engineering models of decompressive craniectomy · decompressive craniectomy can be used to control...
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Engineering models of decompressive craniectomy
Funded by EPSRC and MRC/NIHR Supported by RESCUEicp
1. Division of Neurosurgery, Addenbrooke's Hospital & University of Cambridge2. Department of Engineering, University of Cambridge
Fletcher TL12, Kolias AG1, Timofeev I1, Corteen EA1, Sutcliffe MPF2, Hutchinson PJ1
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Contents
– Introduction
– Finite element modelling approaches
– Image analysis
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Background
Decompressive craniectomy can be used to control refractory intracranial hypertension post TBI.
Associated with a number of complications
– Brain herniation
– Deformation
Engineering models may provide insight into the deformation and possible regions of damage.
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Suboptimum hemi-craniectomy
Computational finite element (FE) model developed of a similar situation.
– Large curvature near bone margin
– Max displacement ~15 mm
Schematic of suboptimum hemicraniectomy.Wagner, S. et al., 2001. J Neurosurg, 94(5), pp.693-6
Finite element model to mimic the schematic of Wagner et. al.
Deformation profile for small craniectomy shown to be detrimental to patient outcome
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The finite element model
Create an overall model
Split the model into small elements (finite elements)
Create a set of partial differential equations....
...Numerically solve
Use commercially available Abaqus FE software.
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FE model of craniectomy
Gao and Ang model of craniectomy size against pressure.
Trade-off between bulge and pressure drop.
We are currently focusing on the possible tissue damage caused by craniectomies of varying size.
Craniectomy size vs maximum displacement from Gao, C. & Ang, B., 2008. Acta Neurochir Suppl, pp.279-282.
Max
imum
di
spla
cem
ent
(mm
)
Elements in subcranial area
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Research plan
Focus on simple spherical axi-symmetric models
Explore the influence on size of 'at risk region' of two geometrical
parameters:
– craniectomy size
– bone edge fillet radius (or sharpness)
Despite simplification the real world trends are still relevant.
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Spherical brain model - schematic
r '=rR
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Defining the 'at risk region'
Elkin and Morrison 2007
– Rat cortical brain experiments
– Varying rates/speeds
– Varying strains (stretch)
Cell death quantified and thresholds for damage hypothesised.
– 20% Lagrangian strain.
• Large deformation stretch ratio
Strain and rate vs cell death for day 4 post injury from Elkin, B.S. & Morrison, B., 2007. Stapp car crash J, 51(Oct), pp.127-38.
(s -1)
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How to use the threshold
Using computational models:
– Output strain for models with varying parameters
– Create a contour of threshold strain
– Output areas/volumes of regions of strain below this (negative) threshold
See example, top, showing FE output
Bottom showing first at risk region
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Output for single fillet radius
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Displacement vs at risk region area
Maximum 'at risk region' when r' is 0.3
Does not directly correlate with maximum displacement, which occurs with r' = 0.2
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Output
At risk region for shear strain greater than 20% for varying craniectomy size and bone edge fillet radius.
Bone edge fillet radius has little effect on size of at risk region
These models must be validated against patient data
– Analysis of CT scans
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CT scan analysis
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CT scans - Introduction
Overview
– Pre to post-op registration
– Analysis of brain shape
Analysis...
– Curvature
– Deformation Δy
– Contusion volume
– Midline shift
– Volume changes
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CT scans - Method
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Conclusions
Models produced show promise in developing understanding of brain deformation post DC
– Potential to assist in determining the optimal size and location of DC
Correlate with radiological and microdialysis data.
Further work will be undertaken to improve the model:
– Poro-elastic materials and time dependence
– Geometrical improvements
– Influence of blood volume on ICP during DC
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Sample images