In this section
@article{Duckworth:2021:10.1002/cnm.3440,
author = {Duckworth, H and Sharp, DJ and Ghajari, M},
doi = {10.1002/cnm.3440},
journal = {International Journal for Numerical Methods in Biomedical Engineering},
title = {Smoothed particle hydrodynamic modelling of the cerebrospinal fluid for brain biomechanics: accuracy and stability},
url = {http://dx.doi.org/10.1002/cnm.3440},
volume = {37},
year = {2021}
}
TY - JOUR
AB - 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.
AU - Duckworth,H
AU - Sharp,DJ
AU - Ghajari,M
DO - 10.1002/cnm.3440
PY - 2021///
SN - 1069-8299
TI - Smoothed particle hydrodynamic modelling of the cerebrospinal fluid for brain biomechanics: accuracy and stability
T2 - International Journal for Numerical Methods in Biomedical Engineering
UR - http://dx.doi.org/10.1002/cnm.3440
UR - http://hdl.handle.net/10044/1/87199
VL - 37
ER -
Established in 2017 by its principal funder the Medical Research Council, in partnership with Alzheimer's Society and Alzheimer’s Research UK, The UK Dementia Research Institute (UK DRI) is the UK’s leading biomedical research institute dedicated to neurodegenerative diseases.
