Compartmental Bone Morphometry in the Mouse Femur: Reproducibility and Resolution Dependence of Microtomographic Measurements
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Microcomputed tomography (μCT) is widely used for nondestructive bone phenotyping in small animals, especially in the mouse. Here, we investigated the reproducibility and resolution dependence of μCT analysis of microstructural parameters in three different compartments in the mouse femur. Reproducibility was assessed with respect to precision error (PE%CV) and intraclass correlation coefficient (ICC). We examined 14 left femurs isolated postmortem from two strains of mice (seven per group). Measurements and analyses were repeated five times on different days. In a second step, analysis was repeated again five times for a single measurement. Resolution dependence was assessed by high-resolution measurements (10 μm) in one strain and subsequent image degrading. Reproducibility was better in full bone compartment and in cortical bone compartment in the diaphysis (PE%CV = 0.06–2.16%) than in trabecular compartment in the distal metaphysis (PE%CV = 0.59–5.24%). Nevertheless, ICC (0.92–1.00) showed a very high reliability of the assessed parameters in all regions, indicating very small variances within repeated measurements compared to the population variances. Morphometric indices computed from lower- and higher-resolution images displayed in general only weak dependence and were highly correlated with each other (R 2 = 0.91–0.99). The results show that parameters in the full and cortical compartments were very reproducible, whereas precision in the trabecular compartment was somewhat lower. Nevertheless, all compartmental analysis methods were very robust, as shown by the high ICC values, demonstrating high suitability for application in inbred strains, where highest precision is needed due to small population variances.
KeywordsMicrocomputed tomography (μCT) Inbred mouse strain Bone density Bone architecture/structure Reproducibility Resolution dependence
This study was supported by the SNF Professorship in Bioengineering of the Swiss National Science Foundation (FP 620-58097.99). The authors thank Dr. Itai Bab for providing the mice and Christoph Buser from the Seminar for Statistics (ETH Zürich) for the helpful discussions on statistics.
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