An asymptotic analysis and numerical simulation of a prostate tumor growth model via the generalized moving least squares approximation combined with semi-implicit time integration

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Vahid Mohammadi
  • Mehdi Dehghan
  • Amirreza Khodadadian
  • Nima Noii
  • Thomas Wick

Externe Organisationen

  • Amirkabir University of Technology
  • École normale supérieure Paris-Saclay (ENS Paris-Saclay)
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Details

OriginalspracheEnglisch
Seiten (von - bis)826-849
Seitenumfang24
FachzeitschriftApplied mathematical modelling
Jahrgang104
Frühes Online-Datum13 Dez. 2021
PublikationsstatusVeröffentlicht - Apr. 2022

Abstract

This paper focuses on presenting an asymptotic analysis and employing simulations of a model describing the growth of local prostate tumor (known as a moving interface problem) in two-dimensional spaces. We first demonstrate that the proposed mathematical model produces the diffuse interfaces with the hyperbolic tangent profile using an asymptotic analysis. Next, we apply a meshless method, namely the generalized moving least squares approximation for discretizing the model in the space variables. The main benefits of the developed meshless method are: First, it does not need a background mesh (or triangulation) for constructing the approximation. Second, the obtained numerical results suggest that the proposed meshless method does not need to be combined with any adaptive technique for capturing the evolving interface between the tumor and the neighboring healthy tissue with proper accuracy. A semi-implicit backward differentiation formula of order 1 is used to deal with the time variable. The resulting fully discrete scheme obtained here is a linear system of algebraic equations per time step solved by an iterative scheme based on a Krylov subspace, namely the generalized minimal residual method with zero–fill incomplete lower–upper preconditioner. Finally, some simulation results based on estimated and experimental data taken from the literature are presented to show the process of prostate tumor growth in two-dimensional tissues, i.e., a square, a circle and non-convex domains using both uniform and quasi-uniform points.

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An asymptotic analysis and numerical simulation of a prostate tumor growth model via the generalized moving least squares approximation combined with semi-implicit time integration. / Mohammadi, Vahid; Dehghan, Mehdi; Khodadadian, Amirreza et al.
in: Applied mathematical modelling, Jahrgang 104, 04.2022, S. 826-849.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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title = "An asymptotic analysis and numerical simulation of a prostate tumor growth model via the generalized moving least squares approximation combined with semi-implicit time integration",
abstract = "This paper focuses on presenting an asymptotic analysis and employing simulations of a model describing the growth of local prostate tumor (known as a moving interface problem) in two-dimensional spaces. We first demonstrate that the proposed mathematical model produces the diffuse interfaces with the hyperbolic tangent profile using an asymptotic analysis. Next, we apply a meshless method, namely the generalized moving least squares approximation for discretizing the model in the space variables. The main benefits of the developed meshless method are: First, it does not need a background mesh (or triangulation) for constructing the approximation. Second, the obtained numerical results suggest that the proposed meshless method does not need to be combined with any adaptive technique for capturing the evolving interface between the tumor and the neighboring healthy tissue with proper accuracy. A semi-implicit backward differentiation formula of order 1 is used to deal with the time variable. The resulting fully discrete scheme obtained here is a linear system of algebraic equations per time step solved by an iterative scheme based on a Krylov subspace, namely the generalized minimal residual method with zero–fill incomplete lower–upper preconditioner. Finally, some simulation results based on estimated and experimental data taken from the literature are presented to show the process of prostate tumor growth in two-dimensional tissues, i.e., a square, a circle and non-convex domains using both uniform and quasi-uniform points.",
keywords = "Asymptotic analysis, Generalized minimal residual method, Generalized moving least squares approximation, Mathematical oncology, Prostate tumor growth model",
author = "Vahid Mohammadi and Mehdi Dehghan and Amirreza Khodadadian and Nima Noii and Thomas Wick",
note = "Funding Information: We wish to express our deep gratitude to anonymous reviewers for their helpful comments, which have significantly improved the quality of the paper. We also appreciate the Associate Editor for giving useful comments and suggestions to improve some parts of the paper related to the non-dimensional form of the mathematical model and the proposed analysis given in Section 3.",
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T1 - An asymptotic analysis and numerical simulation of a prostate tumor growth model via the generalized moving least squares approximation combined with semi-implicit time integration

AU - Mohammadi, Vahid

AU - Dehghan, Mehdi

AU - Khodadadian, Amirreza

AU - Noii, Nima

AU - Wick, Thomas

N1 - Funding Information: We wish to express our deep gratitude to anonymous reviewers for their helpful comments, which have significantly improved the quality of the paper. We also appreciate the Associate Editor for giving useful comments and suggestions to improve some parts of the paper related to the non-dimensional form of the mathematical model and the proposed analysis given in Section 3.

PY - 2022/4

Y1 - 2022/4

N2 - This paper focuses on presenting an asymptotic analysis and employing simulations of a model describing the growth of local prostate tumor (known as a moving interface problem) in two-dimensional spaces. We first demonstrate that the proposed mathematical model produces the diffuse interfaces with the hyperbolic tangent profile using an asymptotic analysis. Next, we apply a meshless method, namely the generalized moving least squares approximation for discretizing the model in the space variables. The main benefits of the developed meshless method are: First, it does not need a background mesh (or triangulation) for constructing the approximation. Second, the obtained numerical results suggest that the proposed meshless method does not need to be combined with any adaptive technique for capturing the evolving interface between the tumor and the neighboring healthy tissue with proper accuracy. A semi-implicit backward differentiation formula of order 1 is used to deal with the time variable. The resulting fully discrete scheme obtained here is a linear system of algebraic equations per time step solved by an iterative scheme based on a Krylov subspace, namely the generalized minimal residual method with zero–fill incomplete lower–upper preconditioner. Finally, some simulation results based on estimated and experimental data taken from the literature are presented to show the process of prostate tumor growth in two-dimensional tissues, i.e., a square, a circle and non-convex domains using both uniform and quasi-uniform points.

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KW - Generalized minimal residual method

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