Fractal analysis of the mandible cortical bone: correlation among fractal dimension values obtained by two processing methods from periapical radiograph and micro-computed tomography with cone-beam computed tomography.

The objectives of the present study were to assess Fractal Dimension (FD) values in the mandible cortical bone obtained from digital periapical radiographs (DPR), high-resolution microtomography (µCT), and cone-beam computed tomography (CBCT), by two processing methods: binarization (FD.b) and grayscale-based method (FD.f) and, finally, to identify the correlation among these values with other micro-architectural parameters. For this, a prospective study was conducted on 18 healthy individuals (mean age 23 ± 2.4 years old) who underwent third molar extraction. Pre-operative CBCT scans were conducted, bone fragments were removed from the retro-molar region, and DPR and µCT were performed on those bone samples. FD.b and FD.f values were calculated using three parasagittal sections for CBCT, one image for DPR, and three sections for µCT. The 3D bone microarchitecture was analyzed in µCT (voxel size: 19 µm). As a result, FD.b mean values of 1.55 ± 0.02 and 1.80 ± 0.01 were obtained for CBCT and µCT, respectively. Furthermore, FD.f mean values of 1.22 ± 0.12 for DPR, 0.99 ± 0.04 for CBCT, and 1.30 ± 0.07 for µCT were obtained. Both FD.b and FD.f values showed a good agreement. FD.f was negatively correlated with the standard deviation of the mean gray value (p = 0.003) for DPR and intra-cortical bone surface (p = 0.02) for µCT. In conclusion, image processing with or without binarization revealed different values for FD, although showing agreement. The grayscale-based method retrieved FD values correlated with the gray levels and the cortical porous network, which means that FD can be a valuable index for mandibular cortical bone evaluation. FD is associated with mineralization and microarchitecture. Nevertheless, there was no correlation between FD values obtained from low- (DPR) and high-resolution (µCT) X-ray modalities with FD obtained from the in vivo CBCT.

Subregional areal bone mineral density (aBMD) is a better predictor of heterogeneity in trabecular microstructure of vertebrae in young and aged women than subregional trabecular bone score (TBS).

BACKGROUND: Currently, bone densitometry fails to identify nearly half of those elderly patients at immediate fracture risk. To improve clinical assessment of vertebral fracture risk, we aimed to determine how the DXA-based 2D parameter Trabecular Bone Score (TBS) relates to subregional variability in 3D trabecular microstructure in young and elderly women compared to aBMD. METHODS: T12 vertebrae from 29 women (11 young: 32 ±â€¯6 years, 18 aged: 71 ±â€¯5 years) were DXA-scanned ex vivo in anterior-posterior (AP) and lateral projection providing vertebral aBMD and TBS. Additionally, aBMD and TBS were measured for three horizontal (superior, mid-horizontal, inferior) and three vertical subregions (anterior, mid-vertical, posterior) and related to 3D microstructure indices, i.e. bone volume per tissue volume (BV/TV), trabecular number and thickness (Tb.N, Tb.Th), based on HRpQCT. RESULTS: Subregional high-resolution tomography showed significant differences in trabecular parameters for both age groups: In horizontal subregions, BV/TV was lowest superiorly, Tb.Th was highest mid-horizontally, and Tb.N was lowest mid-horizontally and highest inferiorly. Correspondingly, aBMD varied between horizontal subregions, with differences depending on projection direction. TBS varied only in lateral projections of the aged group, with lower values for the mid-horizontal subregion. In vertical subregions, BV/TV, Tb.N, and aBMD were highest posteriorly for both groups. TBS did not differ between vertical subregions. Regression analysis showed aBMD as a predictor explained more of the variance in subregional 3D microstructure compared to TBS. Stepwise multi-regression analysis revealed only three combinations of subregion, projection, and group where aBMD and TBS were both significant predictors. CONCLUSIONS: Subregional aBMD reflects variations in trabecular bone microstructure better than subregional TBS for trisected regions. Specifically, lateral aBMD identifies microstructural heterogeneities independent of age and may improve prediction of vertebral strength and susceptibility to specific fracture types.