Rat brain injury mechanism identification through indentation experiment FE reconstruction

Rat brain injury mechanism identification through indentation experiment FE

reconstruction

D. BAUMGARTNER, M. LAMY, R. WILLINGER DEPARTMENT OF FLUID AND SOLID MECHANICS

STRASBOURG UNIVERSITY – FRANCE

M. GILCHRIST DEPARTMENT OF MECHANICAL ENGINEERING

UNIVERSITY COLLEGE DUBLIN – IRELAND

CONTEXT

Rat brain injury mechanism identification through indentation experiment FE reconstruction

Context: TBI

Traumatic Brain Injuries (TBI): Major cause of deaths and disabilities

235/100,000 (EU) 103/100,000 (USA)

Double cost

Mild and severe TBI : not fully explored

Motor-vehicle incidents

Falls Sport-related

Other


Context: Mechanical sollicitations

Mechanical loading results in an brain response

Criteria in head protection systems and standards

Need for injury criteria models Experimental models Numerical models Combination of both models

(Deck et al., 2008)


Context: Rat brain FE models

Shreiber et al., 1997 (University of Pennsylvania)

Gefen et al., 2003 (University of Pennsylvania)

Levchakov et al., 2006 (University of Pennsylvania)

Pena et al., 2005 (University of Cambridge)

Mao et al., 2006 (Wayne State University)

Zhu et al., 2010 (Wayne State University)

Fijalkowski et al., 2009 (Medical College of Wisconsin)

Strasbourg University Model, 2009


Context: Objectives of the study

Reconstruct real experimental protocols with our rat head FEM: Indentation loading from the University College Dublin Compare experimental findings and calculated mechanical response

Contribute to the knowledge on mild and severe TBI from a mechanical point of view


EXPERIMENTAL

PROTOCOL


Experimental setup: Device

Submission of the rat brain to an indentation at two different displacement amplitudes: 0.87 mm (low impact group) and 2.62 mm (high impact group)

The University College Dublin device

for the induction of rat brain indentation


Experimental results: Histology and MRI


a: MRI of animal from low (1) and high (2) impact group

b: Hematoxylin and eosin stain of animal from low (1) and high (2) impact group

Experimental results: Volume variations

Corpus callosum volume



Cerebral spinal fluid volume



Abnormal cerebral grey matter volume


NUMERICAL

SIMULATIONS


Simulations: Model (mesh, 1)

Continuous mesh (Hypermesh 11.0)

Brain 118,016 hexahedrons

Skull

12,880 shells Brain/skull interface 25,760 hexahedrons


Simulations: Model (mesh, 2)


Simulations: Model (behaviour, 1)

The model is assumed to be Linear viscous elastic (Boltzman model) for brain Linear elastic for brain/skull interface With a rigid skull Homogeneous and isotropic

Material properties of the brain

Short term

shear modulus

Long term

shear modulus Time constant Density Bulk modulus

10 kPa 2 kPa 8 s 1,040 kg/m3 2.19 GPa


Simulations: Model (behaviour, 2)

Choice of material properties for the brain

Based on Fijalkowski et al. (2009)

In agreement with MRE data from Vappou et al. (2008)

Short term shear modulus Long term shear modulus

10 kPa 2 kPa


Simulations: Computed parameters

The model is submitted to indentation inputs Main computed parameters (Radioss)

Brain Von Mises stress Brain pressure CSF volume

Regions of interest

Vicinity of the corpus callosum Brain cortex Brain/skull interface


NUMERICAL

RESULTS


Results: Global view


Low impact group i.e. mild injury level

High impact group i.e. severe injury level

Cylinder displacement = 0.87 mm

Cylinder displacement = 2.62 mm

Results: Brain pressure (superficial)




Maximal brain pressure = 798 kPa

Severe brain contusions

Maximal brain pressure = 3,206 kPa


Results: Brain pressure (internal)




Maximal brain pressure = 574 kPa


Maximal brain pressure = 2,472 kPa


Results: Brain Von Mises stress (superf.)




Maximal brain Von Mises stress = 9 kPa

No neurological injuries


Mild neurological injuries

Results: Brain Von Mises stress (internal)





No neurological injuries


Mild neurological injuries

Results: CSF volume




Low compression of CSF Delayed mild increase of CSF

volume ?

High compression of CSF Delayed severe increase of CSF

volume ?

CONCLUSIONS


FEM of the rat’s head including anatomical structures for in-vivo mild and severe TBI investigation through reconstruction of identation tests

Good correlation between brain Von Mises stresses distributions level, as well as brain pressure distributions level, and histological observations

TISSUE-LEVEL STRESSES WITHIN THE BRAIN DURING ROTATIONALLY-INDUCED mTBI: A 3D FINITE ELEMENT MODEL OF THE RAT COUPLED WITH EXPERIMENTS


Main conclusions

Future developments (1)

Expanding the range of existing simulations with new inputs &/or new protocols, espacially from an injury identification point of view

Achieving a more detailed mechanical characterization of the intracranial medium, i.e. taking into account inhomogeneity, anatomically based distribution, … In the long term, transfering the results to human brain, in order to propose some new injury criteria so as to improve human head protection devices


Future developments (2)

New challenge: predict delayed injuries thanks to Calculated mechanical parameters during loading Simulations that can reproduce hours of physiological evolutions


THANK YOU FOR

YOUR ATTENTION


Rat brain injury mechanism identification through indentation experiment FE

reconstruction

D. BAUMGARTNER, M. LAMY, R. WILLINGER DEPARTMENT OF FLUID AND SOLID MECHANICS

STRASBOURG UNIVERSITY – FRANCE

M. GILCHRIST DEPARTMENT OF MECHANICAL ENGINEERING

UNIVERSITY COLLEGE DUBLIN – IRELAND

Technology

Rat brain injury mechanism identification through indentation experiment FE reconstruction