Automated 3D trabecular bone structure analysis of the proximal femur--prediction of biomechanical strength by CT and DXA.

SUMMARY: The standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone. INTRODUCTION: An automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique. METHODS: One hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter. RESULTS: The best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to R(adj) = 0.872) and allowed for a significant better prediction than DXA alone. CONCLUSION: A combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.

Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs.

PURPOSE: Texture analysis of femur radiographs may serve as a potential low cost technique to predict osteoporotic fracture risk and has received considerable attention in the past years. A further application of this technique may be the measurement of the quality of specific bone compartments to provide useful information for treatment of bone fractures. Two challenges of texture analysis are the selection of the best suitable texture measure and reproducible placement of regions of interest (ROIs). The goal of this in vitro study was to automatically place ROIs in radiographs of proximal femur specimens and to calculate correlations between various different texture analysis methods and the femurs' anchorage strength. METHODS: Radiographs were obtained from 14 femoral specimens and bone mineral density (BMD) was measured in the femoral neck. Biomechanical testing was performed to assess the anchorage strength in terms of failure load, breakaway torque, and number of cycles. Images were segmented using a framework that is based on the usage of level sets and statistical in-shape models. Five ROIs were automatically placed in the head, upper and lower neck, trochanteric, and shaft compartment in an atlas subject. All other subjects were registered rigidly, affinely, and nonlinearly, and the resulting transformation was used to map the five ROIs onto the individual femora. RESULTS: In each ROI, texture features were extracted using gray level co-occurence matrices (GLCM), third-order GLCM, morphological gradients (MGs), Minkowski dimensions (MDs), Minkowski functionals (MFs), Gaussian Markov random fields, and scaling index method (SIM). Coefficients of determination for each texture feature with parameters of anchorage strength were computed. In a stepwise multiregression analysis, the most predictive parameters were identified in different models. Texture features were highly correlated with anchorage strength estimated by the failure load of up to R2=0.61 (MF and MG features, p<0.01) and were partially independent of BMD. The correlations were dependent on the choice of the ROI and the texture measure. The best predictive multiregression model for failure load R2adj=0.86 (p<0.001) included a set of recently developed texture methods (MF and SIM) but excluded bone mineral density and commonly used texture measures. CONCLUSIONS: The results suggest that texture information contained in trabecular bone structure visualized on radiographs may predict whether an implant anchorage can be used and may determine the local bone quality from preoperative radiographs.

Detection of vancomycin resistance in enterococci by the Vitek AMS system.

The ability of the Vitek AMS system to detect vancomycin resistance in enterococci was evaluated by comparing the results to an agar dilution screen method. Of 100 strains tested, 43 were resistant and 51 were susceptible by both tests. Two strains were intermediate by Vitek but susceptible by agar screen, one was intermediate by Vitek but resistant by agar screen, and four were susceptible by Vitek but resistant by agar screen. When the Vitek intermediate and resistant results were combined, the false resistant rate was 4.4% and false susceptible rate was 8.5%. In its current format, the Vitek system appears not to have acceptable accuracy for the detection of vancomycin resistance in enterococci.

Deficient calcitonin response to calcium stimulation in postmenopausal osteoporosis?

To test whether mobilisation of immunoreactive calcitonin in response to calcium challenge is reduced in postmenopausal osteoporosis, seventeen postmenopausal osteoporotic women with compression fractures and ten normal age-matched women were given intravenous infusions of 3 mg/kg elemental calcium over a 10 min period. Blood samples were obtained 5 min before and at 0, 10, 20, and 60 min after start of infusion for the measurement of serum calcium and plasma immunoreactive calcitonin. Serum calcium increased significantly from baseline in both normal and osteoporotic groups; immunoreactive calcitonin increased significantly in the controls 10 min and 20 min after the start of infusion, but in the women with osteoporosis calcitonin levels did not change significantly at any time. 20 min after the start of infusion the change in immunoreactive calcitonin from baseline was significantly less in osteoporotic women than in the controls. These data are consistent with a decreased immunoreactive calcitonin response to calcium infusion in postmenopausal osteoporotic women, and suggest that calcitonin deficiency may be involved in the development of postmenopausal osteoporosis.