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Title: Development and validation of two subject-specific finite element models of human head against three cadaveric experiments
Authors: Tse, K.M.
Tan, L.B.
Lee, S.J.
Lim, S.P. 
Lee, H.P. 
Keywords: Computed tomography (CT)
Finite element (FE)
Head injury
Head model
Magnetic resonance imaging (MRI)
Soft tissues
Issue Date: Mar-2014
Citation: Tse, K.M., Tan, L.B., Lee, S.J., Lim, S.P., Lee, H.P. (2014-03). Development and validation of two subject-specific finite element models of human head against three cadaveric experiments. International Journal for Numerical Methods in Biomedical Engineering 30 (3) : 397-415. ScholarBank@NUS Repository.
Abstract: Head injury, being one of the main causes of death or permanent disability, continues to remain a major health problem with significant socioeconomic costs. Numerical simulations using the FEM offer a cost-effective method and alternative to experimental methods in the biomechanical studies of head injury. The present study aimed to develop two realistic subject-specific FEMs of the human head with detailed anatomical features from medical images (Model 1: without soft tissue and Model 2: with soft tissue and differentiation of white and gray matters) and to validate them against the intracranial pressure (ICP) and relative intracranial motion data of the three cadaver experimental tests. In general, both the simulated results were in reasonably good agreement with the experimental measured ICP and relative displacements, despite slight discrepancy in a few neutral density targets markers. Sensitivity analysis showed some variations in the brain's relative motion to the material properties or marker's location. The addition of soft tissue in Model 2 helped to damp out the oscillations of the model response. It was also found that, despite the fundamental anatomical differences between the two models, there existed little evident differences in the predicted ICP and relative displacements of the two models. This indicated that the advancements on the details of the extracranial features would not improve the model's predicting capabilities of brain injury. © 2013 John Wiley & Sons, Ltd.
Source Title: International Journal for Numerical Methods in Biomedical Engineering
ISSN: 20407939
DOI: 10.1002/cnm.2609
Appears in Collections:Staff Publications

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