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Evaluation of Fluid-Structure Interaction and Biofidelity of Finite Element Head Models

Time: Thu 2019-11-21 09.30

Location: T2, Hälsovägen 11, Flemingsberg (English)

Subject area: Applied Medical Technology

Doctoral student: Zhou Zhou , Neuronik, Royal Institute of Technology (KTH)

Opponent: Professor David Meaney, University of Pennsylvania

Supervisor: Professor Svein Kleiven, Neuronik, Flygteknik, Farkost- och flygteknik, Bioteknologi; Xiaogai Li, Neuronik

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Traumatic brain injury is a critical public health issue. Finite element (FE) head models are valuable instruments to explore the causal pathway from mechanical insult to resultant brain injury. Intracranial fluid-structure interaction (FSI) and biofidelity evaluation are two fundamental aspects of FE head modeling. The existing head models usually do not account for the fluid behavior of the cerebrospinal fluid (CSF) and its interaction with the other intracranial structures. Such simplification cannot guarantee a realistic interfacial behavior and may reduce the biofidelity of the head model. The biofidelity of a head model can be partially identified by comparing the model’s responses against relevant experimental data. Given the recent plethora of strain-based metrics for brain injury evaluation, a direct comparison between the computationally predicted deformation and experimentally measured strain is preferred. Due to the paucity of experimental brain deformation data, the majority of FE head models are evaluated by brain-skull relative motion data and then used for strain prediction. However, the validity of employing a model validated against brain-skull relative motion for strain prediction remains elusive.

The current thesis attempted to advance these two important aspects of the FE head modeling. An FSI approach was implemented to describe the brain-skull interface and brain-ventricle interface, in which the CSF was modeled with an arbitrary Lagrangian-Eulerian multi-material formulation with its response being concatenated with the Lagrangian-simulated brain. Such implementation not only contributes to superior validation performance and improved injury predictability of the head models but also largely reveals the mechanisms of age-related acute subdural hematoma (ASDH) and periventricular injury. It is verified that the age-related brain atrophy exacerbates bridging vein strain that explains the predisposition of the elderly to ASDH, while the presence of a fluid ventricle induces strain concentration around the ventricles that aggravates the vulnerability of the periventricular region. For the biofidelity evaluation, the current thesis revisited the only existing dynamic experimental brain strain data with the loading regimes close to traumatic levels and proposed a new approach with guaranteed fidelity to estimate the brain strain. Biofidelity of a head model was evaluated by comparing the model’s responses against the newly estimated brain strain and previously presented brain-skull relative motion data. It is found that the head model evaluated by brain-skull relative motion cannot guarantee its strain prediction accuracy. Thus, it is advocated that a model designed for brain strain prediction should be validated against experimental brain strain, in addition to brain-skull relative motion.

In conclusion, this thesis yields new knowledge of brain injury mechanism by implementing the FSI approach for the brain-skull interface and brain-ventricle interface and standardizes the strain validation protocol for FE head models by reinterpreting the experimental brain strain. It is hoped that this research has made a valuable and lasting contribution to an improved understanding of the basic head impact mechanics.