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脑生物力学中脑脊液的平滑粒子流体动力学建模:准确性和稳定性。

Smoothed particle hydrodynamic modelling of the cerebrospinal fluid for brain biomechanics: Accuracy and stability.

机构信息

Dyson School of Design Engineering, Imperial College London, London, UK.

The Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, London, UK.

出版信息

Int J Numer Method Biomed Eng. 2021 Apr;37(4):e3440. doi: 10.1002/cnm.3440. Epub 2021 Feb 9.

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.

摘要

脑脊液(CSF)在头部运动下会发生剪切变形。有限元(FE)模型常用于模拟大脑的生物力学,包括创伤性脑损伤,使用实体元素来表示 CSF。然而,CSF 中的元素数量有限,加上剪切变形,会降低其预测的准确性。大变形问题可以使用无网格光滑粒子流体动力学(SPH)方法准确建模,但以前关于使用该方法对 CSF 进行建模的工作有限。在这里,我们探讨了 CSF 的 SPH 模型在预测人体体内轻度头部撞击模拟中的相对脑/颅骨位移时,其关键建模参数的稳定性和准确性。移动最小二乘(MLS)SPH 公式和 Ogden 橡胶材料模型被发现是最准确和稳定的。大脑中的应变和应变速率在 SPH 和 CSF 的 FE 模型中有所不同。FE 网格固定了脑回,防止它们经历体内脑实验和 SPH 模型预测的应变水平。此外,SPH 在脑沟中的应变水平高于 FE 模型。然而,发现拉伸不稳定性是 SPH 方法的一个关键挑战,需要在未来加以解决。我们的研究对 SPH 的使用进行了详细的调查,并展示了其在提高大脑生物力学计算模型准确性方面的潜力。

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