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Development of an Unbiased Validation Protocol to Assess the Biofidelity of Finite Element Head Models used in Prediction of Traumatic Brain Injury
KTH, School of Technology and Health (STH). (Neuronic Engineering)ORCID iD: 0000-0002-0569-5118
KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.ORCID iD: 0000-0003-0125-0784
2016 (English)In: Stapp Car Crash Journal, ISSN 1532-8546, Vol. 60, p. 363-471Article in journal (Refereed) Published
Abstract [en]

This study describes a method to identify laboratory test procedures and impact response requirements suitablefor assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of theexperimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility andrelevance of the available experimental data. A weighted averaging procedure was chosen in order to consider differentcontributions from the various test conditions and target measurements based on experimental error. According to the qualitycriteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of responsecurves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time historyresponse to the measured data. Optimization of the CORA global settings led to the recommendation of performing curvecomparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation.The allowable maximum time shift was adjusted depending on the shape of the experimental curves (􀜦􀯆􀮺􀯑􀀃􀀃= 0.12 forintracranial pressure, 􀜦􀯆􀮺􀯑 = 0.40 for brain motion and 􀜦􀯆􀮺􀯑 = 0.25 for brain deformation). Finally, bigger penalization ofratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or timeshift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage offinite element head models for traumatic brain injury prediction.

Place, publisher, year, edition, pages
2016. Vol. 60, p. 363-471
Keywords [en]
Model Validation, Finite Element (FE) Head Model, Traumatic Brain Injury (TBI), Biofidelity
National Category
Engineering and Technology
Research subject
Medical Technology
Identifiers
URN: urn:nbn:se:kth:diva-207793OAI: oai:DiVA.org:kth-207793DiVA, id: diva2:1098396
Note

QC 20170530

Available from: 2017-05-24 Created: 2017-05-24 Last updated: 2017-06-02Bibliographically approved
In thesis
1. Development of an Anisotropic Finite Element Head Model for Traumatic Brain Injury Prediction
Open this publication in new window or tab >>Development of an Anisotropic Finite Element Head Model for Traumatic Brain Injury Prediction
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Traumatic brain injury (TBI) is a worldwide health care problem with very high associatedmorbidity and mortality rates. In particular, the diagnosis of TBI is challenging: symptomsoverlap with other pathologies and the injury is typically not visible with conventionalneuroimaging techniques.Finite element (FE) head models can provide valuable insight into uncovering themechanism underlying brain damage. These models enable the calculation of tissue loadsand deformation patterns, which are thought to be associated with the injury. Measuresbased on tissue strain or invariants of the strain tensor are used as injury predictors and riskinjury curves can be inferred to establish the tolerance of the human head to external loads.However, while in-vitro research shows that the vulnerability to injury is due to highlyorganized structure in white matter tracts, the majority of the current FE models model thebrain as isotropic and homogenous. The deformation of white matter tracts is not calculated.The aim of this doctoral thesis was to incorporate the effects of inhomogeneity andanisotropy of brain tissue into injury analysis. Based on in-vitro experimental evidence, thestrain in the direction of the axons (axonal strain) was proposed as a new, more anatomicallyrelevant, injury predictor. The initial hypothesis to investigate was that an FE anisotropichead model is a better tool to represent TBI because it is more biofidelic in describing thelocal mechanism of axonal impairment.The studies reported in this thesis describe a method for implementing the orientation of thewhite matter tracts in an anisotropic constitutive law for FE modeling. Results from thestudies suggested that the anisotropy of the brain significantly affected the injury predictionsof an FE head model. For an injury dataset from the American National Football League, thepeak of axonal strain - MAS - was found to be a better predictor of injury than isotropic localor global predictors. Finally, based on 27 cases of intracranial pressure, relative skull-brainmotion and brain deformation, the introduction of the brain anisotropy in the FE modelpartially enhanced the biofidelity of the simulations. However, given that the enhancementin biofidelity was not major, it was concluded that further research is necessary forunderstanding the relationship between tissue-level loading and axonal injury.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2017. p. 60
Series
TRITA-STH : report, ISSN 1653-3836 ; 2017:5
Keywords
Axonal Strain, Brain Anisotropy, Traumatic Brain Injury, Finite Element Analysis, Brain Tissue, Constitutive Modeling.
National Category
Engineering and Technology
Research subject
Medical Technology
Identifiers
urn:nbn:se:kth:diva-207797 (URN)978-91-7729-357-6 (ISBN)
Public defence
2017-06-02, T2, Hälsovägen 11C, Huddinge, 13:00 (English)
Opponent
Supervisors
Note

QC 20170524

Available from: 2017-05-24 Created: 2017-05-24 Last updated: 2017-05-24Bibliographically approved

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