The Initial Slope of the Variogram, Foundation of the Trabecular Bone Score, Is Not or Is Poorly Associated With Vertebral Strength

The relationship between bone strain index, bone mass, microarchitecture and mechanical behavior in human vertebrae: an ex vivo study

The aim of this study was to determine whether the Bone Strain Index (BSI), a recent DXA-based bone index, is related to bone mechanical behavior, microarchitecture and finally, to determine whether BSI improves the prediction of bone strength and the predictive role of BMD in clinical practice.

PURPOSE

Bone Strain Index (BSI) is a new DXA-based bone index that represents the finite element analysis of the bone deformation under load. The current study aimed to assess whether the BSI is associated with 3D microarchitecture and the mechanical behavior of human lumbar vertebrae.

METHODS

Lumbar vertebrae (L3) were harvested fresh from 31 human donors. The anteroposterior BMC (g) and aBMD (g/cm2) of the vertebral body were measured using DXA, and then the BSI was automatically derived. The trabecular bone volume (Tb.BV/TV), trabecular thickness (Tb.Th), degree of anisotropy (DA), and structure model index (SMI) were measured using µCT with a 35-µm isotropic voxel size. Quasi-static uniaxial compressive testing was performed on L3 vertebral bodies under displacement control to assess failure load and stiffness.

RESULTS

The BSI was significantly correlated with failure load and stiffness (r = -0.60 and -0.59; p < 0.0001), aBMD and BMC (r = -0.93 and -0.86; p < 0.0001); Tb.BV/TV and SMI (r = -0.58 and 0.51; p = 0.001 and 0.004 respectively). After adjustment for aBMD, the association between BSI and stiffness, BSI and SMI remained significant (r = -0.51; p = 0.004 and r = -0.39; p = 0.03 respectively, partial correlations) and the relation between BSI and failure load was close to significance (r = -0.35; p = 0.06).

CONCLUSION

The BSI was significantly correlated with the microarchitecture and mechanical behavior of L3 vertebrae, and these associations remained statistically significant regardless of aBMD.

Update on trabecular bone score

Trabecular bone score (TBS) is an indirect and noninvasive measure of bone quality. A low TBS indicates degraded bone microarchitecture, predicts osteoporotic fracture, and is partially independent of clinical risk factors and bone mineral density (BMD). There is substantial evidence supporting the use of TBS to assess vertebral, hip, and major osteoporotic fracture risk in postmenopausal women, as well as to assess hip and major osteoporotic fracture risk in men aged > 50 years. TBS complements BMD information and can be used to adjust the FRAX (Fracture Risk Assessment) score to improve risk stratification. While TBS should not be used to monitor antiresorptive therapy, it may be potentially useful for monitoring anabolic therapy. There is also a growing body of evidence indicating that TBS is particularly useful as an adjunct to BMD for fracture risk assessment in conditions associated with increased fracture risk, such as type-2 diabetes, chronic corticosteroid excess, and other conditions wherein BMD readings are often misleading. The interference of abdominal soft tissue thickness (STT) on TBS should also be considered when interpreting these findings because image noise can impact TBS evaluation. A new TBS software version based on an algorithm that accounts for STT rather than BMI seems to correct this technical limitation and is under development. In this paper, we review the current state of TBS, its technical aspects, and its evolving role in the assessment and management of several clinical conditions.

Dose-efficient assessment of trabecular microstructure using ultra-high-resolution photon-counting CT

Photon-counting (PC) detectors for clinical computed tomography (CT) may offer improved imaging capabilities compared to conventional energy-integrating (EI) detectors, e.g. superior spatial resolution and detective efficiency. We here investigate if PCCT can reduce the administered dose in examinations aimed at quantifying trabecular bone microstructure. Five human vertebral bodies were scanned three times in an abdomen phantom (QRM, Germany) using an experimental dual-source CT (Somatom CounT, Siemens Healthineers, Germany) housing an EI detector (0.60 mm pixel size at the iso-center) and a PC detector (0.25 mm pixel size). A tube voltage of 120 kV was used. Tube current-time product for EICT was 355 mAs (23.8 mGy CTDI_{32 cm}). Dose-matched UHR-PCCT (UHRdm, 23.8 mGy) and noise-matched acquisitions (UHRnm, 10.5 mGy) were performed and reconstructed to a voxel size of 0.156 mm using a sharp kernel. Measurements of bone mineral density (BMD) and trabecular separation (Tb.Sp) and Tb.Sp percentiles reflecting the different scales of the trabecular interspacing were performed and compared to a gold-standard measurement using a peripheral CT device (XtremeCT, SCANCO Medical, Switzerland) with an isotropic voxel size of 0.082 mm and 6.6 mGy CTDI_{10 cm}. The image noise was quantified and the relative error with respect to the gold-standard along with the agreement between CT protocols using Lin's concordance correlation coefficient (r_CCC) were calculated. The Mean ± StdDev of the measured image noise levels in EICT was 109.6 ± 3.9 HU. UHRdm acquisitions (same dose as EICT) showed a significantly lower noise level of 78.6 ± 4.6 HU (p = 0.0122). UHRnm (44% dose of EICT) showed a noise level of 115.8 ± 3.7 HU, very similar to EICT at the same spatial resolution. For BMD the overall Mean ± StdDev for EI, UHRdm and UHRnm were 114.8 ± 28.6 mgHA/cm³, 121.6 ± 28.8 mgHA/cm³ and 121.5 ± 28.6 mgHA/cm³, respectively, compared to 123.1 ± 25.5 mgHA/cm³ for XtremeCT. For Tb.Sp these values were 1.86 ± 0.54 mm, 1.80 ± 0.56 mm and 1.84 ± 0.52 mm, respectively, compared to 1.66 ± 0.48 mm for XtremeCT. The ranking of the vertebrae with regard to Tb.Sp data was maintained throughout all Tb.Sp percentiles and among the CT protocols and the gold-standard. The agreement between protocols was very good for all comparisons: UHRnm vs. EICT (BMD r_CCC = 0.97; Tb.Sp r_CCC = 0.998), UHRnm vs. UHRdm (BMD r_CCC = 0.998; Tb.Sp r_CCC = 0.993) and UHRdm vs. EICT (BMD r_CCC = 0.97; Tb.Sp r_CCC = 0.991). Consequently, the relative RMS-errors from linear regressions against the gold-standard for EICT, UHRdm and UHRnm were very similar for BMD (7.1%, 5.2% and 5.4%) and for Tb.Sp (3.3%, 3.3% and 2.9%), with a much lower radiation dose for UHRnm. Short-term reproducibility for BMD measurements was similar and below 0.2% for all protocols, but for Tb.Sp showed better results for UHR (about 1/3 of the level for EICT). In conclusion, CT with UHR-PC detectors demonstrated lower image noise and better reproducibility for assessments of bone microstructure at similar dose levels. For UHRnm, radiation exposure levels could be reduced by 56% without deterioration of performance levels in the assessment of bone mineral density and bone microstructure.

Bone mineral density modeling via random field: Normality, stationarity, sex and age dependence

BACKGROUND AND OBJECTIVE

Capturing the population variability of bone properties is of paramount importance to biomedical engineering. The aim of the present paper is to describe variability and correlations in bone mineral density with a spatial random field inferred from routine computed tomography data.

METHODS

Random fields were simulated by transforming pairwise uncorrelated Gaussian random variables into correlated variables through the spectral decomposition of an age-detrended correlation matrix. The validity of the random field model was demonstrated in the spatiotemporal analysis of bone mineral density. The similarity between the computed tomography samples and those generated via random fields was analyzed with the energy distance metric.

RESULTS

The random field of bone mineral density was found to be approximately Gaussian/slightly left-skewed/strongly right-skewed at various locations. However, average bone density could be simulated well with the proposed Gaussian random field for which the energy distance, i.e., a measure that quantifies discrepancies between two distribution functions, is convergent with respect to the number of correlation eigenpairs.

CONCLUSIONS

The proposed random field model allows the enhancement of computational biomechanical models with variability in bone mineral density, which could increase the usability of the model and provides a step forward in in-silico medicine.

Detecting pathological features and predicting fracture risk from dual-energy X-ray absorptiometry images using deep learning

Dual-energy X-ray absorptiometry (DXA) is the gold standard imaging method for diagnosing osteoporosis in clinical practice. The DXA images are commonly used to estimate a numerical value for bone mineral density (BMD), which decreases in osteoporosis. Low BMD is a known risk factor for osteoporotic fractures. In this study, we used deep learning to identify lumbar scoliosis and structural abnormalities that potentially affect BMD but are often neglected in lumbar spine DXA analysis. In addition, we tested the approach's ability to predict fractures using only DXA images. A dataset of 2949 images gathered by Kuopio Osteoporosis Risk Factor and Prevention Study was used to train a convolutional neural network (CNN) for classification. The model was able to classify scoliosis with an AUC of 0.96 and structural abnormalities causing unreliable BMD measurement with an AUC of 0.91. It predicted fractures occurring within 5 years from the lumbar spine DXA scan with an AUC of 0.63, meeting the predictive performance of combined BMD measurements from the lumbar spine and hip. In an independent test set of 574 clinical patients, AUC for lumbar scoliosis was 0.93 and AUC for unreliable BMD measurements was 0.94. In each classification task, neural network visualizations indicated the model's predictive strategy. We conclude that deep learning could complement the well established DXA method for osteoporosis diagnostics by analyzing incidental findings and image reliability, and improve its predictive ability in the future.

Bone Quality as Measured by Trabecular Bone Score in Normocalcemic Primary Hyperparathyroidism

OBJECTIVE

The impact of normocalcemic hyperparathyroidism (NHPT) on bone quality remains largely unexplored. We aimed to investigate the usefulness of trabecular bone score (TBS) assessment in NHPT and the accuracy of TBS in predicting vertebral fractures (VFs) in NHPT.

METHODS

In this multicentric cross-sectional study, we assessed the TBS in 47 subjects with NHPT, 41 with primary hyperparathyroidism (PHPT), and 39 age- and sex-matched control subjects.

RESULTS

TBS values did not differ among the 3 groups. The prevalence of low TBS (TBS < 1.2) was 23.4% in NHPT, 26.8% in PHPT, and 15.4% in controls, without statistically significant differences between groups. However, we found a lower lumbar spine Z-score adjusted for TBS (LS Z-score∗TBS) in PHPT participants when compared with controls (-0.48 ± 1.06 vs 0.07 ± 0.93, P = .017). In NHPT group, LS Z-score∗TBS did not detect patients with overall VFs (threshold, -0.15; area under the curve, 0.45; 95% CI, 0.253-0.648; accuracy, 55.3%). Instead, it was useful for moderate-severe VFs (threshold, 0.55; area under the curve, 0.81; 95% CI, 0.62-0.996; accuracy, 83%). In PHPT subjects also, TBS did not predict VFs.

CONCLUSION

In NHPT, TBS is not reduced. When adjusted for TBS, the LS Z-score might predict moderate-to-severe VFs.

The BALB/c mouse as a preclinical model of the age-related deterioration in the lumbar vertebra

The likelihood of experiencing an osteoporotic fracture of one or more vertebral bodies increases with age, and this increase is not solely due to sex steroid deficiency. For the purpose of assessing the effectiveness of novel therapeutic strategies in the prevention of vertebral fractures among the elderly, we hypothesized that the BALB/c mouse model of aging phenocopies the age-related decrease in human VB strength. To test this hypothesis, we assessed the age-related changes in trabecular architecture of the L6 VB, with respect to those in the distal femur metaphysis, between 6-mo. (young adulthood, n = 20/sex) and 20-mo. of age (old age, n = 18/sex) and then determined how well the architectural characteristics, volumetric bone mineral density (vBMD), and predicted failure force from μCT-derived finite element analysis (μFEA) with linear elastic failure criteria explained the age-related variance in VB strength, which was the ultimate force during quasi-static loading of the VB in compression. While there was a pronounced age-related deterioration in trabecular architecture in the distal femur metaphysis of female and male BALB/c mice, the decrease in trabecular bone volume fraction and trabecular number between 6-mo. and 20-mo. of age occurred in male mice, but not in female mice. As such, the VB strength was lower with age in males only. Nonetheless, BV/TV and volumetric bone mineral density (vBMD) positively correlated with the ultimate compressive force of the L6 VB for both females and males. Whether using a fixed homogeneous distribution of tissue modulus (E_t = 18 GPa) or a heterogeneous distribution of E_t based on a positive relationship with TMD, the predicted failure force of the VB was not independent of age, thereby suggesting linear μFEA may not be a suitable replacement for mechanical-based measurements of strength with respect to age-related changes. Overall, the BALB/c mouse model of aging mimics the age-related in decline in human VB strength when comparing 6-mo. and 20-mo. old male mice. The decrease in VB strength in female mice may occur over a different age range.

Radiofrequency echographic multi-spectrometry for the in-vivo assessment of bone strength: state of the art-outcomes of an expert consensus meeting organized by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO)

PURPOSE

The purpose of this paper was to review the available approaches for bone strength assessment, osteoporosis diagnosis and fracture risk prediction, and to provide insights into radiofrequency echographic multi spectrometry (REMS), a non-ionizing axial skeleton technique.

METHODS

A working group convened by the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis met to review the current image-based methods for bone strength assessment and fracture risk estimation, and to discuss the clinical perspectives of REMS.

RESULTS

Areal bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is the consolidated indicator for osteoporosis diagnosis and fracture risk assessment. A more reliable fracture risk estimation would actually require an improved assessment of bone strength, integrating also bone quality information. Several different approaches have been proposed, including additional DXA-based parameters, quantitative computed tomography, and quantitative ultrasound. Although each of them showed a somewhat improved clinical performance, none satisfied all the requirements for a widespread routine employment, which was typically hindered by unclear clinical usefulness, radiation doses, limited accessibility, or inapplicability to spine and hip, therefore leaving several clinical needs still unmet. REMS is a clinically available technology for osteoporosis diagnosis and fracture risk assessment through the estimation of BMD on the axial skeleton reference sites. Its automatic processing of unfiltered ultrasound signals provides accurate BMD values in view of fracture risk assessment.

CONCLUSIONS

New approaches for improved bone strength and fracture risk estimations are needed for a better management of osteoporotic patients. In this context, REMS represents a valuable approach for osteoporosis diagnosis and fracture risk prediction.

Evaluation of the capability of the simulated dual energy X-ray absorptiometry-based two-dimensional finite element models for predicting vertebral failure loads

Prediction of the vertebral failure load is of great importance for the prevention and early treatment of bone fracture. However, an efficient and effective method for accurately predicting the failure load of vertebral bones is still lacking. The aim of the present study was to evaluate the capability of the simulated dual energy X-ray absorptiometry (DXA)-based finite element (FE) model for predicting vertebral failure loads. Thirteen dissected spinal segments (T11/T12/L1) were scanned using a HR-pQCT scanner and then were mechanically tested until failure. The subject-specific three-dimensional (3D) and two-dimensional (2D) FE models of T12 were generated from the HR-pQCT scanner and the simulated DXA images, respectively. Additionally, the areal bone mineral density (aBMD) and areal bone mineral content (aBMC) of T12 were calculated. The failure loads predicted by the simulated DXA-based 2D FE models were more moderately correlated with the experimental failure loads (R² = 0.66) than the aBMC (R² = 0.61) and aBMD (R² = 0.56). The 2D FE models were slightly outperformed by the HR-pQCT-based 3D FE models (R² = 0.71). The present study demonstrated that the simulated DXA-based 2D FE model has better capability for predicting the vertebral failure loads than the densitometric measurements but is outperformed by the 3D FE model. The 2D FE model is more suitable for clinical use due to the low radiation dose and low cost, but it remains to be validated by further in vitro and in vivo studies.

The utility and limitations of using trabecular bone score with FRAX

PURPOSE OF REVIEW

Trabecular bone score (TBS) is a texture index derived from the lumbar spine dual-energy X-ray absorptiometry which can assess skeletal quality and provide information about fracture risk independent of bone mineral density (BMD). TBS is useful in assessing osteoporotic fracture risk, with lower TBS values associated with increased fracture risk. In this article, we review the current state of TBS, including its utility and limitations in the assessment and management of osteoporosis, with particular emphasis on the recent literature.

RECENT FINDINGS

Ten-year fracture risk assessment using the FRAX tool can be improved through the use of a TBS adjustment. The use of TBS-adjusted FRAX can change management in a modest but significant number of patients, particularly in those close to an intervention threshold. Change in lumbar spine TBS for patients undergoing antiresorptive treatment is not a useful indicator of antifracture effect.

SUMMARY

Lumbar spine TBS provides information complementary to conventional BMD, and has been shown to be clinically useful for enhancing fracture risk prediction.

Fracture generation in human vertebrae under compression loading: The influence of pedicle preservation and bone mineral density on in vitro fracture behavior

BACKGROUND

Fractured vertebral bodies are a common and wide spread health issue.

OBJECTIVE

The purpose of this study was to develop a standardized method to experimentally generate compression fractures in vertebral bodies. The influence of the pedicles has been investigated with regards to the fracture behavior. The correlation between bone mineral density (BMD), the cause of fractures and the fracture behavior was investigated.

METHODS

Twenty-one fresh frozen human lumbar spines were examined for bone mineral density (BMD) by means of quantitative computed tomography (qCT). All soft tissue was removed, vertebrae were carefully separated from each other and the exposed cranial and caudal endplates were covered with a thin layer of resin to generate a plane and homogeneous surface. A total of 80 vertebral bodies were tested until fracture.

RESULTS

A good positive correlation was found between BMD, fracture compression force and stiffness of the vertebral body. No significant differences were found between the fractures generated in vertebral bodies with and without pedicles, respectively.

CONCLUSIONS

Our model represents a consolidation of already existing testing devices. The comparative measurement of the BMD and the fracture behavior shows validity. In contrast to other authors, the force was applied to the whole vertebral body. Furthermore the upper and lower plates were not parallelized and therefore the natural anatomic shape was imitated. Fracture behavior was not altered by removing the pedicles.

Variogram-based evaluations of DXA correlate with vertebral strength, but do not enhance the prediction compared to aBMD alone

Ancillary evaluation of spinal Dual-energy X-ray Absorptiometry (DXA) via variogram-based texture evaluation (e.g., Trabecular Bone Score) is used for improving the fracture risk assessment, despite no proven relationship with vertebral strength. The purpose of this study was thus to determine whether classical variogram-based parameters (sill variance and correlation length) evaluated from simulated DXA scans could help predicting the in vitro vertebral strength. Experimental data of thirteen human full vertebrae (i.e., with posterior elements) and twelve vertebral bodies were obtained from two existing studies. Areal bone mineral density (aBMD) was calculated from 2D projection images of the 3D HR-pQCT scan of the specimens mimicking clinical DXA scans. Stochastic predictors, sill variance and correlation length, were calculated from their experimental variogram. Vertebral strength was measured as the maximum failure load of human vertebrae and vertebral bodies from mechanical tests. Vertebral strength correlated significantly with sill variance (r = 0.727) and correlation length (r = 0.727) for the vertebral bodies, and with correlation length (r = 0.593) for full vertebrae. However, the stochastic predictors improved the strength prediction made by aBMD alone by only 11% for the vertebral bodies while no improvement was observed for the full vertebrae. Despite a correlation, classical variogram parameters such as sill variance and correlation length do not enhance the prediction of in vitro vertebral strength beyond aBMD. It remains unclear why some variogram-based evaluations of DXA improve fracture prediction without a proven relationship with vertebral strength.

Utility of trabecular bone score in the evaluation of osteoporosis

PURPOSE OF REVIEW

Trabecular bone score (TBS) is a lumbar spine dual-energy absorptiometry texture index which provides information on skeletal quality partially independent of bone mineral density (BMD). A body of work has emerged demonstrating the relationship between TBS and fracture risk, with lower TBS values associated with increased risk for osteoporotic fracture in postmenopausal women and older men. TBS is derived from standard DXA images; however, the information provided by TBS is complementary to that provided by BMD. In this article, we review the current state of TBS and its evolving role in the assessment and management of osteoporosis, with particular emphasis on the literature of the previous year.

RECENT FINDINGS

TBS-adjusted The Fracture Risk Assessment tool (FRAX) probabilities enhance fracture risk prediction compared with conventional FRAX predictions. TBS has been found to better categorize fracture risk and assists in FRAX-based treatment decisions, particularly for patients close to an intervention threshold. However, change in lumbar spine TBS while undergoing antiresorptive treatment is not a useful indicator of antifracture effect.

SUMMARY

Lumbar spine TBS is a recently developed image-based software technique for skeletal assessment, complementary to conventional BMD, which has been shown to be clinically useful as a fracture risk prediction tool.

Trabecular bone score (TBS): Method and applications

Trabecular bone score (TBS) is a texture index derived from standard lumbar spine dual energy X-ray absorptiometry (DXA) images and provides information about the underlying bone independent of the bone mineral density (BMD). Several salient observations have emerged. Numerous studies have examined the relationship between TBS and fracture risk and have shown that lower TBS values are associated with increased risk for major osteoporotic fracture in postmenopausal women and older men, with this result being independent of BMD values and other clinical risk factors. Therefore, despite being derived from standard DXA images, the information contained in TBS is independent and complementary to the information provided by BMD and the FRAX® tool. A procedure to generate TBS-adjusted FRAX probabilities has become available with the resultant predicted fracture risks shown to be more accurate than the standard FRAX tool. With these developments, TBS has emerged as a clinical tool for improved fracture risk prediction and guiding decisions regarding treatment initiation, particularly for patients with FRAX probabilities around an intervention threshold. In this article, we review the development, validation, clinical application, and limitations of TBS.

MRI assessment of bone structure and microarchitecture

Osteoporosis is a disease of weak bone and increased fracture risk caused by low bone mass and microarchitectural deterioration of bone tissue. The standard-of-care test used to diagnose osteoporosis, dual-energy x-ray absorptiometry (DXA) estimation of areal bone mineral density (BMD), has limitations as a tool to identify patients at risk for fracture and as a tool to monitor therapy response. Magnetic resonance imaging (MRI) assessment of bone structure and microarchitecture has been proposed as another method to assess bone quality and fracture risk in vivo. MRI is advantageous because it is noninvasive, does not require ionizing radiation, and can evaluate both cortical and trabecular bone. In this review article, we summarize and discuss research progress on MRI of bone structure and microarchitecture over the last decade, focusing on in vivo translational studies. Single-center, in vivo studies have provided some evidence for the added value of MRI as a biomarker of fracture risk or treatment response. Larger, prospective, multicenter studies are needed in the future to validate the results of these initial translational studies.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 5 J. MAGN. RESON. IMAGING 2017;46:323-337.

Trabecular Bone Score: A New DXA-Derived Measurement for Fracture Risk Assessment

Trabecular bone score (TBS) is a novel method that assesses skeletal texture from spine dual-energy X-ray absorptiometry (DXA) images. TBS improves fracture-risk prediction beyond that provided by DXA bone mineral density (BMD) and clinical risk factors, and can be incorporated to the Word Health Organization Fracture Risk Assessment tool (FRAX®) to enhance fracture prediction. There is insufficient evidence that TBS can be used to monitor treatment with bisphosphonates. TBS may be particularly helpful to assess fracture risk in diabetes. This article reviews technical and clinical aspects of TBS and its potential utility as a clinical tool to predict fracture risk.

Clinical Evaluation of Bone Strength and Fracture Risk

PURPOSE OF REVIEW

This paper seeks to evaluate and compare recent advances in the clinical assessment of the changes in bone mechanical properties that take place as a result of osteoporosis and other metabolic bone diseases and their treatments.

RECENT FINDINGS

In addition to the standard of DXA-based areal bone mineral density (aBMD), a variety of methods, including imaging-based structural measurements, finite element analysis (FEA)-based techniques, and alternate methods including ultrasound, bone biopsy, reference point indentation, and statistical shape and density modeling, have been developed which allow for reliable prediction of bone strength and fracture risk. These methods have also shown promise in the evaluation of treatment-induced changes in bone mechanical properties. Continued technological advances allowing for increasingly high-resolution imaging with low radiation dose, together with the expanding adoption of DXA-based predictions of bone structure and mechanics, as well as the increasing awareness of the importance of bone material properties in determining whole-bone mechanics, lead us to anticipate substantial future advances in this field.

Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis

Stiffness and shear moduli of human trabecular bone may be analyzed in vivo by finite element (FE) analysis from image data obtained by clinical imaging equipment such as high resolution peripheral quantitative computed tomography (HR-pQCT). In clinical practice today, this is done in the peripheral skeleton like the wrist and heel. In this cadaveric bone study, fourteen bone specimens from the wrist were imaged by two dental cone beam computed tomography (CBCT) devices and one HR-pQCT device as well as by dual energy X-ray absorptiometry (DXA). Histomorphometric measurements from micro-CT data were used as gold standard. The image processing was done with an in-house developed code based on the automated region growing (ARG) algorithm. Evaluation of how well stiffness (Young's modulus E3) and minimum shear modulus from the 12, 13, or 23 could be predicted from the CBCT and HR-pQCT imaging data was studied and compared to FE analysis from the micro-CT imaging data. Strong correlations were found between the clinical machines and micro-CT regarding trabecular bone structure parameters, such as bone volume over total volume, trabecular thickness, trabecular number and trabecular nodes (varying from 0.79 to 0.96). The two CBCT devices as well as the HR-pQCT showed the ability to predict stiffness and shear, with adjusted R2-values between 0.78 and 0.92, based on data derived through our in-house developed code based on the ARG algorithm. These findings indicate that clinically used CBCT may be a feasible method for clinical studies of bone structure and mechanical properties in future osteoporosis research.