Smoothed particle hydrodynamic modelling of the cerebrospinal fluid for brain biomechanics: Accuracy and stability. (9th February 2021)

• Record Type: Journal Article
• Authors: Duckworth, Harry; Sharp, David J.; Ghajari, Mazdak
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 37:Number 4(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-02-09
• Subjects: brain biomechanics -- cerebrospinal fluid -- finite element modelling -- smoothed particle hydrodynamics; Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.3440
• Languages: English
• ISSNs: 2040-7939

Abstract

Abstract: 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. Abstract : 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.