02 Fakultät Bau- und Umweltingenieurwissenschaften
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/3
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Item Open Access Multiphasic modelling and computation of metastatic lung-cancer cell proliferation and atrophy in brain tissue based on experimental data(2021) Ehlers, Wolfgang; Rehm, Markus; Schröder, Patrick; Stöhr, Daniela; Wagner, ArndtCancer is one of the most serious diseases for human beings, especially when metastases come into play. In the present article, the example of lung-cancer metastases in the brain is used to discuss the basic problem of cancer growth and atrophy as a result of both nutrients and medication. As the brain itself is a soft tissue that is saturated by blood and interstitial fluid, the biomechanical description of the problem is based on the Theory of Porous Media enhanced by the results of medication tests carried out in in-vitro experiments on cancer-cell cultures. Based on theoretical and experimental results, the consideration of proliferation, necrosis and apoptosis of metastatic cancer cells is included in the description by so-called mass-production terms added to the mass balances of the brain skeleton and the interstitial fluid. Furthermore, the mass interaction of nutrients and medical drugs between the solid and the interstitial fluid and its influence on proliferation, necrosis and apoptosis of cancer cells are considered. As a result, the overall model is appropriate for the description of brain tumour treatment combined with stress and deformation induced by cancer growth in the skull.Item Open Access Patient‐specific simulation of brain tumour growth and regression(2023) Suditsch, Marlon; Ricken, Tim; Wagner, ArndtThe medical relevance of brain tumours is characterised by its locally invasive and destructive growth. With a high mortality rate combined with a short remaining life expectancy, brain tumours are identified as highly malignant. A continuum‐mechanical model for the description of the governing processes of growth and regression is derived in the framework of the Theory of Porous Media (TPM). The model is based on medical multi‐modal magnetic resonance imaging (MRI) scans, which represent the gold standard in diagnosis. The multi‐phase model is described mathematically via strongly coupled partial differential equations. This set of governing equations is transformed into their weak formulation and is solved with the software package FEniCS. A proof‐of‐concept simulation based on one patient geometry and tumour pathology shows the relevant processes of tumour growth and the results are discussed.Item Open Access Analysing the bone cement flow in the injection apparatus during vertebroplasty(2023) Trivedi, Zubin; Gehweiler, Dominic; Wychowaniec, Jacek K.; Ricken, Tim; Gueorguiev-Rüegg, Boyko; Wagner, Arndt; Röhrle, OliverVertebroplasty, a medical procedure for treating vertebral fractures, requires medical practitioners to inject bone cement inside the vertebra using a cannula attached to a syringe. The required injection force must be small enough for the practitioner to apply it by hand while remaining stable for a controlled injection. Several factors could make the injection force unintuitive for the practitioners, one of them being the non‐Newtonian nature of the bone cement. The viscosity of the bone cement varies as it flows through the different parts of the injection apparatus and the porous cancellous interior of the vertebra. Therefore, it is important to study the flow of bone cement through these parts. This work is a preliminary study on the flow of bone cement through the injection apparatus. Firstly, we obtained the rheological parameters for the power law model of bone cement using experiments using standard clinical equipment. These parameters were then used to obtain the shear rate, viscosity, and velocity profiles of the bone cement flow through the cannula. Lastly, an analysis was carried out to understand the influence of various geometrical parameters of the injection apparatus, in which the radius of the cannula was found to be the most influential parameter.