. Wang and S. M. Wise, Error analysis of a mixed finite element method for a Cahn–Hilliard–Hele–Shaw system. Numer. Math. 135 (2017) 679–709. | MR | DOI

[50] C. Chen and X. Yang, A Second-order time accurate and fully-decoupled numerical scheme of the Darcy–Newtonian–Nematic model for two-phase complex fluids confined in the Hele-Shaw cell. J. Comput. Phys. 456 (2022) 111026. | MR | DOI

[51] X. Yang, A novel decoupled second-order time marching scheme for the two-phase incompressible Navier–Stokes/Darcy coupled nonlocal Allen-Cahn model. Comput. Methods Appl. Mech. Eng. 377 (2021) 113597. | MR | DOI

[52] Y. Gao, X. He, L. Mei and X. Yang, Decoupled, linear, and energy stable finite element method for the Cahn–Hilliard–Navier–Stokes–Darcy phase field model. SIAM. J. Sci. Comput. 40 (2018) B110–B137. | MR | DOI

[53] D. N. Arnold, F. Brezzi, B. Cockburn and L. D. Marini, Unified analysis of discontinuous Galerkin methods for elliptic problems. SIAM J. Numer. Anal. 39 (2001) 1749–1779. | MR | Zbl | DOI

[54] B. Cockburn, G. E. Karniadakis and C.-W. Shu, The Development of Discontinuous Galerkin methods. Springer, Berlin Heidelberg (2000). | MR | Zbl | DOI

[55] B. Rivière, Discontinuous Galerkin Methods for Solving Elliptic and Parabolic Equations: Theory and Implementation. SIAM, Philadelphia (2008). | MR | Zbl | DOI

[56] G. N. Wells, E. Kuhl and K. Garikipati, A discontinuous Galerkin method for the Cahn-Hilliard equation. J. Comput. Phys. 218 (2006) 860–877. | MR | Zbl | DOI

[57] D. Kay, V. Styles and E. Süli, Discontinuous Galerkin finite element approximation of the Cahn-Hilliard equation with convection. SIAM J. Numer. Anal. 47 (2009) 2660–2685. | MR | Zbl | DOI

[58] A. C. Aristotelous, O. Karakashian and S. M. Wise, A mixed discontinuous Galerkin, convex splitting scheme for a modified Cahn-Hilliard equation and an efficient nonlinear multigrid solver. Discrete Cont. Dyn. Syst. B 18 (2013) 2211–2238. | MR | Zbl

[59] X. Feng and Y. Li, Analysis of symmetric interior penalty discontinuous Galerkin methods for the Allen-Cahn equation and the mean curvature flow. IMA J. Numer. Anal. 35 (2015) 1622–1651. | MR | DOI

[60] T. Ohta and K. Kawasaki, Equilibrium morphology of block copolymer melts. Macromolecules 9 (1986) 2621–2632. | DOI

[61] X. Wang, Q. Zhai and R. Zhang, The weak Galerkin method for solving the incompressible Brinkman flow. J. Comput. Appl. Math. 9 (2016) 13–24. | MR | DOI

[62] X. Yang and J. Zhao, On linear and unconditionally energy stable algorithms for variable mobility Cahn-Hilliard type equation with logarithmic Flory-Huggins potential. Commun. Comput. Phys. 25 (2019) 703–728. | MR | DOI

[63] X. Wang, J. Kou and J. Cai, Stabilized energy factorization approach for Allen-Cahn equation with logarithmic Flory-Huggins potential. J. Sci. Comput. 82 (2020) 1–23. | MR | DOI

[64] X. Feng and O. A. Karakashian, Fully discrete dynamic mesh discontinuous Galerkin methods for the Cahn-Hilliard equation of phase transition. Math. Comput. 76 (2007) 1093–1117. | MR | Zbl | DOI

[65] J. Xu, G. Vilanova and H. Gomez, Phase-field model of vascular tumor growth: three-dimensional geometry of the vascular network and integration with imaging data. Comput. Methods Appl. Mech. Eng. 359 (2020) 112648. | MR | DOI

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