Heidelberg-mCT-Analyzer: a novel method for standardized microcomputed-tomography-guided evaluation of scaffold properties in bone and tissue research.

R Soc Open Sci

Trauma and Reconstructive Surgery, Center of Orthopedics , Traumatology, and Spinal Cord Injury, Heidelberg University Hospital, Schlierbacher Landstraße 200a, Heidelberg 69118, Germany ; HTRG - Heidelberg Trauma Research Group , Schlierbacher Landstraße 200a , Heidelberg 69118, Germany.

Published: November 2015

AI Article Synopsis

  • Bone tissue engineering and scaffold development face challenges due to the variability in micro-computed tomography (mCT) analysis protocols, which complicates the interpretation of results.
  • The Heidelberg-mCT-Analyzer was introduced to standardize mCT analysis, evaluating 10 bone-inducing scaffolds at two different time points (before and after implantation in mice).
  • The algorithm successfully matched results from established methods while also providing advanced analysis of complex parameters, enhancing the reliability and accuracy of scaffold property assessments in bone tissue engineering research.

Article Abstract

Bone tissue engineering and bone scaffold development represent two challenging fields in orthopaedic research. Micro-computed tomography (mCT) allows non-invasive measurement of these scaffolds' properties in vivo. However, the lack of standardized mCT analysis protocols and, therefore, the protocols' user-dependency make interpretation of the reported results difficult. To overcome these issues in scaffold research, we introduce the Heidelberg-mCT-Analyzer. For evaluation of our technique, we built 10 bone-inducing scaffolds, which underwent mCT acquisition before ectopic implantation (T0) in mice, and at explantation eight weeks thereafter (T1). The scaffolds' three-dimensional reconstructions were automatically segmented using fuzzy clustering with fully automatic level-setting. The scaffold itself and its pores were then evaluated for T0 and T1. Analysing the scaffolds' characteristic parameter set with our quantification method showed bone formation over time. We were able to demonstrate that our algorithm obtained the same results for basic scaffold parameters (e.g. scaffold volume, pore number and pore volume) as other established analysis methods. Furthermore, our algorithm was able to analyse more complex parameters, such as pore size range, tissue mineral density and scaffold surface. Our imaging and post-processing strategy enables standardized and user-independent analysis of scaffold properties, and therefore is able to improve the quantitative evaluations of scaffold-associated bone tissue-engineering projects.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680623PMC
http://dx.doi.org/10.1098/rsos.150496DOI Listing

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