on a nonlinear model for tumor growth global existence of
play

On a nonlinear model for tumor growth: Global existence of weak - PowerPoint PPT Presentation

Tumor Growth On a nonlinear model for tumor growth: Global existence of weak solutions Hamiltonian PDEs: Analysis, Computations and Applications, Fields Institute Konstantina Trivisa January 10-12, 2014 Tumor Growth Collaborators 1 Donatella


  1. Tumor Growth On a nonlinear model for tumor growth: Global existence of weak solutions Hamiltonian PDEs: Analysis, Computations and Applications, Fields Institute Konstantina Trivisa January 10-12, 2014

  2. Tumor Growth Collaborators 1 Donatella Donatelli Supported in part by the 1 National Science Foundation 2 Simons Foundation

  3. Tumor Growth Outline I. On a nonlinear model for tumor growth 1 Motivation - Modeling Governing equations Boundary conditions 2 Strategy Generalized penalty methods - Penalization scheme Penalization of boundary behavior ε Penalization of diffusion and viscosity ω 3 Energy estimates 4 Singular limits: ε → 0 and ω → 0 5 Level set method and the evolution of the interface Γ t . II. Current and future directions: What are the challenges?

  4. Tumor Growth A two-phase flow model Tumor: a growing continuum Ω( t ) with boundary ∂ Ω( t ), both of which evolve in time. The tumor region Ω t := Ω( t ) is contained in a fixed domain B and the region B \ Ω t represents the healthy tissue. Tumor " ( t ) B Healthy Region Figure: Healthy tissue - Tumor regime.

  5. Tumor Growth Modeling Tumor: living cells and dead cells in the presence of a nutrient. 1 Living cells in proliferating phase or in a quiescent phase . Three types of cells: proliferative cells with density P , quiescent cells with density Q and dead cells with density D in the presence of a nutrient with density C . 2 Proliferating cells die as a result of apoptosis which is a cell-loss mechanism. Quiescent cells die in part due to apoptosis but mostly due to starvation. 3 Living cells undergo mitosis , a process that takes place in the nucleus of a dividing cell, but for proliferating cells the period of cell cycle is much shorter.

  6. Tumor Growth The rates of change from one phase to another are functions of the nutrient concentration C: P → Q at rate K Q ( C ) , Q → P at rate K P ( C ) , P → D at rate K A ( C ) , Q → D at rate K D ( C ) , where K A stands for apoptosis. Finally, dead cells are removed at rate K R (independent of C ), and the rate of cell proliferation (new births) is K B .

  7. Tumor Growth There is continuous motion of cells within the tumor. This motion is characterized by the velocity field v , which is given by an extension of Darcy’s Law known in the literature as Brinkman’s equation ∇ σ = − µ K v + µ ∆ v (1) where σ represents the pressure, µ the viscosity and K the permeability.

  8. Tumor Growth Governing equations of cells and nutrient All the cells are assumed to follow the general continuity equation: ∂̺ ∂ t + ∇ · ( ̺ v ) = G ̺ , where ̺ may represent densities of proliferating, quiescent and dead cells. The function G includes in general proliferation, apoptosis or clearance of cells, and chemotaxis terms as appropriate.

  9. Tumor Growth The mass conservation laws for the densities of the proliferative cells P , quiescent cells Q and dead cells D in Ω( t ) take the following form: ∂ P ∂ t + div( P v ) = G P , (2) ∂ Q ∂ t + div( Q v ) = G Q , (3) ∂ D ∂ t + div( D v ) = G D , (4)

  10. Tumor Growth with  K B C − K Q (¯ C − C ) − K A (¯ � � G P = C − C ) P + K P CQ   G Q = K Q (¯ K P C + K D (¯ � � (5) C − C ) P − C − C ) Q G D = K A (¯ C − C ) P + K D (¯  C − C ) Q − K R D .  Tumor cells consume nutrients. Nutrients diffuse into the tumor tissue from the surrounding tissue. The nutrient concentration C satisfies a linear diffusion equation of the form ∂ C K 1 K P CP + K 2 K Q ( C − ¯ � � ∂ t = D 1 ∆ C − C ) Q C .

  11. Tumor Growth Without loss of generality, in this paper we will consider { G P , G Q , G D } in the following simplified version: K B C − K Q (¯ C − C ) − K A (¯  � � G P = C − C ) P   K P C + K D (¯ � � G Q = − C − C ) (6) Q  G D = − K R D .  and for simplicity, we take (cf. Friedman 2004) , ∂ C ∂ t = ν ∆ C − K C C , (7) where ν > 0 is a diffusion coefficient and without loss of generality we consider K C = 1.

  12. Tumor Growth The total density of the mixture is denoted by ̺ f and is given by ̺ f = P + Q + D = Constant . (8) Adding (2)-(4) and taking into consideration (6)-(8) we arrive at the following relation, which represents an additional constraint ρ f div v = G P + G Q + G D =( K A + K B + K Q ) CP − ( K A + K Q )¯ CP − K D ¯ CQ + ( K D − K P ) C − K R D . (9)

  13. Tumor Growth Boundary The boundary of the domain Ω t occupied by the tumor is described by means of a given velocity V ( t , x ) , where t ≥ 0 and x ∈ R 3 . More precisely, assuming V is regular, we solve the associated system of differential equations d dt X ( t , x ) = V ( t , X )( t , x ) , t > 0 , X (0 , x ) = x , and set � Ω τ = X ( τ, Ω 0 ) , where Ω 0 ⊂ R 3 is a given domain, Γ τ = ∂ Ω τ , and Q τ = { ( t , x ) | t ∈ (0 , τ ) , x ∈ Ω τ } .

  14. Tumor Growth We assume that the boundary Γ τ is impermeable, meaning ( v − V ) · n | Γ τ = 0 , for any τ ≥ 0 . (10) In addition, for viscous fluids, Navier proposed the boundary condition of the form [ S n ]tan | Γ τ = 0 , (11) with S denoting the viscous stress tensor which in this context is assumed to be determined through Newton’s rheological law ∇ v + ∇ ⊥ v − 2 � � S = µ 3 div v I + ξ div v I , where µ > 0, ξ ≥ 0 are respectively the shear and bulk viscosity coefficients.

  15. Tumor Growth Our aim is to show existence of global in time weak solutions to problem for any finite energy initial data. Related works on the mathematical analysis of cancer: Friedman et al. (2004), Zhao (2010) ( radially symmetric case ) In the above articles the tumor tissue is assumed to be a porous medium and the velocity field is determined by Darcy’s Law v = −∇ x σ in Ω( t ) . Smooth solutions: Friedman et al. (2004) (small time solutions) Zhao (2010) (global, unique solution)

  16. Tumor Growth General Strategy Penalization: of the boundary behavior , diffusion and viscosity in the weak formulation. Penalization of the boundary behavior The variational (weak) formulation of the Brinkman equation is supplemented by a singular forcing term � T 1 � ( v − V ) · n ϕ · n dS x dt , ε > 0 small , (12) ε 0 Γ t penalizing the normal component of the velocity on the boundary of the tumor domain.

  17. Tumor Growth Penalization of the diffusion and viscosity We introduce a variable shear viscosity coefficient µ = µ ω , as well as a variable diffusion ν = ν ω with µ ω , ν ω vanishing outside the tumor domain and remaining positive within the tumor domain. In constructing the approximating problem we employ the variables ε and ω. Keeping ε and ω fixed, we solve the modified problem in a (bounded) reference domain B ⊂ R 3 chosen in such way that ¯ Ω τ ⊂ B for any τ ≥ 0 .

  18. Tumor Growth We take the initial densities ( P 0 , Q 0 , D 0 ) vanishing outside Ω 0 , and letting ε → 0 for fixed ω > 0 we obtain a “two-phase” model consisting of the tumor region and the healthy tissue . Moreover, we prove that that the densities of cancerous cells vanish in part of the reference domain, namely ((0 , T ) × B ) \ Q T . Specifically, we show that � ( P , Q , D )( τ, · ) B \ Ω τ = 0 for any τ ∈ [0 , T ] . �

  19. Tumor Growth Weak solutions Definition 1. We say that ( P , Q , D , v , C ) is a weak solution of problem supplemented with boundary data satisfying (10)-(11) and initial data ( P 0 , Q 0 , D 0 , v 0 , C 0 ) provided that the following hold: • ̺ = ( P , Q , D ) ≥ 0 represents a weak solution of (2)-(3)-(4) on (0 , ∞ ) × Ω, i.e., for any test function ϕ ∈ C ∞ c (([0 , T ) × R 3 ) , T > 0 � � ̺ϕ ( τ, · ) dx − ̺ 0 ϕ (0 , · ) dx = Ω τ Ω 0 � τ � ( ̺∂ t ϕ + ̺ v · ∇ x ϕ + G ̺ ϕ ( t , · )) dxdt , 0 Ω t In particular, ̺ = ( P , Q , D ) ∈ L ∞ ([0 , T ]; L 2 (Ω)) .

  20. Tumor Growth • Brinkman’s equation (1) holds in the sense of distributions, i.e., for any test function ϕ ∈ C ∞ c ( R 3 ; R 3 ) satisfying ϕ · n | Γ τ = 0 for any τ ∈ [0 , T ] , the following integral relation holds � � µ ∇ x v : ∇ x ϕ + µ � � σ div ϕ dx − K v ϕ dx = 0 . (13) Ω τ Ω τ All quantities in (13) are required to be integrable, so in particular, v ∈ W 1 , 2 ( R 3 ; R 3 ) , and ( v − V ) · n ( τ, · ) | Γ τ = 0 for a.a. τ ∈ [0 , T ] .

  21. Tumor Growth • C ≥ 0 is a weak solution of (7), i.e., for any test function ϕ ∈ C ∞ c (([0 , T ) × R 3 ) , T > 0 the following integral relations hold � � C ϕ ( τ, · ) dx − C 0 ϕ (0 , · ) dx = Ω τ Ω 0 � τ � τ � � C ∂ t ϕ dxdt + ν ∇ x C ∇ x ϕ dxdt 0 Ω τ 0 Ω t � τ � − C ϕ ( τ, · ) dxdt . 0 Ω t

  22. Tumor Growth Theorem Let Ω 0 ⊂ R 3 be a bounded domain of class C 2+ ν and let V ∈ C 1 ([0 , T ]; C 3 c ( R 3 ; R 3 )) be given. Let the initial data satisfy P 0 ∈ L 2 ( R 3 ) , Q 0 ∈ L 2 ( R 3 ) , D 0 ∈ L 2 ( R 3 ) , C 0 ∈ L 2 ( R 3 ) , ( P 0 , Q 0 , D 0 , C 0 ) ≥ 0 , ( P 0 , Q 0 , D 0 , C 0 ) �≡ 0 ( P 0 , Q 0 , D 0 , C 0 ) | R 3 \ Ω 0 = 0 . Then the problem (2) - (11) with initial data as specified earlier and boundary data (10) - (11) admits a weak solution in the sense specified in Definition.

Recommend


More recommend