Simulation of Multispecies Desmoplastic Cancer Growth via a Fully Adaptive Non-linear Full Multigrid Algorithm

A fully adaptive non-linear full multigrid (FMG) algorithm is implemented to computationally simulate a model of multispecies desmoplastic tumor growth in three spatial dimensions. The algorithm solves a thermodynamic mixture model employing a diffuse interface approach with Cahn-Hilliard-type fourt...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Frontiers in physiology Ročník 9; s. 821
Hlavní autori: Ng, Chin F., Frieboes, Hermann B.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland Frontiers Media S.A 12.07.2018
Predmet:
adaptive mesh refinement
cancer
computational simulation
diffuse interface model
mathematical model
non-linear 3D tumor growth
Physiology
computational simulation
diffuse interface model
non-linear 3D tumor growth
mathematical model
cancer
adaptive mesh refinement
full multigrid
full approximation scheme
ISSN:1664-042X, 1664-042X
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:A fully adaptive non-linear full multigrid (FMG) algorithm is implemented to computationally simulate a model of multispecies desmoplastic tumor growth in three spatial dimensions. The algorithm solves a thermodynamic mixture model employing a diffuse interface approach with Cahn-Hilliard-type fourth-order equations that are coupled, non-linear, and numerically stiff. The tumor model includes extracellular matrix (ECM) as a major component with elastic energy contribution in its chemical potential term. Blood and lymphatic vasculatures are simulated via continuum representations. The model employs advection-reaction-diffusion partial differential equations (PDEs) for the cell, ECM, and vascular components, and reaction-diffusion PDEs for the elements diffusing from the vessels. This study provides the details of the numerical solution obtained by applying the fully adaptive non-linear FMG algorithm with finite difference method to solve this complex system of PDEs. The results indicate that this type of computational model can simulate the extracellular matrix-rich desmoplastic tumor microenvironment typical of fibrotic tumors, such as pancreatic adenocarcinoma.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Edited by: Luca Mesin, Politecnico di Torino, Italy
This article was submitted to Computational Physiology and Medicine, a section of the journal Frontiers in Physiology
Reviewed by: Luigi Preziosi, Politecnico di Torino, Italy; Silvina Ponce Dawson, Universidad de Buenos Aires, Argentina
ISSN:1664-042X
1664-042X
DOI:10.3389/fphys.2018.00821