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Optimization of Imaging Polymer Based Scaffolds Using X-Ray Microcomputed Tomography

Published

Author(s)

David E. Morris, Melissa L. Mather, Carl Simon Jr., John A. Crowe

Abstract

The performance of polymer based scaffolds used in regenerative medicine is linked to their structural properties and as such strategies for structural characterization of scaffolds have been developed. X-ray microscopic computed tomography (X-ray micro CT) is a widely used approach to determine produce measurements of properties such as scaffold porosity, pore size and interconnectivity. The utility of these measures, however, is highly dependent on the imaging acquisition parameters. In this work the role of resolution (spatial and angular); integration time; image averaging; and X-ray settings (tube voltage and current) on the determination of scaffold porosity was investigated. These studies were performed on a National Institute of Standards and Technology (NIST) reference scaffold (NIST RM 8396) with well defined structure. Results show that increase in image averaging and angular resolution reduces error in porosity while a rise in spatial resolution increases error. Increase in integration time and tube current, initially improve results, however, further increase causes error to rise. Lowering tube voltage reduced error until the voltage was too low for sufficient signal to be detected. Based on these findings guidelines were developed to assist in the selection of suitable image acquisition parameters to allow rapid and accurate imaging of scaffolds.
Citation
Biotechnology and Bioengineering
Volume
100B

Keywords

Scaffold characterisation, Micro CT, Image analysis, Porosity, Regenerative medicine

Citation

Morris, D. , Mather, M. , Simon Jr., C. and Crowe, J. (2012), Optimization of Imaging Polymer Based Scaffolds Using X-Ray Microcomputed Tomography, Biotechnology and Bioengineering (Accessed December 2, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created May 14, 2012, Updated October 12, 2021