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    Calcif Tissue Int. 2007 Nov;81(5):394-402. Epub 2007 Oct 21.

    Particle-induced osteolysis in three-dimensional micro-computed tomography.

    Source

    Department of Orthopedics, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany. christian.wedemeyer@uni-duisburg-essen.de

    Abstract

    Small-animal models are useful for the in vivo study of particle-induced osteolysis, the most frequent cause of aseptic loosening after total joint replacement. Microstructural changes associated with particle-induced osteolysis have been extensively explored using two-dimensional (2D) techniques. However, relatively little is known regarding the 3D dynamic microstructure of particle-induced osteolysis. Therefore, we tested micro-computed tomography (micro-CT) as a novel tool for 3D analysis of wear debris-mediated osteolysis in a small-animal model of particle-induced osteolysis. The murine calvarial model based on polyethylene particles was utilized in 14 C57BL/J6 mice randomly divided into two groups. Group 1 received sham surgery, and group 2 was treated with polyethylene particles. We performed 3D micro-CT analysis and histological assessment. Various bone morphometric parameters were assessed. Regression was used to examine the relation between the results achieved by the two methods. Micro-CT analysis provides a fully automated means to quantify bone destruction in a mouse model of particle-induced osteolysis. This method revealed that the osteolytic lesions in calvaria in the experimental group were affected irregularly compared to the rather even distribution of osteolysis in the control group. This is an observation which would have been missed if histomorphometric analysis only had been performed, leading to false assessment of the actual situation. These irregularities seen by micro-CT analysis provide new insight into individual bone changes which might otherwise be overlooked by histological analysis and can be used as baseline information on which future studies can be designed.

    PMID:
    17952672
    [PubMed - indexed for MEDLINE]

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