Justin Saul – Fibrin Scaffold

09/23/09


Google Presentation

Video:

 

3D Scaffold Video

fibrin scaffold movie 1 from Web Master on Vimeo.

A 3D video of the scaffold.

 

 

Axial Video

fibrin scaffold topdown from Web Master on Vimeo.

An axial video of the fibrin scaffold showing the channels.

 


Scanner Settings
Machine Xradia microXCT
Binning
1
Source Setting
40 kv, 200 µA
Source Distance
50 mm
Detector Distance 30 mm
Pixel Size
2.1426 µm
FOV 4.38 mm
Magnification 3.938 X
Exposure Time 60 s
Image Size 2048 X 2048
Number of Projections 721






 


 

Summary

Fibrin scaffolds are used in neural regeneration research to provide a framework for neurons to regenerate on. The objective of this scan was to confirm the porosity and connectivity of the neural channels in the fibrin scaffold. Knowing the porosity and connectivity was important because neurons need a relatively straight channel of constant diameter to grow in. Nondestructive CT scanning was utilized for this study because a scanning electron microscope (SEM) required that the sample be cut to reveal the pathways. Cutting the sample eliminated the possibility of confirming connections between the channels, making CT scanning particularly advantageous in this case.

Subject

The subject of the scan is a fibrin scaffold which was created by extruding 100,000 Da poly(methyl methacrylate) (pMMA) fibers in a piston extrusion system at the NC State College of Textiles. The diameter of the fibers was varied by changing the extrusion temperature and rate of uptake on the collection godets. The fibers were then packed into polytetrafluoroethylene (PTFE) molds and back filled with a fibrinogen solution which was then polymerized to fibrin with a thrombin solution. pMMA fibers were then carefully dissolved from the system by acetone washes to yield hollow conduits in the scaffold.

About the Scan

The sample was prepared by packing it into a plastic tube to prevent  it from moving during the scan.

Links and Literature

Development of Axially-Aligned Scaffolds
for Optimization of Neural Regeneration

J. M. Saul, J. B. Scott

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