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We apply noval techniques, the Scaling Index Method (SIM), which reveals local topology of the structure, and the Minkowski Functionals (MF), which provide four global topological characteristics, to assess strength of the trabecular network of the human bone. We compare capabilities of these methods with the standard analysis, biomechanical Finite Element Method (FEM) and morphological parameters, in prediction of bone strength and fracture risk. Our study is based on a sample of 151 specimens taken from the trabecular part of human thoracic and lumbar vertebrae in vitro, visualised using µCT imaging (isotropic resolution 26µm) and tested by uniaxial compression. The sample of donors is heterogeneous, consisting of 58 male and 54 female cadavers with a mean age of 80 ±10 years. To estimate the predictive power of the methods, we correlate texture measures derived from µCT images with the maximum compressive strength (MCS) as obtained in biomechanical tests. A linear regression analysis reveals that the failure load estimated by FEM shows the highest correlation with MCS (Pearson's correlation coefficient r=0.76). None of the methods in current study is superior to the FEM: morphometric parameters give r<0.5, global topological characteristics show r=0.73 for the first Minkowski Functional MF₁, which coincides with bone volume fraction BV/TV and r=0.61 for the second Minkowski functional MF₂, which coincides with bone surface BS. Although scaling indices provided by SIM correlate only moderately with MCS (r=0.55), texture measures based on the nonlinear combination of local (SIM) and global (MF) topological characteristics demonstrate high correlation with experimental MCS (r=0.74) and with failure load estimated by FEM (r=0.95). Additional advantage of the proposed texture measures is possibility to reveal the role of the topologically different trabecular structure elements for the bone strength.

Purpose: To investigate differences in magnetic resonance imaging (MRI) of trabecular bone at 1.5T and 3.0T and to specifically study noise effects on the visualization and quantification of trabecular architecture using conventional histomorphometric and nonlinear measures of bone structure., Materials and Methods: Sagittal MR images of 43 calcaneus specimens (donor age: 81 +/- 10 years) were acquired at 1.5T and 3.0T using gradient echo sequences. Noise was added to obtain six sets of images with decreasing signal-to-noise ratios (SNRs). Micro-CT images were obtained from biopsies taken from 37 calcaneus samples and bone strength was determined. Morphometric and nonlinear structure parameters were calculated in all datasets., Results: Originally, SNR was 1.5 times higher at 3.0T. In the simulated image sets, SNR was similar at both fields. Trabecular dimensions measured by microCT were adequately estimated by MRI, with residual errors (e(r)), ranging from 16% to 2.7% at 3.0T. Comparing e(r) at similar SNR, 3.0T consistently displayed lower errors than 1.5T (eg, bone fraction at SNR approximately 4: e(r)[3.0T] = 15%; e(r)[1.5T] = 21%, P < 0.05)., Conclusion: The advances of 3.0T compared to 1.5T in visualizing trabecular bone structure are partially SNR-independent. The better performance at 3.0T may be explained by pronounced susceptibility, enhancing the visualization of thin trabecular structures.

Purpose: To investigate in vitro the calcaneal trabecular bone structure in elderly human donors with high spatial resolution magnetic resonance (MR) imaging at 3.0 T and 1.5 T, to quantitatively compare MR measures of bone microarchitecture with those from micro-computed tomography (CT), and to compare the performance of 3.0-T MR imaging with that of 1.5-T MR imaging in differentiating donors with spinal fractures from those without spinal fractures., Materials and Methods: The study was performed in line with institutional and legislative requirements; all donors had dedicated their body for educational and research purposes prior to death. Sagittal MR images of 49 human calcaneus cadaveric specimens were obtained (mean age of donors, 79.5 years +/- 11 [standard deviation]; 26 male donors, 23 female donors). After the spatial coregistering of images acquired at 3.0-T and 1.5-T MR imaging, the signal-to-noise-ratios and structural parameters obtained at each magnetic field strength were compared in corresponding sections. Micro-CT was performed on calcaneus cores obtained from corresponding regions in 40 cadaveric specimens. Vertebral deformities of the thoracic and lumbar spine were radiographically classified by using the spinal fracture index. Diagnostic performance of the structural parameters in differentiating donors with vertebral fractures from those without was assessed by using receiver operator characteristic (ROC) analysis, including area under the ROC curve (A(z))., Results: Correlations between structural parameters at 3.0-T MR imaging and those at micro-CT were significantly higher (P < .05) than correlations between structural parameters at 1.5-T MR imaging and those at micro-CT (trabecular thickness, r = 0.76 at 3.0 T vs r = 0.57 at 1.5 T). Trabecular dimensions were amplified at 3.0 T because of increasing susceptibility artifacts. Also, higher ROC values were found for structural parameters at 3.0 T than at 1.5 T, but differences were not significant (trabecular thickness, A(z) = 0.75 at 3.0 T vs A(z) = 0.66 at 1.5 T, P > .05)., Conclusion: MR imaging at 3.0 T provided a better measure of the trabecular bone structure than did MR imaging at 1.5 T. There was a trend for better differentiation of donors with from those without osteoporotic vertebral fractures at 3.0 T than at 1.5 T., ((c) RSNA, 2006.)

We tested the hypothesis that bone mineral density (BMD) and bone mineral content (BMC) in proximal human femur specimens in the upper neck region of interest (ROI) and femoral neck axis length (FNAL) provide a significantly better prediction of femoral bone strength than standard ROIs in vitro. BMD and BMC were measured in 110 proximal femur specimens using a standard dual-energy X-ray absorptiometry (DXA) scanner. The analysis included a new ROI in the upper neck as well as the standard ROIs. FNAL was obtained from the scan images. The specimens' failure-load was measured in a mechanical loading device, simulating a fall on the greater trochanter. For the standard ROIs, correlations between failure-load and BMD ranged from R2 = 0.64 (shaft ROI) to R2 = 0.70, p < 0.001 (femoral neck). Prediction of strength by BMD did not significantly differ from those of BMC (R2 ranging from 0.65 to 0.75, p < 0.001). In the upper neck ROI, for both BMD and BMC correlations with failure-load were higher (R2 = 0.76 and 0.81, respectively; p < 0.001). A lower, yet still significant, correlation was found between FNAL and bone strength (R2 = 0.23, p < 0.001). Normalization of failure-load with respect to FNAL did not significantly increase the correlations with densitometric measures. This study provides in vitro evidence indicating that among the ROIs of the proximal femur the newly defined upper neck ROI provides the best prediction of bone strength. Only a weak association was observed between failure load and FNAL.