Transcript Slide 1

Micro-CT symposium 31/05/07
Characterization of porous scaffold
materials for bone tissue
engineering
- Saartje Impens -
GBE project
•
2 different aims:
1. Setting up a protocol for the healing of large
and complex, but critical bone defects
2. High throughput screening of different
scaffolds (= porous structure)
 With the aid of micro-CT evaluation
1. Healing of critical bone defects
Scaffold
Scaffold seeding and
culturing with cells
Cells +
medium
Bioreactor
Bone Patient own
+ growth
defect cells
factors
Operation Haeled
bone
Room
defect
In vitro
2. High
throughput
screening
input = material
+ coating +
growth factors
Optimize
scaffold
Toxicity testing
Yes
Not Ok
If 2D plates are
possible
REJECT
Clinical
approved
scaffold
No
Ok
2D plates
Optimization
possible?
3D scaffold
Yes
No
Macrostructural & µ-CT screening
Mechanical parameters
Fluid Flow
Macrostructural
shortcoming
Further screening until
clinical approvement
Not Ok
Yes
input = cells
Ok
2D cell seeding
3D cell seeding
2D cell culture
3D cell culture
time point analysis
No
No perfusion
perfusion possible
in vivo screening
nude mice
output =
proliferation
differentiation
No
Yes
GBE strategy
• Multidisciplinary approach
Micro-CT use
1. Micro-CT based characterization of scaffolds
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Calculate structural parameters
Calculate mechanical parameters with the aid of a
FE-model
Calculate fluid flow
2. Evaluation of bone formation in explanted
scaffold
–
Replacement of histology?
1. Scaffold characterization
• Important parameters for bone formation in Matlab
– Porosity
– Specific surface area
(Mentat)
– Pore size
 As high as possible (100%)
 As high as possible
>3,95mm-1 (Ding et al. based on bone)
 100-800µm
(PorousAnalyser)
– Permeability
(PoreNet)
– Interconnectivity
 As high as possible
> 10-8m2 (Kohles et al. based on bone)
 As high as possible (100%)
• Mechanical parameters with FE-modeling (Mesh creation in Matlab)
 Expected load during walking is 1,2 x body weight
– Strength
– Stiffness
– Stretch on surface
 100% under yield strength
 17-20 GPa (cortical bone)
10-1500MPa (trabecular bone)
 (500-)1500-4000µstrain
1. Scaffold characterization
Scaffolds
Reconstructed micro-CT
Image
FE-mesh
1. Scaffold characterization
• Structural and biomechanical parameters
Scaffold characterization
• Extra important parameter for the GBE project
– Fluid flow
• Nutrient & Oxygen transport
– Wall shear stress
• May stimulate proliferation and differentiation
i.e. May stimulate bone formation
Ideally Computing Fluid Flow of microCT based models
1. Scaffold characterization
• 2D Fluid flow on µCT based model
Inflow: 1 ml/min
Scaffold:
Ø 6 mm, L 8 mm
Figures: Tim van Cleynenbreugel
1. Scaffold characterization
• 3D Fluid flow on CAD-based model
Figures: Silvia Truscello
1. Scaffold characterization
• Problems occur when meshing regular
scaffolds produced by rapid prototyping
Blue  Best
Violet
Pink
Orange
Red  Worst
Manually
remeshing
2. Substitute for Histology
• Evaluation different scaffold materials
– Time consuming
• Embedding 2 weeks
• Sectioning
– 1 scaffold/day
– Labor intensive
• Staining
– 1 day
• Analysis
– 1 scaffold/day
– Labor intensive
*
1. Scaffold characterization
2. Substitute for Histology
• Polymer scaffolds
Binarized histological
Section
Histological
image
Interpolated
micro-CT image
After registration
Green: Overlap
Blue: only histology
Red: only micro-CT
2. Substitute for Histology
• Distinguish between scaffold and bone by
thresholding?
Bone
Scaffold
Zone of bone ingrowth
 Difficult, depends on
scaffold material
2. Substitute for Histology
• Micro-CT analysis
– Micro-CT Scanning
– Micro-CT scanning
explant
– Positioning and subtracting in Mimics to
determine the amount
of bone ingrowth
2. Substitute for Histology
Conclusion
• Micro-CT is a very useful tool for this type of
research
– Scaffold parameters can be calculated
• Prior to implantation
• Non destructive
– Time consuming histology
• Can be replaced
• If necessary, histology can be performed after scanning
• If FE models and meshing problems are solved
– Fluid flow
– Wall shear stresses
can be calculated
Acknowledgement
Special thanks goes to:
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Jan Schrooten
Tim van Cleynenbreugel
Barbara Neirinck
Silvia Truscello
Greet Kerckhofs
-Thanks-
-Thanks-