Abstract
Existing continuum multiphase tumor growth models typically do not include microvasculature, or if present, this is modeled as a non-deformable network of vessels. Vasculature behavior and blood flow are usually non-coupled with the underlying tumor phenomenology from the mechanical viewpoint; hence, phenomena like vessel compression/occlusion modifying microcirculation and oxygen supply cannot be taken into account. Here, the tumor tissue is modeled as a reactive bi-compartment porous medium: the extracellular matrix constitutes the solid scaffold; blood flows in the vascular porosity, whereas the extravascular porous compartment is saturated by two cell phases and interstitial fluid (mixture of water and nutrient species). The pressure difference between blood and the extravascular overall pressure is sustained by vessel walls and drives shrinkage or dilatation of the vascular porosity. Model closure is achieved thanks to a consistent non-conventional definition of the Biot’s effective stress tensor. Angiogenesis is modeled by introducing a vascularization state variable and accounting for tumor angiogenic factors and endothelial cells. Closure relationships and mass exchange terms related to vessel formation are detailed in a numerical example reproducing the principal features of angiogenesis. This example is preceded by a first pedagogical numerical study on one-dimensional bio-consolidation. Results demonstrate that the bi-compartment poromechanical model is fully coupled (the external loads impact fluid flow in both porous compartments) and that it can serve as a basis for further applications like modeling of drug delivery and tissue ulceration.
Similar content being viewed by others
References
Michor, F., Liphardt, J., Ferrari, M., Widom, J.: What does physics have to do with cancer? Nat. Rev. Cancer 11(9), 657–670 (2013)
Dusheck, J.: Oncology: getting physical. Nature 491, S50–S51 (2012)
Jonietz, E.: Mechanics: the forces of cancer. Nature 491(7425), S56 (2012)
Ferrari, M.: Frontiers in cancer nanomedicine: directing mass transport through biological barriers. Trends Biotechnol. 28(4), 181–8 (2010)
Jain, R.K., Martin, J.D., Stylianopoulos, T.: The role of mechanical forces in tumor growth and therapy. Annu. Rev. Biomed. Eng. 16, 321–46 (2014)
Vilanova, G., Colominas, I., Gomez, H.: A mathematical model of tumour angiogenesis: growth, regression and regrowth. J. R. Soc. Interface 14, 20160918 (2017)
Santagiuliana, R., Ferrari, M., Schrefler, B.: Simulation of angiogenesis in a multiphase tumor growth model. Comput. Methods Appl. Mech. Eng. 304, 197 (2016)
Kremheller, J., Vuong, A.T., Schrefler, B., Wall, W.: An approach for vascular tumor growth based on a hybrid embedded/homogenized treatment of the vasculature within a multiphase porous medium model. Int. J. Numer. Methods Biomed. Eng. 35, e3253 (2019)
Scianna, M., Bell, C.G., Preziosi, L.: A review of mathematical models for the formation of vascular networks. J. Theor. Biol. 333, 174 (2013)
Sciumè, G., Gray, W.G., Ferrari, M., Decuzzi, P., Schrefler, B.A.: On computational modeling in tumor growth. Arch. Comput. Methods Eng. 20(4), 327–52 (2013)
Gray, W.G., Miller, C.T.: Introduction to the Thermodynamically Constrained Averaging Theory for Porous Medium Systems. Springer, Berlin (2014)
Sciumè, G., Shelton, S., Gray, W.G., Miller, C.T., Hussain, F., Ferrari, M., Decuzzi, P., Schrefler, B.: A multiphase model for three-dimensional tumor growth. New J. Phys. 15, 015005 (2013)
Sciumè, G., Ferrari, M., Schrefler, B.A.: Saturation-pressure relationships for two- and three-phase flow analogies for soft matter. Mech. Res. Commun. 62, 132 (2014)
Sciumè, G., Gray, W.G., Hussain, F., Ferrari, M., Decuzzi, P., Schrefler, B.A.: Three phase flow dynamics in tumor growth. Comput. Mech. 53(3), 465 (2014)
Sciumè, G., Santagiuliana, R., Ferrari, M., Decuzzi, P., Schrefler, B.A.: A tumor growth model with deformable ECM. Phys. Biol. 11(6), 065004 (2014)
Bearer, E.L., Lowengrub, J., Frieboes, H.B., Chuang, Y.L., Jin, F., Wise, S.M., Ferrari, M., Agus, D.B., Cristini, V.: Multiparameter computational modeling of tumor invasion. Cancer Res. 69(10), 4493–501 (2009)
Sciumè, G.: A hierarchical multi-compartment porous medium system for evolution of tumor microenvironment during avascular and vascular growth. In: ALERT Workshop 2017 (ALERT GEOMATERIALS—The Alliance of Laboratories in Europe for Education, Research and Technology, 2017). http://alertgeomaterials.eu/presentations-of-the-alert-workshop-2017/ (2017)
Sciumè, G.: A two-compartment hierarchical porous medium system for vascular tumor growth: theory and implementation in Cast3M. In: Club Cast3M 2017 (CEA— French Atomic Energy and Alternative Energy Commission, 2017). http://www-cast3m.cea.fr/index.php?xml=clubcast3m2017 (2017)
Kremheller, J., Vuong, A.T., Yoshihara, W., Schrefler, B., Wall, W.: A monolithic multiphase porous medium framework for (a-)vascular tumor growth. Comput. Methods Appl. Mech. Eng. 340, 657 (2018)
Lewis, R.W., Schrefler, B.A.: The Finite Element Method in the Static and Dynamic Deformation and Consolidation of Porous Media, 2nd, Edition edn. Wiley, Hoboken (1998)
Le Maout, V.D., Alessandri, K., Gurchenkov, B., Bertin, h, Nassoy, P., Sciumè, G.: Role of mechanical cues and hypoxia on the growth of tumor cells in strong and weak confinement: a dual in vitro–in silico approach. Sci. Adv. 6, eaaz7130 (2020)
Anderson, A.R.A., Chaplain, M.A.J.: Continuous and discrete mathematical models of tumor-induced angiogenesis. Bull. Math. Biol. 60, 857–899 (1998)
Anderson, A., Chaplain, M.: Continuous and discrete mathematical models of tumor-induced angiogenesis. Bull. Math. Biol. 60(5), 857 (1998)
Heldin, C.H., Rubin, K., Pietras, K., Ostman, A.: High interstitial fluid pressure: an obstacle in cancer therapy. Nat. Rev. Cancer 10, 806–813 (2004)
Jain, R.: Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy. Science 307(5706), 58 (2005)
Baxter, L., Jain, R.: Transport of fluid and macromolecules in tumors. I. Role of interstitial pressure and convection. Microvasc. Res. 37(1), 77 (1989)
Baxter, L., Jain, R.: Transport of fluid and macromolecules in tumors. II. Role of heterogeneous perfusion and lymphatics. Microvasc. Res. 40(2), 246 (1990)
Urcun, S., Rohan, P.Y., Skalli, W., Nassoy, P., Bordas, S.P., Sciumè, G.: Quantifying the role of mechanics in the free and encapsulated growth of cancer spheroids, bioRxiv (2020). https://doi.org/10.1101/2020.06.09.142927. https://www.biorxiv.org/content/early/2020/06/11/2020.06.09.142927
Alessandri, K., Sarangi, B.R., Gurchenkov, V.V., Sinha, B., Kießling, T.R., Fetler, L., Rico, F., Scheuring, S., Lamaze, C., Simon, A., Geraldo, S., Vignjević, D., Doméjean, H., Rolland, L., Funfak, A., Bibette, J., Bremond, N., Nassoy, P.: Cellular capsules as a tool for multicellular spheroid production and for investigating the mechanics of tumor progression in vitro. Proc. Natl. Acad. Sci. 110(37), 14843 (2013)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix: Chemotactic-Fickian model for EC diffusive velocity
Appendix: Chemotactic-Fickian model for EC diffusive velocity
Let us assume that all non-endothelial cell species (e.g., non-endothelial host cells, chemical species, etc.) can be modeled jointly as a species named H, the dominant species in h. Consequently let us treat species E as a diluted species in h. For such a situation, neglecting body forces potential and assuming isothermal condition, TCAT [11] provides from simplified entropy inequality the following force–flux pair:
where \(\theta\) is the temperature and \(\nabla {\mu ^{\overline{Eh}}}\) and \(\nabla {\mu ^{\overline{Hh}}}\) are the chemical potentials of endothelial and non-endothelial species, respectively. At equilibrium, both force and flux terms are zero. Conversely, near equilibrium a first-order closure approximation for the force–flux relationship reads
where \({{\mathbf{D}}^{Eh}}\) is a second-order symmetric tensor, and \({\chi ^{\overline{\overline{ih}}}}\) is the molar fraction of species i. The Gibbs–Duhem equation for this binary mixture reads
The expected pressure gradient in the phase h is relatively weak. Hence, for the isothermal case considered, Eq. (93) reduces for a binary mixture to
Equation (94) allows us to obtain the gradient of the chemical potential of species H as
With \({\omega ^{\overline{Eh} }} \ll {\omega ^{\overline{Hh} }}\) it follows that \(\nabla {\mu ^{\overline{Hh} }} \ll \nabla {\mu ^{\overline{Eh} }}\) and consequently Eq. (92) reduces to
To gain usefulness of the previous equation, a relationship between the macroscale chemical potential of species E and its mass fraction is needed. The macroscale chemical potential for the species E can be written as
where \(\mu _0^{\overline{Eh} }\left( {{p^h},\theta } \right)\) is a reference chemical potential for species E, R is the ideal gas constant, \(M_E\) is the molar mass of species E, and \({\gamma ^{\overline{\overline{Eh}} }}\) is the macroscale activity coefficient. With the system in isothermal condition (\(\theta = {\theta _0}\)) and the impact of pressure gradient of phase h assumed negligible, differentiating this expression in space gives
For dilute species, the macroscale activity coefficient is usually assumed constant and equal to 1. To account for chemotaxis we set here an activity coefficient linearly dependent on the mass fraction of TAF in h. We assume here local chemical equilibrium, so despite the mass fraction of TAF in h, \({\omega ^{\overline{Ah}}}\), not being a primary variable of the model, its value can be linearly related (as a first approximation) to the mass fraction of TAF in the adjacent IF phase, \({\omega ^{\overline{Ah}}}\propto {\omega ^{\overline{Al}}}\). This allows us to assume that the activity coefficient, \({\gamma ^{\overline{\overline{Eh}} }}\), is linearly dependent on the mass fraction of TAF in l. Thanks to short-range diffusion and molecular signaling the TAF in the phase l interferes (via the hl interface) with endothelial cells modifying their activity coefficient. The following relationship is assumed, with c the constant chemotactic coefficient and \({\chi ^{\overline{\overline{Al}}}}\) the molar fraction of TAF in IF:
Introducing Eq. (99) into Eq. (98) gives
We reasonably assume here that the molar masses of phases h and l are weakly affected by variation of species concentration. This allows us to assume constant molar masses of phases h and l and to express the molar fraction of the species E, A and H as functions of the respective mass fractions:
Introducing the first two relationships of Eq. (101) into Eq. (100) and setting \(C = c\frac{{{M_l}}}{{{M_A}}}\) gives
We now introduce Eq. (102) into Eq. (96) and express \({\chi ^{\overline{\overline{i\alpha }} }}\) as function of \({\omega ^{\overline{i\alpha } }}\). After some calculations, we obtain
As shown in the previous equation, some quantities are expected to stay almost constant, resulting in always \({\omega ^{\overline{Hh} }} \cong 1\). This observation allows us to rewrite the previous equation in a simplified form
where the diffusivity tensor \({{{\hat{\mathbf{D}}}}^{Eh}}\) reads
We assume here an isotropic effective diffusivity which linearly increases with the volume fraction of phase h. Therefore, Eq. (104) can be rewritten in the form
where indicating with \(D_0^{\overline{Eh}}\) the bulk diffusivity of endothelial cells in h, the effective diffusivity reads
Rights and permissions
About this article
Cite this article
Sciumè, G. Mechanistic modeling of vascular tumor growth: an extension of Biot’s theory to hierarchical bi-compartment porous medium systems. Acta Mech 232, 1445–1478 (2021). https://doi.org/10.1007/s00707-020-02908-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00707-020-02908-z