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  • Title: Assessment of trabecular bone structure of the calcaneus using multi-detector CT: correlation with microCT and biomechanical testing.
    Author: Diederichs G, Link TM, Kentenich M, Schwieger K, Huber MB, Burghardt AJ, Majumdar S, Rogalla P, Issever AS.
    Journal: Bone; 2009 May; 44(5):976-83. PubMed ID: 19442610.
    Abstract:
    The prediction of bone strength can be improved when determining bone mineral density (BMD) in combination with measures of trabecular microarchitecture. The goal of this study was to assess parameters of trabecular bone structure and texture of the calcaneus by clinical multi-detector row computed tomography (MDCT) in an experimental in situ setup and to correlate these parameters with microCT (microCT) and biomechanical testing. Thirty calcanei in 15 intact cadavers were scanned using three different protocols on a 64-slice MDCT scanner with an in-plane pixel size of 208 microm and 500 microm slice thickness. Bone cores were harvested from each specimen and microCT images with a voxel size of 16 microm were obtained. After image coregistration, trabecular bone structure and texture were evaluated in identical regions on the MDCT images. After data acquisition, uniaxial compression testing was performed. Significant correlations between MDCT- and microCT-derived measures of bone volume fraction (BV/TV), trabecular thickness (Tb.Th) and trabecular separation (Tb.Sp) were found (range, R(2)=0.19-0.65, p<0.01 or 0.05). The MDCT-derived parameters of volumetric BMD, app. BV/TV, app. Tb.Th and app. Tb.Sp were capable of predicting 60%, 63%, 53% and 25% of the variation in bone strength (p<0.01). When combining those measures with one additional texture index (either GLCM, TOGLCM or MF.euler), prediction of mechanical competence was significantly improved to 86%, 85%, 71% and 63% (p<0.01). In conclusion, this study showed the feasibility of trabecular microarchitecture assessment using MDCT in an experimental setup simulating the clinical situation. Multivariate models of BMD or structural parameters combined with texture indices improved prediction of bone strength significantly and might provide more reliable estimates of fracture risk in patients.
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