» Articles » PMID: 35908096

Coupling Solid and Fluid Stresses with Brain Tumour Growth and White Matter Tract Deformations in a Neuroimaging-informed Model

Overview
Publisher Springer
Date 2022 Jul 30
PMID 35908096
Authors
Affiliations
Soon will be listed here.
Abstract

Brain tumours are among the deadliest types of cancer, since they display a strong ability to invade the surrounding tissues and an extensive resistance to common therapeutic treatments. It is therefore important to reproduce the heterogeneity of brain microstructure through mathematical and computational models, that can provide powerful instruments to investigate cancer progression. However, only a few models include a proper mechanical and constitutive description of brain tissue, which instead may be relevant to predict the progression of the pathology and to analyse the reorganization of healthy tissues occurring during tumour growth and, possibly, after surgical resection. Motivated by the need to enrich the description of brain cancer growth through mechanics, in this paper we present a mathematical multiphase model that explicitly includes brain hyperelasticity. We find that our mechanical description allows to evaluate the impact of the growing tumour mass on the surrounding healthy tissue, quantifying the displacements, deformations, and stresses induced by its proliferation. At the same time, the knowledge of the mechanical variables may be used to model the stress-induced inhibition of growth, as well as to properly modify the preferential directions of white matter tracts as a consequence of deformations caused by the tumour. Finally, the simulations of our model are implemented in a personalized framework, which allows to incorporate the realistic brain geometry, the patient-specific diffusion and permeability tensors reconstructed from imaging data and to modify them as a consequence of the mechanical deformation due to cancer growth.

Citing Articles

Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!.

Greiner A, Reiter N, Hinrichsen J, Kainz M, Sommer G, Holzapfel G Interface Focus. 2024; 14(6):20240026.

PMID: 39649453 PMC: 11620825. DOI: 10.1098/rsfs.2024.0026.


Simulating the impact of tumor mechanical forces on glymphatic networks in the brain parenchyma.

Siri S, Burchett A, Datta M Biomech Model Mechanobiol. 2024; 23(6):2229-2241.

PMID: 39298038 PMC: 11554883. DOI: 10.1007/s10237-024-01890-y.


Mechanical models and measurement methods of solid stress in tumors.

Bi Y, Jin J, Wang R, Liu Y, Zhu L, Wang J Appl Microbiol Biotechnol. 2024; 108(1):363.

PMID: 38842572 PMC: 11156757. DOI: 10.1007/s00253-024-13211-5.

References
1.
Ambrosi D, Mollica F . The role of stress in the growth of a multicell spheroid. J Math Biol. 2004; 48(5):477-99. DOI: 10.1007/s00285-003-0238-2. View

2.
Ehlers W, Wagner A . Multi-component modelling of human brain tissue: a contribution to the constitutive and computational description of deformation, flow and diffusion processes with application to the invasive drug-delivery problem. Comput Methods Biomech Biomed Engin. 2013; 18(8):861-79. DOI: 10.1080/10255842.2013.853754. View

3.
Tracqui P, Cruywagen G, Woodward D, Bartoo G, Murray J, Alvord Jr E . A mathematical model of glioma growth: the effect of chemotherapy on spatio-temporal growth. Cell Prolif. 1995; 28(1):17-31. DOI: 10.1111/j.1365-2184.1995.tb00036.x. View

4.
Balbi V, Trotta A, Destrade M, Ni Annaidh A . Poynting effect of brain matter in torsion. Soft Matter. 2019; 15(25):5147-5153. DOI: 10.1039/c9sm00131j. View

5.
Ellingson B, Nguyen H, Lai A, Nechifor R, Zaw O, Pope W . Contrast-enhancing tumor growth dynamics of preoperative, treatment-naive human glioblastoma. Cancer. 2016; 122(11):1718-27. DOI: 10.1002/cncr.29957. View