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Validation of Cortical Bone Mineral Density Distribution Using Micro-computed Tomography

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Journal Bone
Date 2017 Apr 2
PMID 28363808
Citations 16
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Abstract

Changes in the bone mineral density distribution (BMDD), due to disease or drugs, can alter whole bone mechanical properties such as strength, stiffness and toughness. The methods currently available for assessing BMDD are destructive and two-dimensional. Micro-computed tomography (μCT) has been used extensively to quantify the three-dimensional geometry of bone and to measure the mean degree of mineralization, commonly called the tissue mineral density (TMD). The TMD measurement has been validated to ash density; however parameters describing the frequency distribution of TMD have not yet been validated. In the current study we tested the ability of μCT to estimate six BMDD parameters: mean, heterogeneity (assessed by the full-width-at-half-maximum (FWHM) and the coefficient of variation (CoV)), the upper and lower 5% cutoffs of the frequency distribution, and peak mineralization) in rat sized femoral cortical bone samples. We used backscatter scanning electron microscopy (bSEM) as the standard. Aluminum and hydroxyapatite phantoms were used to identify optimal scanner settings (70kVp, and 57μA, with a 1500ms integration time). When using hydroxyapatite samples that spanned a broad range of mineralization levels, high correlations were found between μCT and bSEM for all BMDD parameters (R≥0.92, p<0.010). When using cortical bone samples from rats and various species machined to mimic rat cortical bone geometry, significant correlations between μCT and bSEM were found for mean mineralization (R=0.65, p<0.001), peak mineralization (R=0.61, p<0.001) the lower 5% cutoff (R=0.62, p<0.001) and the upper 5% cutoff (R=0.33, p=0.021), but not for heterogeneity, measured by FWHM (R=0.05, p=0.412) and CoV (R=0.04, p=0.469). Thus, while mean mineralization and most parameters used to characterize the BMDD can be assessed with μCT in rat sized cortical bone samples, caution should be used when reporting the heterogeneity.

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