We are analyzing https://link.springer.com/article/10.1007/s00466-024-02471-7.

Title:
Modelling and simulation of anisotropic growth in brain tumours through poroelasticity: A study of ventricular compression and therapeutic protocols | Computational Mechanics
Description:
Malignant brain tumours represent a significant medical challenge due to their aggressive nature and unpredictable locations. The growth of a brain tumour can result in a mass effect, causing compression and displacement of the surrounding healthy brain tissue and possibly leading to severe neurological complications. In this paper, we propose a multiphase mechanical model for brain tumour growth that quantifies deformations and solid stresses caused by the expanding tumour mass and incorporates anisotropic growth influenced by brain fibres. We employ a sharp interface model to simulate localised, non-invasive solid brain tumours, which are those responsible for substantial mechanical impact on the surrounding healthy tissue. By using patient-specific imaging data, we create realistic three-dimensional brain geometries and accurately represent ventricular shapes, to evaluate how the growing mass may compress and deform the cerebral ventricles. Another relevant feature of our model is the ability to simulate therapeutic protocols, facilitating the evaluation of treatment efficacy and guiding the development of personalized therapies for individual patients. Overall, our model allows to make a step towards a deeper analysis of the complex interactions between brain tumours and their environment, with a particular focus on the impact of a growing cancer on healthy tissue, ventricular compression, and therapeutic treatment.
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Keywords {🔍}

mathbb, tumour, omega, brain, growth, article, google, scholar, model, text, tissue, tensor, phi, partial, endaligned, diffusion, beginaligned, time, fluid, grad, solid, left, cdot, mass, anisotropic, cell, int, boundary, data, cancer, ventricles, textrmt, mechanical, textrms, healthy, tumours, volume, anisotropy, initial, phase, ell, days, mathscinet, pressure, stress, mathematical, lambda, directions, values, deformation,

Topics {✒️}

=\frac{g_{\textrm{max}}-g_{\textrm{mid}}}{g_{\textrm{max}}+g_\textrm{mid}+g_{\textrm{min}}} =\frac{3 g_\textrm{min}}{g_{\textrm{max}}+g_{\textrm{mid}}+g_{\textrm{min}}} g_\textrm{min}=\min {\left\{ g_1 g_{\textrm{max}}=\max {\left\{ g_1 }}-\phi _{\textrm{sn}}}{1-\phi _{\textrm{sn}}}} }{2}\frac{\phi _{\textrm{sn}}^2-\phi _{\textrm{ }}-1}{1-\phi _{\textrm{sn}}}-\ln {\frac{j_{\textrm{ $$\begin{aligned}&-\int _{\omega _{\textrm{ $$\begin{aligned}&\int _{\omega _{\textrm{ =k_{0}\left[ \frac{\phi _{\textrm{sn}}\left 1-\frac{1-\phi _{\textrm{sn}}}{j_{\textrm{ }}{\dot{\phi }}_{\textrm{sn}}+j_{\textrm{ $$\begin{aligned}&-\int _{\omega ^{}}\left $$\begin{aligned}&\int _{\omega ^{}}\left lambda _{\textrm{mid}} = {\left\{ \begin{array}{ll}k_{ phi _{\textrm{sn}}=j_{\textrm{ phi _{\textrm{sn}} =j_{\textrm{ }_{\textrm{nfw}}}-\textrm{fa}_{\mathbb { $$\begin{aligned}&\dot{\overline{j_{\textrm{ $$\begin{aligned} {\tilde{\lambda }}_i ^{}=\int _{\omega _{\textrm{ ^{}&=-\int _{\omega _{\textrm{ g_{\textrm{mid}} phi _{\textrm{max}} _{\partial \omega _{\textrm{ lambda _1-\lambda _2 lambda _1-\lambda _3 $$\begin{aligned} \phi _{\textrm{ lambda _2-\lambda _3 dfrac{{\tilde{\lambda }}_i^ $$\begin{aligned} {\text {tr}}\left }}}_{\textrm{sn}}^\omega \left a_{\text {mid}} }}={\hat{\rho }}_{\mathrm{\ell }} $$\begin{aligned} \frac{{\dot{ }{{\tilde{\lambda }}_1 {\tilde{ +{\tilde{\lambda }}_2 {\tilde{ +{\tilde{\lambda }}_3{\tilde{ +{\tilde{\lambda }}_3 {\tilde{ a_\textrm{mid} a_{\textrm{mid}} a_{\text {min}} end{aligned}\nonumber \\ \end{aligned}$$ }}_1}{g_1} + \frac{{\dot{ 1-\phi _{\textrm{sn}} phi _{\textrm{sn}} 1-\phi _{\textrm{sn}} }}-\phi _{\textrm{sn}}} phi _{\textrm{sn}}

Questions {❓}

Hatzikirou H, Basanta D, Simon M, Schaller K, Deutsch A (2012) “Go or Grow’’: The key to the emergence of invasion in tumour progression?
He Y, Kaina B (2019) Are there thresholds in glioblastoma cell death responses triggered by temozolomide?
Löber-Handwerker R, Döring K, Bock C, Rohde V, Malinova V (2022) Defining the impact of adjuvant treatment on the prognosis of patients with inoperable glioblastoma undergoing biopsy-only: Does the survival benefit outweigh the treatment effort?
Onwudiwe K, Najera J, Siri S, Datta M (2022) Do tumor mechanical stresses promote cancer immune escape?

Schema {🗺️}

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         description:Malignant brain tumours represent a significant medical challenge due to their aggressive nature and unpredictable locations. The growth of a brain tumour can result in a mass effect, causing compression and displacement of the surrounding healthy brain tissue and possibly leading to severe neurological complications. In this paper, we propose a multiphase mechanical model for brain tumour growth that quantifies deformations and solid stresses caused by the expanding tumour mass and incorporates anisotropic growth influenced by brain fibres. We employ a sharp interface model to simulate localised, non-invasive solid brain tumours, which are those responsible for substantial mechanical impact on the surrounding healthy tissue. By using patient-specific imaging data, we create realistic three-dimensional brain geometries and accurately represent ventricular shapes, to evaluate how the growing mass may compress and deform the cerebral ventricles. Another relevant feature of our model is the ability to simulate therapeutic protocols, facilitating the evaluation of treatment efficacy and guiding the development of personalized therapies for individual patients. Overall, our model allows to make a step towards a deeper analysis of the complex interactions between brain tumours and their environment, with a particular focus on the impact of a growing cancer on healthy tissue, ventricular compression, and therapeutic treatment.
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            Poroelasticity
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            Ventricular compression
            Therapeutic protocols
            Finite element method
            Theoretical and Applied Mechanics
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            Classical and Continuum Physics
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      headline:Modelling and simulation of anisotropic growth in brain tumours through poroelasticity: A study of ventricular compression and therapeutic protocols
      description:Malignant brain tumours represent a significant medical challenge due to their aggressive nature and unpredictable locations. The growth of a brain tumour can result in a mass effect, causing compression and displacement of the surrounding healthy brain tissue and possibly leading to severe neurological complications. In this paper, we propose a multiphase mechanical model for brain tumour growth that quantifies deformations and solid stresses caused by the expanding tumour mass and incorporates anisotropic growth influenced by brain fibres. We employ a sharp interface model to simulate localised, non-invasive solid brain tumours, which are those responsible for substantial mechanical impact on the surrounding healthy tissue. By using patient-specific imaging data, we create realistic three-dimensional brain geometries and accurately represent ventricular shapes, to evaluate how the growing mass may compress and deform the cerebral ventricles. Another relevant feature of our model is the ability to simulate therapeutic protocols, facilitating the evaluation of treatment efficacy and guiding the development of personalized therapies for individual patients. Overall, our model allows to make a step towards a deeper analysis of the complex interactions between brain tumours and their environment, with a particular focus on the impact of a growing cancer on healthy tissue, ventricular compression, and therapeutic treatment.
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         Poroelasticity
         Anisotropic growth
         Ventricular compression
         Therapeutic protocols
         Finite element method
         Theoretical and Applied Mechanics
         Computational Science and Engineering
         Classical and Continuum Physics
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