Smoothed particle hydrodynamic modelling of the cerebrospinal fluid for brain biomechanics: accuracy and stability
| Autor: | Mazdak Ghajari, David J. Sharp, Harry Duckworth |
|---|---|
| Přispěvatelé: | Engineering and Physical Sciences Research Council, Imperial College Healthcare NHS Trust- BRC Funding, Wellcome Trust |
| Rok vydání: | 2021 |
| Předmět: |
Mathematics
Interdisciplinary Applications Technology smoothed particle hydrodynamics Traumatic Brain Injury 0206 medical engineering Finite Element Analysis Biomedical Engineering 02 engineering and technology 030204 cardiovascular system & hematology Instability cerebrospinal fluid 09 Engineering brain biomechanics Smoothed-particle hydrodynamics Motion 03 medical and health sciences 0302 clinical medicine Engineering Research Article ‐ Applications Humans Computer Simulation Molecular Biology Engineering Biomedical finite element modelling Research Article ‐ Application 01 Mathematical Sciences Computational model Science & Technology Applied Mathematics Biomechanics Brain Mechanics Strain rate 020601 biomedical engineering Finite element method Biomechanical Phenomena Shear (sheet metal) Computational Theory and Mathematics Modeling and Simulation Physical Sciences Hydrodynamics Mathematical & Computational Biology Moving least squares Life Sciences & Biomedicine Software Mathematics |
| Zdroj: | International Journal for Numerical Methods in Biomedical Engineering |
| Popis: | The Cerebrospinal Fluid (CSF) can undergo shear deformations under head motions. Finite Element (FE) models, which are commonly used to simulate biomechanics of the brain, including traumatic brain injury, employ solid elements to represent the CSF. However, the limited number of elements paired with shear deformations in CSF can decrease the accuracy of their predictions. Large deformation problems can be accurately modelled using the mesh‐free Smoothed Particle Hydrodynamics (SPH) method, but there is limited previous work on using this method for modelling the CSF. Here we explored the stability and accuracy of key modelling parameters of an SPH model of the CSF when predicting relative brain/skull displacements in a simulation of an in vivo mild head impact in human. The Moving Least Squares (MLS) SPH formulation and Ogden rubber material model were found to be the most accurate and stable. The strain and strain rate in the brain differed across the SPH and FE models of CSF. The FE mesh anchored the gyri, preventing them from experiencing the level of strains seen in the in vivo brain experiments and predicted by the SPH model. Additionally, SPH showed higher levels of strains in the sulci compared to the FE model. However, tensile instability was found to be a key challenge of the SPH method, which needs to be addressed in future. Our study provides a detailed investigation of the use of SPH and shows its potential for improving the accuracy of computational models of brain biomechanics. Here we show the key benefits, and challenges, when modelling brain biomechanics using the meshfree method Smoothed Particle Hydrodynamics (SPH) to represent the cerebrospinal fluid in finite element models. A parametric study of the accuracy and stability of different modelling parameters is presented. Additionally, the meshfree method is shown to predict strains and strain rates similar to those seen in‐vivo, unlike the traditional modelling method. |
| Databáze: | OpenAIRE |
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