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

机译:Heidelberg-mCT-Analyzer:一种用于骨和组织研究中支架特性的标准化微计算机断层扫描引导的评估新方法

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摘要

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.
机译:骨组织工程学和骨支架的发展代表了整形外科研究中两个具有挑战性的领域。微型计算机断层扫描(mCT)可以在体内无创地测量这些支架的特性。但是,由于缺乏标准化的mCT分析协议,因此该协议的用户依赖性使得难以解释所报告的结果。为了克服支架研究中的这些问题,我们引入了Heidelberg-mCT分析仪。为了评估我们的技术,我们建立了10个骨诱导支架,这些支架在小鼠异位植入(T0)之前和移植后八周(T1)经历了mCT采集。脚手架的三维重建是使用具有自动水平设置的模糊聚类自动分割的。然后评估支架本身及其孔的T0和T1。用我们的定量方法分析了支架的特征参数集,发现随着时间的推移骨形成。我们能够证明我们的算法在基本支架参数(例如支架体积,孔数和孔体积)方面获得了与其他已建立的分析方法相同的结果。此外,我们的算法能够分析更复杂的参数,例如孔径范围,组织矿物质密度和支架表面。我们的成像和后处理策略能够对支架属性进行标准化和用户独立的分析,因此能够改善与支架相关的骨组织工程项目的定量评估。

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