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Proceedings Paper

Synchrotron radiation CT methods for 3D quantitative assessment of mechanically relevant ultrastructural properties in murine bone
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Paper Abstract

Recent data have shown that predicting bone strength can be greatly improved by including microarchitectural parameters in the analysis. Moreover, bone ultrastructure has been implicated as an important contributor to bone strength. We therefore hypothesized that a better understanding of phenotypes linked to bone ultrastructure will provide new insight in the assessment of bone quality and its contribution to bone strength and fracture risk. Therefore, we first developed an experimental design to assess quantitatively ultrastructural murine bone tissue properties non-invasively in three dimensions by using synchrotron radiation-based (SR) computed tomography (CT) methods with resolutions on the order of one micrometer and below. New morphometric indices were introduced to quantify ultrastructural phenotypes of murine cortical bone assessed by our SR CT-based setup, namely the canal network and the osteocyte lacunar system. These ultrastructural phenotypes were then successfully studied in two genetically distinct mouse strains. Finally, we provided strong evidence for a significant influence of the canal network on murine bone mechanics. In the long run, we believe that the morphometric analysis of the ultrastructural phenotypes and the study of bone phenotypes at different hierarchy levels, in conjunction with bone mechanics, will provide new insights in the assessment of bone quality.

Paper Details

Date Published: 12 March 2008
PDF: 12 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 691619 (12 March 2008); doi: 10.1117/12.772668
Show Author Affiliations
Philipp Schneider, ETH Zürich (Switzerland)
Romain Voide, ETH Zürich (Switzerland)
Marco Stampanoni, Paul Scherrer Institut (Switzerland)
Ralph Müller, ETH Zürich (Switzerland)

Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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