Marie Skłodowska -Curie Actions (MSCA) Innovative Training ...
Transcript of Marie Skłodowska -Curie Actions (MSCA) Innovative Training ...
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Marie Skłodowska-Curie Actions (MSCA) Innovative Training Networks (ITN)
H2020-MSCA-ITN-2017
SPINe: Numerical and Experimental Repair StrategiesManagement Meeting
Friday, 23rd October 2020
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 766012
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Modelling for spinal surgeries
ESR5: Marco Sensale
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Modelling for spinal surgeries
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The goal of the project is to develop CT-based efficient planning andintra-operative tools to be used by surgeons to improve the outcomes of
spinal surgeries
CT-scan images
Hopefully I will have a normal
life!
...I need better tools than
these.
Vertebral fracture
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Thoracolumbar burst fractures (TBF)
4[1] Schousboe 2015, [2] Magerl et al. 1994, [3] Oprel et al. 2010, [4] Kumar et al. 2005, [5] Wang et al. 2017
• Societal burden of vertebral
fractures exceeded only by hip
fracture [1]
• TBF 30 % of total share[2]
• Falls, motor or sport accidents [3]
• Typically at lumbar spine [3]
[2]
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Thoracolumbar burst fractures (TBF)
5[1] Schousboe 2015, [2] Magerl et al. 1994, [3] Oprel et al. 2010, [4] Kumar et al. 2005, [5] Wang et al. 2017
[2] [4]
Minimally invasive techniques
[5]
• Societal burden of vertebral
fractures exceeded only by hip
fracture [1]
• TBF 30 % of total share[2]
• Falls, motor or sport accidents [3]
• Typically at lumbar spine [3]
Posterior fixation Kyphoplasty
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Two modelling approaches
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Statistical shape modellingBiomechanical modelling
• Sensitivity analyses of FE models
• RBF Morphing
• Reduced order modelling
Goal: to optimize the outcomes of
posterior screw fixation
Goal 1: to predict the pre-fracture shape of
a lumbar verterbra to optimize kyphoplasty
Goal 2: pre-processing of FE pipeline
• Gaussian free form deformation
models
• RBF Morphing
• Machine learning techniques
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Methods
F1 F2
FE model of one instrumented lumbar vertebra with heterogeneous material properties subjected to body weight
Verification and sensitivity analyses
D (mm)
45
405,5 6,5 7,5
L (mm)
50
Max deflectionScrew
Max σVMScrew
Min εp3BoneMetrics
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Results
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Diameter
7.5 mm 6.5 mm 5.5 mm
Leng
th 40 mm - = +45 mm - REF +50 mm - - +
Max σVM Screw
Sensitivity analysis
Diameter
7.5 mm 6.5 mm 5.5 mm
Leng
th 40 mm - + +45 mm - REF +50 mm - - +
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Scientific outcomes
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Submission to international journal:
Sensale, M., Vendeuvre, T., Schilling, C., Grupp, T.,
Rochette, M., Dall’Ara, E.. Tentative title: “Sensitivity
analyses for patient-specific Finite element models of
posterior fixation”
Special research topic of Frontiers in Bioengineeringand Biotechnology (Biomechanics)
Oral presentation at an international conference
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Statistical Shape Modelling
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• Morphing techniques to obtain an iso-topological population of vertebrae • Singular Value Decomposition (SVD) analysis to summarize the variability of the dataset in
deformation modes
Challenge: avoid the sliding of nodes to preserve the topology-anatomy correspondence
...
...
Morphing
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Statistical Shape Modelling
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• Same number of nodes• Same number of elements• Same connectivity• Preserved topology-anatomy
correspondence
Application of twoimplemented tools by:
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Current works
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• Development of a model with non-linear
contact mechanics
• Application of a ROM-based Ansys approach
• Application to different patients
Statistical shape modellingBiomechanical modelling
• Morphing of T12, L1 and L2
• Development of an SSM of T12, L1 and L2
• Machine learning techniques to predict the
shape of L1 from the shape of T12 and L2
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Acknowledgments
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This project has received funding from the European Union’s Horizon 2020 researchand innovation programme under the Marie Skłodowska-Curie grant agreementSpinner No. 766012.
Supervisors:Michel RochetteEnrico Dall’Ara
Tanguy VendeuvreMarco Biancolini
Thomas GruppChristoph Schilling