kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Brain Strain from Motion of Sparse Markers
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
2019 (English)In: Stapp Car Crash Journal, ISSN 1532-8546, Vol. 63Article in journal (Refereed) Published
Abstract [en]

Brain strain secondary to head impact or inertial loading is closely associated with pathologic observations in the brain. The only experimental brain strain under loading close to traumatic level was calculated by imposing the experimentally measured motion of markers embedded in the brain to an auxiliary model formed by triad elements (Hardy et al., 2007). However, fidelity of this strain calculation as well as the suitability of using triad elements for three-dimensional strain estimation remains to be verified. Therefore, this study proposes to use tetrahedron elements as a new approach to estimate the brain strain. Fidelity of this newly-proposed approach along with the previous triad-based approach is evaluated with the aid of a finite element (FE) head model by numerically replicating the experimental impacts and strain estimation procedures. Strain in the preselected brain elements obtained from the whole head simulation exhibits good correlation with its tetra estimation which exceeds triad estimation, indicating that the tetra approach more accurately estimates the strain in the preselected region. The newly calculated brain strain curves using tetra elements provide better representation of the experimental brain deformation and can be used for strain validation of FE head models.

Place, publisher, year, edition, pages
2019. Vol. 63
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-263068PubMedID: 32311050Scopus ID: 2-s2.0-85082974041OAI: oai:DiVA.org:kth-263068DiVA, id: diva2:1366318
Note

QCR 20191029

Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2024-03-18Bibliographically 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

Open Access in DiVA

No full text in DiVA

PubMedScopus

Authority records

Zhou, ZhouLi, XiaogaiKleiven, Svein

Search in DiVA

By author/editor
Zhou, ZhouLi, XiaogaiKleiven, Svein
By organisation
Neuronic Engineering
In the same journal
Stapp Car Crash Journal
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar

pubmed
urn-nbn

Altmetric score

pubmed
urn-nbn
Total: 261 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf