Reconstruction of real-world car-to-pedestrian accident using computational biomechanics model: Effects of the choice of boundary conditions of the brain on brain injury risk

Fang Wang, Bingyu Wang, Yong Han, Qian Peng, Fan Li, Adam Wittek

    Research output: Chapter in Book/Conference paperChapter

    Abstract

    In the current study, the effects of the approach for modelling the brain-skull interface on prediction of the brain injury risk are investigated using a previously validated computational head-brain model. Four types of brain-skull interface modelling approaches (1): The method used in original Total HUman Model for Safety THUMS Head-brain model, (2): Brain rigidly attached to the skull, (3): Frictionless contact between the brain and skull, and (4): Cohesive layer (springtype) between the brain and skull are employed in numerical reconstruction of a real-world car-to-pedestrian impact accident. The results indicate that the predicted brain injury risk is strongly affected by the approach for modelling the brain- skull interface. The comparison of the predicted risk of diffuse axonal injury DAI and brain contusions with the injuries sustained by the pedestrian involved in the accident seems to suggest that accurate prediction of the brain injury risk using computational biomechanics models requires direct representation of the meninges and subarachnoidal space with the CSF.

    Original languageEnglish
    Title of host publicationComputational Biomechanics for Medicine
    Subtitle of host publicationMeasurements, Models, and Predictions
    PublisherSpringer International Publishing AG
    Pages15-30
    Number of pages16
    ISBN (Electronic)9783319755892
    ISBN (Print)9783319755885
    DOIs
    Publication statusPublished - 14 May 2018

    Fingerprint

    brain damage
    biodynamics
    Biomechanics
    accidents
    Biomechanical Phenomena
    Brain Injuries
    Accidents
    brain
    Brain
    skull
    Railroad cars
    Skull
    Boundary conditions
    boundary conditions
    Brain models
    Diffuse Axonal Injury
    Head
    Meninges
    Pedestrians
    predictions

    Cite this

    Wang, F., Wang, B., Han, Y., Peng, Q., Li, F., & Wittek, A. (2018). Reconstruction of real-world car-to-pedestrian accident using computational biomechanics model: Effects of the choice of boundary conditions of the brain on brain injury risk. In Computational Biomechanics for Medicine: Measurements, Models, and Predictions (pp. 15-30). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-75589-2_3
    Wang, Fang ; Wang, Bingyu ; Han, Yong ; Peng, Qian ; Li, Fan ; Wittek, Adam. / Reconstruction of real-world car-to-pedestrian accident using computational biomechanics model : Effects of the choice of boundary conditions of the brain on brain injury risk. Computational Biomechanics for Medicine: Measurements, Models, and Predictions. Springer International Publishing AG, 2018. pp. 15-30
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    abstract = "In the current study, the effects of the approach for modelling the brain-skull interface on prediction of the brain injury risk are investigated using a previously validated computational head-brain model. Four types of brain-skull interface modelling approaches (1): The method used in original Total HUman Model for Safety THUMS Head-brain model, (2): Brain rigidly attached to the skull, (3): Frictionless contact between the brain and skull, and (4): Cohesive layer (springtype) between the brain and skull are employed in numerical reconstruction of a real-world car-to-pedestrian impact accident. The results indicate that the predicted brain injury risk is strongly affected by the approach for modelling the brain- skull interface. The comparison of the predicted risk of diffuse axonal injury DAI and brain contusions with the injuries sustained by the pedestrian involved in the accident seems to suggest that accurate prediction of the brain injury risk using computational biomechanics models requires direct representation of the meninges and subarachnoidal space with the CSF.",
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    Wang, F, Wang, B, Han, Y, Peng, Q, Li, F & Wittek, A 2018, Reconstruction of real-world car-to-pedestrian accident using computational biomechanics model: Effects of the choice of boundary conditions of the brain on brain injury risk. in Computational Biomechanics for Medicine: Measurements, Models, and Predictions. Springer International Publishing AG, pp. 15-30. https://doi.org/10.1007/978-3-319-75589-2_3

    Reconstruction of real-world car-to-pedestrian accident using computational biomechanics model : Effects of the choice of boundary conditions of the brain on brain injury risk. / Wang, Fang; Wang, Bingyu; Han, Yong; Peng, Qian; Li, Fan; Wittek, Adam.

    Computational Biomechanics for Medicine: Measurements, Models, and Predictions. Springer International Publishing AG, 2018. p. 15-30.

    Research output: Chapter in Book/Conference paperChapter

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    AU - Han, Yong

    AU - Peng, Qian

    AU - Li, Fan

    AU - Wittek, Adam

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    N2 - In the current study, the effects of the approach for modelling the brain-skull interface on prediction of the brain injury risk are investigated using a previously validated computational head-brain model. Four types of brain-skull interface modelling approaches (1): The method used in original Total HUman Model for Safety THUMS Head-brain model, (2): Brain rigidly attached to the skull, (3): Frictionless contact between the brain and skull, and (4): Cohesive layer (springtype) between the brain and skull are employed in numerical reconstruction of a real-world car-to-pedestrian impact accident. The results indicate that the predicted brain injury risk is strongly affected by the approach for modelling the brain- skull interface. The comparison of the predicted risk of diffuse axonal injury DAI and brain contusions with the injuries sustained by the pedestrian involved in the accident seems to suggest that accurate prediction of the brain injury risk using computational biomechanics models requires direct representation of the meninges and subarachnoidal space with the CSF.

    AB - In the current study, the effects of the approach for modelling the brain-skull interface on prediction of the brain injury risk are investigated using a previously validated computational head-brain model. Four types of brain-skull interface modelling approaches (1): The method used in original Total HUman Model for Safety THUMS Head-brain model, (2): Brain rigidly attached to the skull, (3): Frictionless contact between the brain and skull, and (4): Cohesive layer (springtype) between the brain and skull are employed in numerical reconstruction of a real-world car-to-pedestrian impact accident. The results indicate that the predicted brain injury risk is strongly affected by the approach for modelling the brain- skull interface. The comparison of the predicted risk of diffuse axonal injury DAI and brain contusions with the injuries sustained by the pedestrian involved in the accident seems to suggest that accurate prediction of the brain injury risk using computational biomechanics models requires direct representation of the meninges and subarachnoidal space with the CSF.

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    Wang F, Wang B, Han Y, Peng Q, Li F, Wittek A. Reconstruction of real-world car-to-pedestrian accident using computational biomechanics model: Effects of the choice of boundary conditions of the brain on brain injury risk. In Computational Biomechanics for Medicine: Measurements, Models, and Predictions. Springer International Publishing AG. 2018. p. 15-30 https://doi.org/10.1007/978-3-319-75589-2_3