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A reanalysis of experimental brain strain data: implication for finite element head model validation
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.ORCID iD: 0000-0002-3910-0418
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.ORCID iD: 0000-0001-8522-4705
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.ORCID iD: 0000-0003-0125-0784
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2018 (English)In: Stapp Car Crash Journal, ISSN 1532-8546, Vol. 62, p. 293-318Article in journal (Refereed) Published
Abstract [en]

Relative motion between the brain and skull and brain deformation are biomechanics aspects associated with many types of traumatic brain injury (TBI). Thus far, there is only one experimental endeavor (Hardy et al., 2007) reported brain strain under loading conditions commensurate with levels that were capable of producing injury. Most of the existing finite element (FE) head models are validated against brain-skull relative motion and then used for TBI prediction based on strain metrics. However, the suitability of using a model validated against brain-skull relative motion for strain prediction remains to be determined. To partially address the deficiency of experimental brain deformation data, this study revisits the only existing dynamic experimental brain strain data and updates the original calculations, which reflect incremental strain changes. The brain strain is recomputed by imposing the measured motion of neutral density target (NDT) to the NDT triad model. The revised brain strain and the brain-skull relative motion data are then used to test the hypothesis that an FE head model validated against brainskull relative motion does not guarantee its accuracy in terms of brain strain prediction. To this end, responses of brain strain and brain-skull relative motion of a previously developed FE head model (Kleiven, 2007) are compared with available experimental data. CORrelation and Analysis (CORA) and Normalized Integral Square Error (NISE) are employed to evaluate model validation performance for both brain strain and brain-skull relative motion. Correlation analyses (Pearson coefficient) are conducted between average cluster peak strain and average cluster peak brain-skull relative motion, and also between brain strain validation scores and brain-skull relative motion validation scores. The results show no significant correlations, neither between experimentally acquired peaks nor between computationally determined validation scores. These findings indicate that a head model validated against brain-skull relative motion may not be sufficient to assure its strain prediction accuracy. It is suggested that a FE head model with intended use for strain prediction should be validated against the experimental brain deformation data and not just the brain-skull relative motion.

Place, publisher, year, edition, pages
The Stapp Association , 2018. Vol. 62, p. 293-318
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-242238PubMedID: 30608998Scopus ID: 2-s2.0-85059498927OAI: oai:DiVA.org:kth-242238DiVA, id: diva2:1283359
Note

QC 20190514

Available from: 2019-01-29 Created: 2019-01-29 Last updated: 2024-01-18Bibliographically approved
In thesis
1. Evaluation of Fluid-Structure Interaction and Biofidelity of Finite Element Head Models
Open this publication in new window or tab >>Evaluation of Fluid-Structure Interaction and Biofidelity of Finite Element Head Models
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2019. p. 48
Series
TRITA-CBH-FOU ; 2019:57
National Category
Medical Engineering
Research subject
Applied Medical Technology
Identifiers
urn:nbn:se:kth:diva-263122 (URN)
Public defence
2019-11-21, T2, Hälsovägen 11, Flemingsberg, 09:30 (English)
Opponent
Supervisors
Note

QC 2019-10-30

Available from: 2019-10-30 Created: 2019-10-30 Last updated: 2022-10-24Bibliographically approved

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Zhou, ZhouLi, XiaogaiKleiven, Svein

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