Heidelberg-mCT-Analyzer

• Verfasst von: Westhauser, Fabian [VerfasserIn]
• Verfasst von: Weis, Christian [VerfasserIn]
• Verfasst von: Höllig, Melanie Elke [VerfasserIn]
• Verfasst von: Swing, Tyler [VerfasserIn]
• Verfasst von: Schmidmaier, Gerhard [VerfasserIn]
• Verfasst von: Weber, Marc-André [VerfasserIn]
• Verfasst von: Stiller, Wolfram [VerfasserIn]
• Verfasst von: Kauczor, Hans-Ulrich [VerfasserIn]
• Verfasst von: Moghaddam-Alvandi, Arash [VerfasserIn]
• Titel: Heidelberg-mCT-Analyzer
• Titelzusatz: a novel method for standardized microcomputed-tomography-guided evaluation of scaffold properties in bone and tissue research
• Verf.angabe: Fabian Westhauser, Christian Weis, Melanie Hoellig, Tyler Swing, Gerhard Schmidmaier, Marc-André Weber, Wolfram Stiller, Hans-Ulrich Kauczor and Arash Moghaddam
• E-Jahr: 2015
• Jahr: 1 November 2015
• Fussnoten: Gesehen am 30.06.2020
• Titel Quelle: Enthalten in: Royal Society (London)Royal Society Open Science
• Ort Quelle: London : Royal Soc. Publ., 2014
• Jahr Quelle: 2015
• Band/Heft Quelle: 2(2015) Artikel-Nummer 150496, 15 Seiten
• ISSN Quelle: 2054-5703
• DOI: doi:10.1098/rsos.150496
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1702953165

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.