Your browser doesn't support javascript.
loading
Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect.
Subramanian, Shashank; Gholami, Amir; Biros, George.
Afiliação
  • Subramanian S; Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX, 78712, USA. shashanksubramanian@utexas.edu.
  • Gholami A; Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, CA, 94720, USA.
  • Biros G; Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX, 78712, USA.
J Math Biol ; 79(3): 941-967, 2019 08.
Article em En | MEDLINE | ID: mdl-31127329
In this article, we present a multispecies reaction-advection-diffusion partial differential equation coupled with linear elasticity for modeling tumor growth. The model aims to capture the phenomenological features of glioblastoma multiforme observed in magnetic resonance imaging (MRI) scans. These include enhancing and necrotic tumor structures, brain edema and the so-called "mass effect", a term-of-art that refers to the deformation of brain tissue due to the presence of the tumor. The multispecies model accounts for proliferating, invasive and necrotic tumor cells as well as a simple model for nutrition consumption and tumor-induced brain edema. The coupling of the model with linear elasticity equations with variable coefficients allows us to capture the mechanical deformations due to the tumor growth on surrounding tissues. We present the overall formulation along with a novel operator-splitting scheme with components that include linearly-implicit preconditioned elliptic solvers, and a semi-Lagrangian method for advection. We also present results showing simulated MRI images which highlight the capability of our method to capture the overall structure of glioblastomas in MRIs.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Simulação por Computador / Neoplasias Encefálicas / Imageamento por Ressonância Magnética / Glioblastoma / Imageamento Tridimensional / Modelos Teóricos Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: J Math Biol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Simulação por Computador / Neoplasias Encefálicas / Imageamento por Ressonância Magnética / Glioblastoma / Imageamento Tridimensional / Modelos Teóricos Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: J Math Biol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Alemanha