12345673 of 32
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Evaluation of Fluid-Structure Interaction and Biofidelity of Finite Element Head Models
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering. Royal Institute of Technology (KTH).ORCID iD: 0000-0002-3910-0418
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: urn:nbn:se:kth:diva-263122OAI: oai:DiVA.org:kth-263122DiVA, id: diva2:1366592
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: 2019-10-30Bibliographically approved
List of papers
1. Fluid–structure interaction simulation of the brain–skull interface for acute subdural haematoma prediction
Open this publication in new window or tab >>Fluid–structure interaction simulation of the brain–skull interface for acute subdural haematoma prediction
2018 (English)In: Biomechanics and Modeling in Mechanobiology, ISSN 1617-7959, E-ISSN 1617-7940, Vol. 18, no 1, p. 155-173Article in journal (Refereed) Published
Abstract [en]

Traumatic brain injury is a leading cause of disability and mortality. Finite element-based head models are promising tools for enhanced head injury prediction, mitigation and prevention. The reliability of such models depends heavily on adequate representation of the brain–skull interaction. Nevertheless, the brain–skull interface has been largely simplified in previous three-dimensional head models without accounting for the fluid behaviour of the cerebrospinal fluid (CSF) and its mechanical interaction with the brain and skull. In this study, the brain–skull interface in a previously developed head model is modified as a fluid–structure interaction (FSI) approach, in which the CSF is treated on a moving mesh using an arbitrary Lagrangian–Eulerian multi-material formulation and the brain on a deformable mesh using a Lagrangian formulation. The modified model is validated against brain–skull relative displacement and intracranial pressure responses and subsequently imposed to an experimentally determined loading known to cause acute subdural haematoma (ASDH). Compared to the original model, the modified model achieves an improved validation performance in terms of brain–skull relative motion and is able to predict the occurrence of ASDH more accurately, indicating the superiority of the FSI approach for brain–skull interface modelling. The introduction of the FSI approach to represent the fluid behaviour of the CSF and its interaction with the brain and skull is crucial for more accurate head injury predictions.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2018
National Category
Other Medical Engineering
Identifiers
urn:nbn:se:kth:diva-233858 (URN)10.1007/s10237-018-1074-z (DOI)000457974500012 ()2-s2.0-85053071855 (Scopus ID)
Note

QC 20180906

Available from: 2018-08-30 Created: 2018-08-30 Last updated: 2019-10-30Bibliographically approved
2. Biomechanics of acute subdural hematoma in the elderly: A fluid-structure interaction study
Open this publication in new window or tab >>Biomechanics of acute subdural hematoma in the elderly: A fluid-structure interaction study
2019 (English)In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042, Vol. 36, no 13, p. 2099-2108Article in journal (Refereed) Published
Abstract [en]

Acute subdural hematoma (ASDH) due to bridging vein (BV) rupture is a frequent and lethal head injury, especially in the elderly. Brain atrophy has been hypothesized to be a primary pathogenesis associated with the increased risk of ASDH in the elderly. Though decades of biomechanical endeavours have been made to elucidate the potential mechanisms, a thorough explanation for this hypothesis appears lacking. Thus, a recently improved finite element head model, in which the brain-skull interface was modelled using a fluid-structure interaction (FSI) approach with special treatment of the cerebrospinal fluid as arbitrary Lagrangian-Eulerian fluid formulation, is used to partially address this understanding gap. Models with various degrees of atrophied brains and thereby different subarachnoid thicknesses are generated and subsequently exposed to experimentally determined loadings known to cause ASDH or not. The results show significant increases in the cortical relative motion and BV strain in the atrophied brain, which consequently exacerbates the ASDH risk in the elderly. Results of this study are suggested to be considered while developing age-adapted protecting strategies for the elderly in the future.

Place, publisher, year, edition, pages
Mary Ann Liebert, 2019
National Category
Medical and Health Sciences Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:kth:diva-243833 (URN)10.1089/neu.2018.6143 (DOI)000473049600431 ()30717617 (PubMedID)2-s2.0-85068219142 (Scopus ID)
Note

QC 20190212

Available from: 2019-02-06 Created: 2019-02-06 Last updated: 2019-11-14Bibliographically approved
3. Biomechanics of periventricular injury
Open this publication in new window or tab >>Biomechanics of periventricular injury
2019 (English)In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042Article in journal (Other academic) Submitted
National Category
Medical Engineering
Identifiers
urn:nbn:se:kth:diva-263069 (URN)
Note

QCR 20191029

Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2019-11-13Bibliographically approved
4. A reanalysis of experimental brain strain data: implication for finite element head model validation
Open this publication in new window or tab >>A reanalysis of experimental brain strain data: implication for finite element head model validation
Show others...
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
NLM, 2018
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:kth:diva-242238 (URN)30608998 (PubMedID)2-s2.0-85059498927 (Scopus ID)
Note

QC 20190514

Available from: 2019-01-29 Created: 2019-01-29 Last updated: 2019-11-13Bibliographically approved
5. Brain Strain from Motion of Sparse Markers
Open this publication in new window or tab >>Brain Strain from Motion of Sparse Markers
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.

National Category
Medical Engineering
Identifiers
urn:nbn:se:kth:diva-263068 (URN)
Note

QCR 20191029

Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2019-10-30Bibliographically approved

Open Access in DiVA

fulltext(3027 kB)52 downloads
File information
File name FULLTEXT01.pdfFile size 3027 kBChecksum SHA-512
02ccb5c3815338b281263ed9d2a3f5506d56b4761183f17c75a5ee7b65a4d90c639417c5afce7084effe861487e614f5be4ddb2a2909c904791daf4dd8a09273
Type fulltextMimetype application/pdf

Authority records BETA

Zhou, Zhou

Search in DiVA

By author/editor
Zhou, Zhou
By organisation
Neuronic Engineering
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 52 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 580 hits
12345673 of 32
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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