Universität Stuttgart

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Open Access
A continuum mechanical porous media model for vertebroplasty : numerical simulations and experimental validation
(2023) Trivedi, Zubin; Gehweiler, Dominic; Wychowaniec, Jacek K.; Ricken, Tim; Gueorguiev, Boyko; Wagner, Arndt; Röhrle, Oliver
The outcome of vertebroplasty is hard to predict due to its dependence on complex factors like bone cement and marrow rheologies. Cement leakage could occur if the procedure is done incorrectly, potentially causing adverse complications. A reliable simulation could predict the patient-specific outcome preoperatively and avoid the risk of cement leakage. Therefore, the aim of this work was to introduce a computationally feasible and experimentally validated model for simulating vertebroplasty. The developed model is a multiphase continuum-mechanical macro-scale model based on the Theory of Porous Media. The related governing equations were discretized using a combined finite element-finite volume approach by the so-called Box discretization. Three different rheological upscaling methods were used to compare and determine the most suitable approach for this application. For validation, a benchmark experiment was set up and simulated using the model. The influence of bone marrow and parameters like permeability, porosity, etc., was investigated to study the effect of varying conditions on vertebroplasty. The presented model could realistically simulate the injection of bone cement in porous materials when used with the correct rheological upscaling models, of which the semi-analytical averaging of the viscosity gave the best results. The marrow viscosity is identified as the crucial reference to categorize bone cements as ‘high- ’or ‘low-’ viscosity in the context of vertebroplasty. It is confirmed that a cement with higher viscosity than the marrow ensures stable development of the injection and a proper cement interdigitation inside the vertebra.
Open Access
Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction
(2023) Kneifl, Jonas; Rosin, David; Avci, Okan; Röhrle, Oliver; Fehr, Jörg
Over the last decades, computer modeling has evolved from a supporting tool for engineering prototype design to an ubiquitous instrument in non-traditional fields such as medical rehabilitation. This area comes with unique challenges, e.g. the complex modeling of soft tissue or the analysis of musculoskeletal systems. Conventional modeling approaches like the finite element (FE) method are computationally costly when dealing with such models, limiting their usability for real-time simulation or deployment on low-end hardware, if the model at hand cannot be simplified without losing its expressiveness. Non-traditional approaches such as surrogate modeling using data-driven model order reduction are used to make complex high-fidelity models more widely available regardless. They often involve a dimensionality reduction step, in which the high-dimensional system state is transformed onto a low-dimensional subspace or manifold, and a regression approach to capture the reduced system behavior. While most publications focus on one dimensionality reduction, such as principal component analysis (PCA) (linear) or autoencoder (nonlinear), we consider and compare PCA, kernel PCA, autoencoders, as well as variational autoencoders for the approximation of a continuum-mechanical system. In detail, we demonstrate the benefits of the surrogate modeling approach on a complex musculoskeletal system of a human upper-arm with severe nonlinearities and physiological geometry. We consider both, the model’s deformation and the internal stress as the two main quantities of interest in a FE context. By doing so we are able to create computationally low-cost surrogate models which capture the system behavior with high approximation quality and fast evaluations.

Universität Stuttgart

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