Clinical interest of bone texture analysis in osteoporosis: a case control multicenter study

Digital wrist tomosynthesis (DWT)-based finite element analysis of ultra-distal radius differentiates patients with and without a history of osteoporotic fracture

Despite effective therapies for those at risk of osteoporotic fracture, low adherence to screening guidelines and limited accuracy of bone mineral density (BMD) in predicting fracture risk preclude identification of those at risk. Because of high adherence to routine mammography, bone health screening at the time of mammography using a digital breast tomosynthesis (DBT) scanner has been suggested as a potential solution. BMD and bone microstructure can be measured from the wrist using a DBT scanner. However, the extent to which biomechanical variables can be derived from digital wrist tomosynthesis (DWT) has not been explored. Accordingly, we measured stiffness from a DWT based finite element (DWT-FE) model of the ultra-distal (UD) radius and ulna, and correlate these to reference microcomputed tomography image based FE (μCT-FE) from five cadaveric forearms. Further, this method is implemented to determine in vivo reproducibility of FE derived stiffness of UD radius and demonstrate the in vivo utility of DWT-FE in bone quality assessment by comparing two groups of postmenopausal women with and without a history of an osteoporotic fracture (Fx; n = 15, NFx; n = 51). Stiffness obtained from DWT and μCT had a strong correlation (R2 = 0.87, p < 0.001). In vivo repeatability error was <5 %. The NFx and Fx groups were not significantly different in DXA derived minimum T-scores (p > 0.3), but stiffness of the UD radius was lower for the Fx group (p < 0.007). Logistic regression models of fracture status with stiffness of the nondominant arm as the predictor were significant (p < 0.01). In conclusion this study demonstrates the feasibility of fracture risk assessment in mammography settings using DWT imaging and FE modeling in vivo. Using this approach, bone and breast screening can be performed in a single visit, with the potential to improve both the prevalence of bone health screening and the accuracy of fracture risk assessment.

Investigation of the effect of oral and internal bisphosphonate use on bone density in the jaws in patients with osteoporosis in panoramic radiography

OBJECTIVES

This study aims to quantitatively evaluate the effects of bisphosphonate use duration and route of administration on mandibular cortical and trabecular bone in postmenopausal women.

STUDY DESIGN

Ninety postmenopausal women over the age of 50 were included in this study. Trabecular bone density was specified numerically by fractal dimension (FD) in the region of interest selected on the panoramic radiograph. The width of the mandibular cortical (MCW) bone under the mental foramen of the mandible was measured. Mann-Whitney U test was used for parameters that did not show a normal distribution. Spearman rho correlation test was used to determine the relationship between continuous measurement parameters.

RESULTS

It was observed that FD and MCW of dentate and edentate individuals using bisphosphonate were statistically significantly lower than those of healthy individuals (P < .05). There was no significant correlation was found between the duration of use of bisphosphonates and the fractal values obtained from the relevant regions of the mandible (P > .05).

CONCLUSION

Fractal dimension was found to be lower in oral bisphosphonate use than in intravenous bisphosphonate use. The width of the mandibular cortical bone values was found to be lower in individuals using bisphosphonate than in healthy individuals. Fractal dimension and MCW may benefit clinicians as quantitative parameters in panoramic radiography in the diagnosis of osteoporosis.

Vertebral trabecular bone texture analysis in opportunistic MRI and CT scan can distinguish patients with and without osteoporotic vertebral fracture: A preliminary study

PURPOSE

To investigate the potential of texture parameters from opportunistic MRI and CT for the detection of patients with vertebral fragility fracture, to design a decision tree and to compute a Random Forest analysis for the prediction of fracture risk.

METHODS

One hundred and eighty vertebrae of sixty patients with at least one (30) or without (30) a fragility fracture were retrospectively assessed. Patients had a DXA, an MRI and a CT scan from the three first lumbar vertebrae. Vertebrae texture analysis was performed in routine abdominal or lumbar CT and lumbar MRI using 1st and 2nd order texture parameters. Hounsfield Unit Bone density (HU BD) was also measured on CT-scan images.

RESULTS

Twelve texture parameters, Z-score and HU BD were significantly different between the two groups whereas T score and BMD were not. The inter observer reproducibility was good to excellent. Decision tree showed that age and HU BD were the most relevant factors to predict the fracture risk with a 93 % sensitivity and 56 % specificity. AUC was 0.91 in MRI and 0.92 in CT-scan using the Random Forest analysis. The corresponding sensitivity and specificity were 72 % and 93 % in MRI and 83 and 89 % in CT.

CONCLUSIONS

This study is the first to compare texture indices computed from opportunistic CT and MR images. Age and HU-BD together with selected texture parameters could be used to assess risk fracture. Machine learning algorithm can detect fracture risk in opportunistic CT and MR imaging and might be of high interest for the diagnosis of osteoporosis.

Comparison of the Classification Results Accuracy for CT Soft Tissue and Bone Reconstructions in Detecting the Porosity of a Spongy Tissue

The aim of the study was to compare the accuracy of the classification pertaining to the results of two types of soft tissue and bone reconstructions of the spinal CT in detecting the porosity of L1 vertebral body spongy tissue. The dataset for each type of reconstruction (high-resolution bone reconstruction and soft tissue reconstruction) included 400 sponge tissue images from 50 healthy patients and 50 patients with osteoporosis. Texture feature descriptors were calculated based on the statistical analysis of the grey image histogram, autoregression model, and wavelet transform. The data dimensional reduction was applied by feature selection using nine methods representing various approaches (filter, wrapper, and embedded methods). Eleven methods were used to build the classifier models. In the learning process, hyperparametric optimization based on the grid search method was applied. On this basis, the most effective model and the optimal subset of features for each selection method used were determined. In the case of bone reconstruction images, four models achieved a maximum accuracy of 92%, one of which had the highest sensitivity of 95%, with a specificity of 89%. For soft tissue reconstruction images, five models achieved the highest testing accuracy of 95%, whereas the other quality indices (TPR and TNR) were also equal to 95%. The research showed that the images derived from soft tissue reconstruction allow for obtaining more accurate values of texture parameters, which increases the accuracy of the classification and offers better possibilities for diagnosing osteoporosis.

Deep Radiomics-based Approach to the Diagnosis of Osteoporosis Using Hip Radiographs

PURPOSE

To develop and validate deep radiomics models for the diagnosis of osteoporosis using hip radiographs.

MATERIALS AND METHODS

A deep radiomics model was developed using 4924 hip radiographs from 4308 patients (3632 women; mean age, 62 years ± 13 [SD]) obtained between September 2009 and April 2020. Ten deep features, 16 texture features, and three clinical features were used to train the model. T score measured with dual-energy x-ray absorptiometry was used as a reference standard for osteoporosis. Seven deep radiomics models that combined different types of features were developed: clinical (model C); texture (model T); deep (model D); texture and clinical (model TC); deep and clinical (model DC); deep and texture (model DT); and deep, texture, and clinical features (model DTC). A total of 444 hip radiographs obtained between January 2019 and April 2020 from another institution were used for the external test. Six radiologists performed an observer performance test. The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic performance.

RESULTS

For the external test set, model D (AUC, 0.92; 95% CI: 0.89, 0.95) demonstrated higher diagnostic performance than model T (AUC, 0.77; 95% CI: 0.70, 0.83; adjusted P < .001). Model DC (AUC, 0.95; 95% CI: 0.92, 0.97; adjusted P = .03) and model DTC (AUC, 0.95; 95% CI: 0.92, 0.97; adjusted P = .048) showed improved diagnostic performance compared with model D. When observer performance without and with the assistance of the model DTC prediction was compared, performance improved from a mean AUC of 0.77 to 0.87 (P = .002).

CONCLUSION

Deep radiomics models using hip radiographs could be used to diagnose osteoporosis with high performance.Keywords: Skeletal-Appendicular, Hip, Absorptiometry/Bone Densitometry© RSNA, 2022.

Assessment of dynamic balance during walking in patients with adult spinal deformity

PURPOSE

To assess dynamic postural alignment in ASD during walking using a subject-specific 3D approach.

METHODS

69 ASD (51 ± 20 years, 77%F) and 62 controls (34 ± 13 years, 62%F) underwent gait analysis along with full-body biplanar Xrays and filled HRQoL questionnaires. Spinopelvic and postural parameters were computed from 3D skeletal reconstructions, including radiographic odontoid to hip axis angle (ODHA) that evaluates the head's position over the pelvis (rODHA), in addition to rSVA and rPT. The 3D bones were then registered on each gait frame to compute the dynamic ODHA (dODHA), dSVA, and dPT. Patients with high dODHA (> mean + 1SD in controls) were classified as ASD-DU (dynamically unbalanced), otherwise as ASD-DB (dynamically balanced). Between-group comparisons and relationship between parameters were investigated.

RESULTS

26 patients were classified as ASD-DU having an average dODHA of 10.4° (ASD-DB: 1.2°, controls: 1.7°), dSVA of 112 mm (ASD-DB: 57 mm, controls: 43 mm), and dPT of 21° (ASD-DB: 18°, controls: 14°; all p < 0.001). On static radiographs, ASD-DU group showed more severe sagittal malalignment than ASD-DB, with more altered HRQoL outcomes. The ASD-DU group had an overall abnormal walking compared to ASD-DB & controls (gait deviation index: 81 versus 93 & 97 resp., p < 0.001) showing a reduced flexion/extension range of motion at the hips and knees with a slower gait speed and shorter step length. Dynamic ODHA was correlated to HRQoL scores.

CONCLUSION

Dynamically unbalanced ASD had postural malalignment that persist during walking, associated with kinematic alterations in the trunk, pelvis, and lower limbs, making them more prone to falls. Dynamic-ODHA correlates better with HRQoL outcomes than dSVA and dPT.

Fractal dimension analysis on CBCT scans for detecting low bone mineral density in postmenopausal women

Purpose

The aim of this study was to compare the fractal dimension (FD) measured at 2 bone sites (second cervical vertebra and mandible) on cone-beam computed tomography (CBCT). The research question was whether FD could serve as an accessory tool to refer postmenopausal women for densitometric analysis. Therefore, the reliability and accuracy of FD were evaluated.

Materials and Methods

In total, 103 postmenopausal women were evaluated, of whom 52 had normal bone mineral density and 51 had osteoporosis, according to dual X-ray absorptiometry of the lumbar spine and hip. On the CBCT scans, 2 regions of interest were selected for FD analysis: 1 at the second cervical vertebra and 1 located at the mandible. The correlations between both measurements, intra- and inter-observer agreement, and the accuracy of the measurements were calculated. A P value less than 0.05 was considered to indicate statistical significance for all tests.

Results

The mean FD values were significantly lower at the mandibular region of interest in osteoporotic patients than in individuals with normal bone mineral density. The areas under the curve were 0.644 (P=0.008) and 0.531 (P=0.720) for the mandibular and vertebral sites, respectively.

Conclusion

FD at the vertebral site could not be used as an adjuvant tool to refer women for osteoporosis investigation. Although FD differed between women with normal BMD and osteoporosis at the mandibular site, it demonstrated low accuracy and reliability.

Prediction of mechanical properties of human rib cortical bone using fractal dimension

A large number of post mortem human subjects was used to investigate the relation between the micro-structure of rib cortical bone and the mechanical properties using Fractal Dimension. Uniaxial tensile tests were performed on coupons of rib cortical bone. Tensile strength, yield stress, Young's Modulus, maximum strain, and work to fracture were determined for each coupon. Fractal dimension was computed using CT images and Digital Image Correlation procedures. A highly significant effect of fractal dimension in the mechanical properties was found. In addition, the variation in mechanical properties was found to be adequately represented by Generalized Extreme Value type distributions.

Texture Analysis and Genetic Algorithms for Osteoporosis Diagnosis

Early diagnosis of osteoporosis can efficiently predict fracture risk. There is a great demand to prevent this disease. The goal of this study was to distinguish osteoporotic cases from healthy controls on 2D bone radiograph images, using texture analysis and genetic algorithms (GAs). Gray Level Co-occurrence Matrix (GLCM), Run length Matrix (RLM) and Binarized Statistical Image Features (BSIF) were used for texture analysis. Features are numerous and parameter-dependent. The related experts can pick out the useful input features for the classifier. It however remains a difficult task and may be inefficient or even harmful as the data pattern is not clear. In this paper, GAs were used to optimize the two parameters of the co-occurrence matrix (distance parameter or pixel separation, orientation or direction) and the number of gray levels used in the preprocessing quantification step. GAs were also used to select the best combination of features extracted from GLCM and RLM matrices. Experiments were conducted on two populations composed of Osteoporotic Patients and Control Subjects. Results show that GAs combined with GLCM and BSIF features can improve the classification rates (ACC = 87.50%) obtained using GLCM (ACC = 77.8%) alone.

Enhancing hip fracture risk prediction by statistical modeling and texture analysis on DXA images

Each year in the US more than 300,000 older adults suffer from hip fractures. While protective measures exist, identification of those at greatest risk by DXA scanning has proved inadequate. This study proposed a new technique to enhance hip fracture risk prediction by accounting for many contributing factors to the strength of the proximal femur. Twenty-two isolated cadaveric femurs were DXA scanned, 16 of which had been mechanically tested to failure. A function consisting of the calculated modes from the statistical shape and appearance modeling (to consider the shape and BMD distribution), homogeneity index (representing trabecular quality), BMD, age and sex of the donor was created in a training set and used to predict the fracture load in a test group. To classify patients as "high risk" or "low risk", fracture load thresholds were investigated. Hip fracture load estimation was significantly enhanced using the new technique in comparison to using t-score or BMD alone (average R² of 0.68, 0.32, and 0.50, respectively) (P < 0.05). Using a fracture cut-off of 3400 N correctly predicted risk in 94% of specimens, a substantial improvement over t-score classification (38%). Ultimately, by identifying patients at high risk more accurately, devastating hip fractures can be prevented through applying protective measures.

Osteoporosis Recognition in Rats under Low-Power Lens Based on Convexity Optimization Feature Fusion

Considering the poor medical conditions in some regions of China, this paper attempts to develop a simple and easy way to extract and process the bone features of blurry medical images and improve the diagnosis accuracy of osteoporosis as much as possible. After reviewing the previous studies on osteoporosis, especially those focusing on texture analysis, a convexity optimization model was proposed based on intra-class dispersion, which combines texture features and shape features. Experimental results show that the proposed model boasts a larger application scope than Lasso, a popular feature selection method that only supports generalized linear models. The research findings ensure the accuracy of osteoporosis diagnosis and enjoy good potentials for clinical application.

Mandibular bone effects of botulinum toxin injections in masticatory muscles in adult

OBJECTIVE

Botulinum toxin (BTX) is injected into masticatory muscles to treat various conditions. Animal studies have demonstrated bone loss at the condylar and alveolar regions of the mandible after BTX injection into masticatory muscles. The aim of the present study was to investigate mandibular bone changes in patients who received BTX injections in masticatory muscles.

STUDY DESIGN

Twelve adult patients who received BTX injections into masticatory muscles were included in this study. Cone beam computed tomography (CBCT) was performed before and 12 months after the injection. The condylar and alveolar regions of the mandible were analyzed by using texture analysis of the CBCT images with the run length method. Condylar cortical thickness was measured, and 3-dimensional analysis of the mandible was also performed. Six patients who did not receive BTX injections were used as controls.

RESULTS

A run length parameter (gray level nonuniformity) was found to be increased in condylar and alveolar bones. A significant cortical thinning was found at the anterior portion of the right condyle. Three-dimensional analysis showed significant changes in the condylar bone and at the digastric fossa. No changes in mandibular angles were found.

CONCLUSIONS

This study identified mandibular bone changes in adult patients who received BTX injection into masticatory muscles.

Assessing the effects of long-term osteoporosis treatment by using conventional spine radiographs: results from a pilot study in a sub-cohort of a large randomized controlled trial

OBJECTIVE

To evaluate the clinical applicability of a software tool developed to extract bone textural information from conventional lumbar spine radiographs, and to test it in a subset of postmenopausal women treated for osteoporosis with the fully human monoclonal antibody denosumab.

METHODS

The software was developed based on the principles of a fractal model using pixel grey-level variations together with a specific machine-learning algorithm. The obtained dimensionless parameter, termed bone structure value (BSV), was then tested and compared to bone mineral density (BMD) in a sub-cohort of postmenopausal women with osteoporosis who were treated with the monoclonal antibody denosumab, within the framework of a large randomized controlled trial and its open-label extension phase.

RESULTS

After 3 years and after 8 years of treatment with denosumab, mean lumbar spine BMD as well as mean lumbar BSV were significantly higher compared to study entry (one-way repeated measures ANOVA for DXA: F = 108.2, p < 0.00001; and for BSV: F = 84.3, p < 0.00001). The overall increase in DXA-derived lumbar spine BMD at year 8 was + 42% (mean ± SD; 0.725 ± 0.038 g/cm² to 1.031 ± 0.092 g/cm²; p < 0.0001), and the overall increase of BSV was 255% (mean ± SD; 0.076 ± 0.022 to 0.270 ± 0.09, p < 0.0001). Overall, BMD and BSV were significantly correlated (R = 0.51; p < 0.0001).

CONCLUSIONS

This pilot study provides evidence that lumbar spine BSV as obtained from conventional radiographs constitutes a useful means for the assessment of bone-specific treatment effects in postmenopausal women with osteoporosis.

Current and Emerging Diagnostic Imaging-Based Techniques for Assessment of Osteoporosis and Fracture Risk

Osteoporosis is a metabolic bone disorder characterized by low bone mass, degradation of bone microarchitecture, and susceptibility to fracture. It is a growing major health concern across the world, especially in the elderly population. Osteoporosis can cause hip or spinal fractures that may lead to high morbidity and socio-economic burden. Therefore, there is a need for early diagnosis of osteoporosis and prediction of fragility fracture risk. In this review, state of the art and recent advances in imaging techniques for diagnosis of osteoporosis and fracture risk assessment have been explored. Segmentation methods used to segment the regions of interest and texture analysis methods used for classification of healthy and osteoporotic subjects are also presented. Furthermore, challenges posed by the current diagnostic tools have been studied and feasible solutions to circumvent the limitations are discussed. Early diagnosis of osteoporosis and prediction of fracture risk require the development of highly precise and accurate low-cost diagnostic techniques that would help the elderly population in low economies.

The QUALYOR (QUalité Osseuse LYon Orléans) study: a new cohort for non invasive evaluation of bone quality in postmenopausal osteoporosis. Rationale and study design

The diagnostic performance of densitometry is inadequate. New techniques of non-invasive evaluation of bone quality may improve fracture risk prediction. Testing the value of these techniques is the goal of the QUALYOR cohort.

INTRODUCTION

The bone mineral density (BMD) of postmenopausal women who sustain osteoporotic fracture is generally above the World Health Organization definition for osteoporosis. Therefore, new approaches to improve the detection of women at high risk for fracture are warranted.

METHODS

We have designed and recruited a new cohort to assess the predictive value of several techniques to assess bone quality, including high-resolution peripheral quantitative computerized tomography (HRpQCT), hip QCT, calcaneus texture analysis, and biochemical markers. We have enrolled 1575 postmenopausal women, aged at least 50, with an areal BMD femoral neck or lumbar spine T-score between - 1.0 and - 3.0. Clinical risk factors for fracture have been collected along with serum and blood samples.

RESULTS

We describe the design of the QUALYOR study. Among these 1575 women, 80% were aged at least 60. The mean femoral neck T-score was - 1.6 and the mean lumbar spine T-score was -1.2. This cohort is currently being followed up.

CONCLUSIONS

QUALYOR will provide important information on the relationship between bone quality variables and fracture risk in women with moderately decreased BMD.

Anisotropic Discrete Dual-Tree Wavelet Transform for Improved Classification of Trabecular Bone

This paper deals with a new anisotropic discrete dual-tree wavelet transform (ADDTWT) to characterize the anisotropy of bone texture. More specifically, we propose to extend the conventional discrete dual-tree wavelet transform (DDTWT) by using the anisotropic basis functions associated with the hyperbolic wavelet transform instead of isotropic spectrum supports. A texture classification framework is adopted to assess the performance of the proposed transform. The generalized Gaussian distribution is used to model the distribution of the sub-band coefficients. The estimated vector of parameters for each image is then used as input for the support vector machine classifier. Experiments were conducted on synthesized anisotropic fractional Brownian motion fields and on a real database composed of osteoporotic patients and control cases. Results show that the ADDTWT outperforms most of the competing anisotropic transforms with an area under curve rate of 93%.

The use of bone mineral density measured by dual energy X-ray absorptiometry (DXA) and peripheral quantitative computed microtomography in chronic kidney disease

Chronic kidney disease (CKD) is a risk factor for fractures. The current evaluation of fracture risk is based upon the combination of various clinical factors and quantitative imaging of bone. X-ray-based tools were developed to evaluate bone status and predict fracture risk. Dual energy X-ray absorptiometry (DXA) is available worldwide. Longitudinal studies showed that low areal Bone Mineral Density (BMD) measured by DXA predicts fractures in the CKD population as it does in non uremic populations, with good specificity and moderate sensitivity. Peripheral quantitative computed tomography (pQCT) and high resolution pQCT are research tools which measure volumetric BMD at the tibia and radius. They are able to discriminate between the cortical and trabecular envelopes which are differentially affected by renal osteodystrophy. In CKD, a rapid thinning and increased porosity at the cortex is observed which is associated with increased the risk for fracture.

Fractional Brownian Motion and Rao Geodesic Distance for Bone X-Ray Image Characterization

Osteoporosis diagnosis has attracted particular attention in recent decades. Textured images from the microarchitecture of osteoporotic and healthy subjects show a high degree of similarity, increasing the difficulty of classifying such textures. Thus, the evaluation of osteoporosis from the bone X-ray images presents a major challenge for pattern recognition and medical applications. The purpose of this paper is to use the fractional Brownian motion (fBm) model and the probability density function of its increments to compute a similarity measure with the Rao geodesic distance to classify trabecular bone X-ray images. When evaluated on synthetic fBm images (test vectors) with the well-known Hurst parameter H, the proposed method met our expectations in which a good classification of the synthetic images was achieved. A clinical study was conducted on textured bone X-ray images from two different female populations of osteoporotic patients (fracture cases) and control subjects. Using the proposed method, an area under curve rate of 97% was achieved.

Fracture discrimination by combined bone mineral density (BMD) and microarchitectural texture analysis

The use of bone mineral density (BMD) for fracture discrimination may be improved by considering bone microarchitecture. Texture parameters such as trabecular bone score (TBS) or mean Hurst parameter (H) could help to find women who are at high risk of fracture in the non-osteoporotic group. The purpose of this study was to combine BMD and microarchitectural texture parameters (spine TBS and calcaneus H) for the detection of osteoporotic fractures. Two hundred and fifty five women had a lumbar spine (LS), total hip (TH), and femoral neck (FN) DXA. Additionally, texture analyses were performed with TBS on spine DXA and with H on calcaneus radiographs. Seventy-nine women had prevalent fragility fractures. The association with fracture was evaluated by multivariate logistic regressions. The diagnostic value of each parameter alone and together was evaluated by odds ratios (OR). The area under curve (AUC) of the receiver operating characteristics (ROC) were assessed in models including BMD, H, and TBS. Women were also classified above and under the lowest tertile of H or TBS according to their BMD status. Women with prevalent fracture were older and had lower TBS, H, LS-BMD, and TH-BMD than women without fracture. Age-adjusted ORs were 1.66, 1.70, and 1.93 for LS, FN, and TH-BMD, respectively. Both TBS and H remained significantly associated with fracture after adjustment for age and TH-BMD: OR 2.07 [1.43; 3.05] and 1.47 [1.04; 2.11], respectively. The addition of texture parameters in the multivariate models didn't show a significant improvement of the ROC-AUC. However, women with normal or osteopenic BMD in the lowest range of TBS or H had significantly more fractures than women above the TBS or the H threshold. We have shown the potential interest of texture parameters such as TBS and H in addition to BMD to discriminate patients with or without osteoporotic fractures. However, their clinical added values should be evaluated relative to other risk factors.

Textural entropy as a potential feature for quantitative assessment of jaw bone healing process

INTRODUCTION

The aim of the study was to propose and evaluate textural entropy as a parameter for bone healing assessment.

MATERIAL AND METHODS

One hundred and twenty radiographs with loss of bone architecture were investigated (a bone defect was circumscribed - ROI DEF). A reference region (ROI REF) of the same surface area as the ROI DEF was placed in a field distant from the defect, where a normal, trabecular pattern of bone structure was well visualized. Data of three time points were investigated: T0 - immediately after the surgical procedure, T1 - 3 months post-op, and T2 - 12 months post-op.

RESULTS

Textural entropy as a parameter describing bone structure regeneration was selected based on Fisher coefficient (F) evaluation. F was highest in T0 (3.4) and was decreasing later in T1 (1.7) and T2 (1.0 - means final lack of difference in the structure to reference bone). Textural entropy is a measure of structure disarrangement which in a bone defect region attains minimal value due to structural homogeneity, i.e. low complexity of the texture. The calculated parameter in the investigated material revealed a gradual increase inside the bone defect (p < 0.05), i.e. increase of complexity in a time-dependent manner starting from immediate post-op (T0 = 2.51; T1 = 2.68) up to most complex 1 year post-operational (T2 = 2.73), reaching the reference level of a normal bone.

CONCLUSIONS

Textural entropy may be useful for computer assisted evaluation of bone regeneration process. The complexity of the texture corresponds to mature trabecular bone formation.

Random field assessment of inhomogeneous bone mineral density from DXA scans can enhance the differentiation between postmenopausal women with and without hip fractures

Bone mineral density (BMD) measurements from Dual-energy X-ray Absorptiometry (DXA) alone cannot account for all factors associated with the risk of hip fractures. For example, the inhomogeneity of bone mineral density in the hip region also contributes to bone strength. In the stochastic assessment of bone inhomogeneity, the BMD map in the hip region is considered as a random field and stochastic predictors can be calculated by fitting a theoretical model onto the experimental variogram of the BMD map. The objective of this study was to compare the ability of bone mineral density and stochastic assessment of inhomogeneous distribution of bone mineral density in predicting hip fractures for postmenopausal women. DXA scans in the hip region were obtained from postmenopausal women with hip fractures (N=47, Age: 71.3±11.4 years) and without hip fractures (N=45, Age: 66.7±11.4 years). Comparison of BMD measurements and stochastic predictors in assessing bone fragility was based on the area under the receiver operating characteristic curves (AUC) from logistic regression analyses. Although stochastic predictors offered higher accuracy (AUC=0.675) in predicting the risk of hip fractures than BMD measurements (AUC=0.625), this difference was not statistically significant (p=0.548). Nevertheless, the combination of stochastic predictors and BMD measurements had significantly (p=0.039) higher prediction accuracy (AUC=0.748) than BMD measurements alone. This study demonstrates that stochastic assessment of bone mineral distribution from DXA scans can serve as a valuable tool in enhancing the prediction of hip fractures for postmenopausal women in addition to BMD measurements.

Assessment of risk of femoral neck fracture with radiographic texture parameters: a retrospective study

PURPOSE

To investigate whether femoral neck fracture can be predicted retrospectively on the basis of clinical radiographs by using the combined analysis of bone geometry, textural analysis of trabecular bone, and bone mineral density (BMD).

MATERIALS AND METHODS

Formal ethics committee approval was obtained for the study, and all participants gave informed written consent. Pelvic radiographs and proximal femur BMD measurements were obtained in 53 women aged 79-82 years in 2006. By 2012, 10 of these patients had experienced a low-impact femoral neck fracture. A Laplacian-based semiautomatic custom algorithm was applied to the radiographs to calculate the texture parameters along the trabecular fibers in the lower neck area for all subjects. Intra- and interobserver reproducibility was calculated by using the root mean square average coefficient of variation to evaluate the robustness of the method.

RESULTS

The best predictors of hip fracture were entropy (P = .007; reproducibility coefficient of variation < 1%), the neck-shaft angle (NSA) (P = .017), and the BMD (P = .13). For prediction of fracture, the area under the receiver operating characteristic curve was 0.753 for entropy, 0.608 for femoral neck BMD, and 0.698 for NSA. The area increased to 0.816 when entropy and NSA were combined and to 0.902 when entropy, NSA, and BMD were combined.

CONCLUSION

Textural analysis of pelvic radiographs enables discrimination of patients at risk for femoral neck fracture, and our results show the potential of this conventional imaging method to yield better prediction than that achieved with dual-energy x-ray absorptiometry-based BMD. The combination of the entropy parameter with NSA and BMD can further enhance predictive accuracy.

Trabecular homogeneity index derived from plain radiograph to evaluate bone quality

Radiographic texture analysis has been developed lately to improve the assessment of bone architecture as a determinant of bone quality. We validate here an algorithm for the evaluation of trabecular homogeneity index (HI) in the proximal femur from hip radiographs, with a focus on the impact of the principal compressive system of the trabecular bone, and evaluate its correlation with femoral strength, bone mineral density (BMD), and volumetric trabecular structure parameters. A semiautomatic custom-made algorithm was applied to calculate the HI in the femoral neck and trochanteric areas from radiographs of 178 femoral bone specimens (mean age 79.3 ± 10.4 years). Corresponding neck region was selected in CT scans to calculate volumetric parameters of trabecular structure. The site-specific BMDs were assessed from dual-energy X-ray absorptiometry (DXA), and the femoral strength was experimentally tested in side-impact configuration. Regression analysis was performed between the HI and biomechanical femoral strength, BMD, and volumetric parameters. The correlation between HI and failure load was R(2)  = 0.50; this result was improved to R(2)  = 0.58 for cervical fractures alone. The discrimination of bones with high risk of fractures (load <3000 N) was similar for HI and BMD (AUC = 0.87). Regression analysis between the HIs versus site-specific BMDs yielded R(2)  = 0.66 in neck area, R(2)  = 0.60 in trochanteric area, and an overall of R(2)  = 0.66 for the total hip. Neck HI and BMD correlated significantly with volumetric structure parameters. We present here a method to assess HI that can explain 50% of an experimental failure load and determines bones with high fracture risk with similar accuracy as BMD. The HI also had good correlation with DXA and computed tomography-derived data.

Fractal dimension and mandibular cortical width in normal and osteoporotic men and women

OBJECTIVE

To verify whether fractal dimensions (FD) on the mandibular trabecular and cortical bone and mandibular cortical width (MCW) differ between patients with normal bone mineral density (BMD) and osteoporosis.

STUDY DESIGN

In this retrospective study, 133 dental panoramic radiographs from men aged >60 years and postmenopausal women with a bone densitometry report of the lumbar spine and hip classified as either normal or osteoporotic were selected. Fractal dimensions of five standardized trabecular and cortical mandibular regions of interest and mandibular cortical width were measured on the panoramic radiographs by an experienced oral radiologist, blinded to the densitometric diagnosis. The following statistical analyses were performed: ANOVA and a forward logistic stepwise regression to verify associations between dental panoramic measurements and the densitometric diagnosis. P values less than .05 indicated statistical significance.

MAIN OUTCOME MEASURES

Fractal dimension and mandibular cortical width.

RESULTS

Differences were found in the FD values on mandibular cortical bone and MCW between patients with normal BMD and with osteoporosis, but not in the FD values of trabecular bone. The odds of having lower mean values of MCW and FD on cortical bone were 2.16, 3125 and 1005 times in osteoporotic patients, respectively, compared with patients with normal BMD.

CONCLUSION

The values of FD analysis on mandibular cortical bone and MCW were lower in women with osteoporosis. A well-adjusted logistic regression model showed that cortical bone measurements might be considered as auxiliary tools to referring patients for DXA exam.

Radiographical texture analysis improves the prediction of vertebral fracture: an ex vivo biomechanical study

STUDY DESIGN

Compression biomechanical tests using fresh cadaveric thoracolumbar motion segments.

OBJECTIVE

The purpose of this study was to determine if the combination of bone texture parameters using bone microarchitecture, and bone mineral density (BMD) measurement by dual-energy x-ray absorptiometry provided a better prediction of vertebral fracture than BMD evaluation alone.

SUMMARY OF BACKGROUND DATA

Bone strength is routinely evaluated using BMD, as measured by dual-energy x-ray absorptiometry. Currently, there is an ongoing debate about the strengths and limitations of bone densitometry in clinical practice. To assess the fracture risk properly, other factors are important to be taken into account such as the macro- and microarchitecture of the bone. Recently, a new high-resolution x-ray device with direct digitization, named bone microarchitecture (BMA, D3A Medical Systems), has been developed to provide a better precision of texture parameters than those previously obtained on digitized films.

METHODS

Twenty-seven 3-level thoracolumbar motion segments (T11, T12, L1, and L2, L3, L4) of excised spines, obtained at the Anatomy Department of Marseille, were studied using bone microarchitecture to estimate 3 textural parameters: fractal parameter Hmean, co-occurrence matrix, and run-length matrix, dual-energy x-ray absorptiometry to measure BMD, and mechanical compression tests to failure. All specimens were examined by computed tomography before and after compression. The prediction of the vertebral failure load was evaluated using multiple regression analyses.

RESULTS

Twenty-seven vertebral fractures were observed with a mean failure load of 2636.3 N (standard deviation, 996 N). Fractal parameter Hmean, co-occurrence matrix, and run-length matrix were each significantly correlated with BMD (P< 0.01) and bone strength (P< 0.01). Combining bone texture parameters and BMD significantly improved the fracture load prediction from adjusted r = 0.701 to adjusted r = 0.806 (P< 0.01).

CONCLUSION

In these excised vertebrae, the combination of bone texture parameters with BMD demonstrated a better performance in the failure load prediction than that of BMD alone.

LEVEL OF EVIDENCE

N/A.

Biomechanical properties and microarchitecture parameters of trabecular bone are correlated with stochastic measures of 2D projection images

It is well known that loss of bone mass, quantified by areal bone mineral density (aBMD) using DXA, is associated with the increasing risk of bone fractures. However, bone mineral density alone cannot fully explain changes in fracture risks. On top of bone mass, bone architecture has been identified as another key contributor to fracture risk. In this study, we used a novel stochastic approach to assess the distribution of aBMD from 2D projection images of Micro-CT scans of trabecular bone specimens at a resolution comparable to DXA images. Sill variance, a stochastic measure of distribution of aBMD, had significant relationships with microarchitecture parameters of trabecular bone, including bone volume fraction, bone surface-to-volume ratio, trabecular thickness, trabecular number, trabecular separation and anisotropy. Accordingly, it showed significantly positive correlations with strength and elastic modulus of trabecular bone. Moreover, a combination of aBMD and sill variance derived from the 2D projection images (R2=0.85) predicted bone strength better than using aBMD alone (R2=0.63). Thus, it would be promising to extend the stochastic approach to routine DXA scans to assess the distribution of aBMD, offering a more clinically significant technique for predicting risks of bone fragility fractures.

The predictive value of trabecular bone score (TBS) on whole lumbar vertebrae mechanics: an ex vivo study

We investigated the association of trabecular bone score (TBS) with microarchitecture and mechanical behavior of human lumbar vertebrae. We found that TBS reflects vertebral trabecular microarchitecture and is an independent predictor of vertebral mechanics. However, the addition of TBS to areal BMD (aBMD) did not significantly improve prediction of vertebral strength.

INTRODUCTION

The trabecular bone score (TBS) is a gray-level measure of texture using a modified experimental variogram which can be extracted from dual-energy X-ray absorptiometry (DXA) images. The current study aimed to confirm whether TBS is associated with trabecular microarchitecture and mechanics of human lumbar vertebrae, and if its combination with BMD improves prediction of fracture risk.

METHODS

Lumbar vertebrae (L3) were harvested fresh from 16 donors. The anteroposterior and lateral bone mineral content (BMC) and areal BMD (aBMD) of the vertebral body were measured using DXA; then, the TBS was extracted using TBS iNsight software (Medimaps SA, France). The trabecular bone volume (Tb.BV/tissue volume, TV), trabecular thickness (Tb.Th), degree of anisotropy, and structure model index (SMI) were measured using microcomputed tomography. Quasi-static uniaxial compressive testing was performed on L3 vertebral bodies to assess failure load and stiffness.

RESULTS

The TBS was significantly correlated to Tb.BV/TV and SMI (r = 0.58 and -0.62; p = 0.02, 0.01), but not related to BMC and BMD. TBS was significantly correlated with stiffness (r = 0.64; p = 0.007), independently of bone mass. Using stepwise multiple regression models, we failed to demonstrate that the combination of BMD and TBS was better at explaining mechanical behavior than either variable alone. However, the combination TBS, Tb.Th, and BMC did perform better than each parameter alone, explaining 79% of the variability in stiffness.

CONCLUSIONS

In our study, TBS was associated with microarchitecture parameters and with vertebral mechanical behavior, but TBS did not improve prediction of vertebral biomechanical properties in addition to aBMD.

Computational identification and quantification of trabecular microarchitecture classes by 3-D texture analysis-based clustering

High resolution peripheral quantitative computed tomography (HR-pQCT) permits the non-invasive assessment of cortical and trabecular bone density, geometry, and microarchitecture. Although researchers have developed various post-processing algorithms to quantify HR-pQCT image properties, few of these techniques capture image features beyond global structure-based metrics. While 3D-texture analysis is a key approach in computer vision, it has been utilized only infrequently in HR-pQCT research. Motivated by high isotropic spatial resolution and the information density provided by HR-pQCT scans, we have developed and evaluated a post-processing algorithm that quantifies microarchitecture characteristics via texture features in HR-pQCT scans. During a training phase in which clustering was applied to texture features extracted from each voxel of trabecular bone, three distinct clusters, or trabecular microarchitecture classes (TMACs) were identified. These TMACs represent trabecular bone regions with common texture characteristics. The TMACs were then used to automatically segment the voxels of new data into three regions corresponding to the trained cluster features. Regional trabecular bone texture was described by the histogram of relative trabecular bone volume covered by each cluster. We evaluated the intra-scanner and inter-scanner reproducibility by assessing the precision errors (PE), intra class correlation coefficients (ICC) and Dice coefficients (DC) of the method on 14 ultradistal radius samples scanned on two HR-pQCT systems. DC showed good reproducibility in intra-scanner set-up with a mean of 0.870±0.027 (no unit). Even in the inter-scanner set-up the ICC showed high reproducibility, ranging from 0.814 to 0.964. In a preliminary clinical test application, the TMAC histograms appear to be a good indicator, when differentiating between postmenopausal women with (n=18) and without (n=18) prevalent fragility fractures. In conclusion, we could demonstrate that 3D-texture analysis and feature clustering seems to be a promising new HR-pQCT post-processing tool with good reproducibility, even between two different scanners.

Prospective assessment of bone texture parameters at the hand in rheumatoid arthritis

OBJECTIVE

Fractal bone analysis (Hmean) is a texture parameter reflecting bone microarchitecture. The BMA device (D3A™ Medical Systems, Orléans, France) is a high-resolution X-ray device that allows assessment of bone texture analysis. We aimed to measure Hmean in rheumatoid arthritis patients at the second and third metacarpal bones, at baseline and after 1 year of follow-up, and to assess the relationship of Hmean and rheumatoid arthritis disease parameters.

METHODS

Patients with rheumatoid arthritis according to ACR criteria were included. They were assessed over 1 year, in the context of a prospective study conducted in Maastricht. For this substudy, activity of the disease was assessed by erythrocyte sedimentation rate, C-reactive protein and Disease Activity Score 28 performed at each visit. Radiographic bone damage was assessed using hand and feet radiographs at baseline and on a 1-year basis. The bone texture parameters were evaluated on the second and third metacarpal heads of the left hand using BMA device.

RESULTS

One hundred and sixty-five rheumatoid arthritis patients were included in this study. At baseline, Hmean was negatively correlated with age [r=-0.22 (P=0.013)] and erythrocyte sedimentation rate [r=-0.16 (P=0.039)]. No significant correlation was found between Hmean and Disease Activity Score, disease activity Visual Analog Scale, daily corticosteroid dose and C-reactive protein. There was a significant increase in Hmean of second and third metacarpal bones over 1 year (1.6% and 1.3%, P<0.01) except in patients with local second and third metacarpal bones erosion.

CONCLUSION

The bone texture parameter Hmean is influenced by age, inflammation and local erosions in rheumatoid arthritis.

Assessment of bone fragility with clinical imaging modalities

INTRODUCTION

Osteoporotic fractures are a vital public health concern and have created a great economic burden to our society. Therefore, early diagnosis of patients with high risk of osteoporotic fractures is essential. The current gold standard for assessment of fracture risk is the measurement of bone mineral density using dual-energy X-ray absorptiometry. However, such techniques are not very effective in the diagnosis of patients with osteopaenia. Doctors are usually unable to make an informed decision regarding the treatment plan of these patients. In addition to bone mineral density, advanced imaging modalities have been explored in recent years to assess bone quality in other contributing factors, such as microarchitecture of trabecular bone, mineralisation, microdamage and bone remodelling rates. Currently, the microarchitecture of trabecular bone can be evaluated in vivo by high-resolution peripheral quantitative computed tomography techniques, which have a resolution of 80 µm. However, such imaging techniques still remain a high-end research tool rather than a diagnostic tool for clinical applications. Thus, the limited accessibility and affordability of high-resolution peripheral quantitative computed tomography have become major concerns for the general public. Alternatively, combining bone mineral density measurements with stochastic assessments of spatial bone mineral density distribution from dual-energy X-ray absorptiometry images may offer an economic and efficient approach to non-invasively evaluate skeletal integrity and identify the at-risk population for osteoporotic fractures. The aim of this critical review is to assess bone fragility with clinical imaging modalities.

CONCLUSION

High-resolution quantitative computed tomography imaging technique may provide direct measurements of microarchitectures of trabecular bone in vivo. However, it is an expensive method of imaging modality.

Bone texture analysis is correlated with three-dimensional microarchitecture and mechanical properties of trabecular bone in osteoporotic femurs

Fracture of the proximal femur is a major public health problem in elderly persons. It has recently been suggested that combining texture analysis and bone mineral density measurement improves the failure load prediction in human femurs. In this study, we aimed to compare bone texture analysis with three-dimensional (3D) microarchitecture and mechanical properties of trabecular bone in osteoporotic femurs. Eight femoral heads from osteoporotic patients who fractured their femoral neck provided 31 bone cores. Bone samples were studied using a new high-resolution digital X-ray device (BMA™, D3A Medical Systems) allowing for texture analysis with fractal parameter H (mean), and were examined using micro-computed tomography (microCT) for 3D microarchitecture. Finally, uniaxial compression tests to failure were performed to estimate failure load and apparent modulus of bone samples. The fractal parameter H (mean) was strongly correlated with bone volume fraction (BV/TV) (r = 0.84) and trabecular thickness (Tb.Th) (r = 0.91) (p < 0.01). H (mean) was also markedly correlated with failure load (r = 0.84) and apparent modulus (r = 0.71) of core samples (p < 0.01). Bone volume fraction (BV/TV) and trabecular thickness (Tb.Th) demonstrated significant correlations with failure load (r = 0.85 and 0.72, respectively) and apparent modulus (r = 0.72 and 0.64, respectively) (p < 0.01). Overall, the best predictors of failure load were H (mean), bone volume fraction, and trabecular thickness, with r (2) coefficients of 0.83, 0.76, and 0.80 respectively. This study shows that the fractal parameter H (mean) is correlated with 3D microCT parameters and mechanical properties of femoral head bone samples, which suggests that radiographic texture analysis is a suitable approach for trabecular bone microarchitecture assessment in osteoporotic femurs.

Assessment of bone mineral density and radiographic texture analysis at the tibial subchondral bone

Microstructural changes of subchondral bone constitute one of the figures characterising osteoarthritis on a structural level. Subchondral bone mineral density may reflect the complex relationship between bone and cartilage submitted to movement and loading. In this review, the authors discussed the interest of tibial subchondral bone mineral density assessment in the perspective of its diagnostic, etiopathogenic and prognostic value in osteoarthritis. In addition, the sources of variability linked to the measurement of tibial subchondral bone mineral density are precised. Trabecular bone structure characterisation by radiographic texture analyses may also represent a new promising tool to evaluate the microarchitectural changes that occur with initiation and progression of osteoarthritis. In this paper, the authors also highlighted the interest of different radiographic texture analyses and their clinical relevance in the field of osteoarthritis.

Bone texture analysis of human femurs using a new device (BMA™) improves failure load prediction

We measured bone texture parameters of excised human femurs with a new device (BMA™). We also measured bone mineral density by DXA and investigated the performance of these parameters in the prediction of failure load. Our results suggest that bone texture parameters improve failure load prediction when added to bone mineral density.

INTRODUCTION

Bone mineral density (BMD) is a strong determinant of bone strength. However, nearly half of the fractures occur in patients with BMD which does not reach the osteoporotic threshold. In order to assess fracture risk properly, other factors are important to be taken into account such as clinical risk factors as well as macro- and microarchitecture of bone. Bone microarchitecture is usually assessed by high-resolution QCT, but this cannot be applied in routine clinical settings due to irradiation, cost and availability concerns. Texture analysis of bone has shown to be correlated to bone strength.

METHODS

We used a new device to get digitized X-rays of 12 excised human femurs in order to measure bone texture parameters in three different regions of interest (ROIs). We investigated the performance of these parameters in the prediction of the failure load using biomechanical tests. Texture parameters measured were the fractal dimension (Hmean), the co-occurrence matrix, and the run length matrix. We also measured bone mineral density by DXA in the same ROIs as well as in standard DXA hip regions.

RESULTS

The Spearman correlation coefficient between BMD and texture parameters measured in the same ROIs ranged from -0.05 (nonsignificant (NS)) to 0.57 (p = 0.003). There was no correlation between Hmean and co-occurrence matrix nor Hmean and run length matrix in the same ROI (r = -0.04 to 0.52, NS). Co-occurrence matrix and run length matrix in the same ROI were highly correlated (r = 0.90 to 0.99, p < 0.0001). Univariate analysis with the failure load revealed significant correlation only with BMD results, not texture parameters. Multiple regression analysis showed that the best predictors of failure load were BMD, Hmean, and run length matrix at the femoral neck, as well as age and sex, with an adjusted r (2) = 0.88. Added to femoral neck BMD, Hmean and run length matrix at the femoral neck (without the effect of age and sex) improved failure load prediction (compared to femoral neck BMD alone) from adjusted r (2) = 0.67 to adjusted r (2) = 0.84.

CONCLUSION

Our results suggest that bone texture measurement improves failure load prediction when added to BMD.

Combination of texture analysis and bone mineral density improves the prediction of fracture load in human femurs

Twenty-one excised femurs were studied using (1) a high-resolution digital X-ray device to estimate three textural parameters, (2) dual-energy X-ray absorptiometry (DXA) to measure bone mineral density (BMD), and (3) mechanical tests to failure. Textural parameters significantly correlated with BMD (p < 0.05) and bone strength (p < 0.05). Combining texture parameters and BMD significantly improved the fracture load prediction from adjusted r(2) = 0.74 to adjusted r(2) =0.82 (p < 0.05).

INTRODUCTION

The purpose of this study is to determine if the combination of bone texture parameters using a new high-resolution X-ray device and BMD measurement by DXA provided a better prediction of femoral failure load than BMD evaluation alone.

METHODS

The proximal ends of 21 excised femurs were studied using (1) a high-resolution digital X-ray device (BMA, D3A Medical Systems) to estimate three textural parameters: fractal parameter Hmean, co-occurrence, and run-length matrices, (2) DXA to measure BMD, and (3) mechanical tests to failure in a side-impact configuration. Regions of interest in the femoral neck, intertrochanteric region, and greater trochanter were selected for DXA and bone texture analysis. Every specimen was scanned twice with repositioning before mechanical testing to assess reproducibility using intraclass correlation coefficient (ICC) with 95% confidence interval. The prediction of femoral failure load was evaluated using multiple regression analysis.

RESULTS

Thirteen femoral neck and 8 intertrochanteric fractures were observed with a mean failure load of 2,612 N (SD, 1,382 N). Fractal parameter Hmean, co-occurrence, and run-length matrices each significantly correlated with site-matched BMD (p < 0.05) and bone strength (p < 0.05). The ICC of the textural parameters varied between 0.65 and 0.90. Combining bone texture parameters and BMD significantly improved the fracture load prediction from adjusted r(2) =0.74 to adjusted r(2) = 0.82 (p < 0.05).

CONCLUSION

In these excised femurs, the combination of bone texture parameters with BMD demonstrated a better performance in the failure load prediction than that of BMD alone.

Assessment of bone microarchitecture in chronic kidney disease: a comparison of 2D bone texture analysis and high-resolution peripheral quantitative computed tomography at the radius and tibia

Bone microarchitecture can be studied noninvasively using high-resolution peripheral quantitative computed tomography (HR-pQCT). However, this technique is not widely available, so more simple techniques may be useful. BMA is a new 2D high-resolution digital X-ray device, allowing for bone texture analysis with a fractal parameter (H(mean)). The aims of this study were (1) to evaluate the reproducibility of BMA at two novel sites (radius and tibia) in addition to the conventional site (calcaneus), (2) to compare the results obtained with BMA at all of those sites, and (3) to study the relationship between H(mean) and trabecular microarchitecture measured with an in vivo 3D device (HR-pQCT) at the distal tibia and radius. BMA measurements were performed at three sites (calcaneus, distal tibia, and radius) in 14 healthy volunteers to measure the short-term reproducibility and in a group of 77 patients with chronic kidney disease to compare BMA results to HR-pQCT results. The coefficient of variation of H(mean) was 1.2, 2.1, and 4.7% at the calcaneus, radius, and tibia, respectively. We found significant associations between trabecular volumetric bone mineral density and microarchitectural variables measured by HR-pQCT and H(mean) at the three sites (e.g., Pearson correlation between radial trabecular number and radial H(mean) r = 0.472, P < 0.001). This study demonstrated a significant but moderate relationship between 2D bone texture and 3D trabecular microarchitecture. BMA is a new reproducible technique with few technical constraints. Thus, it may represent an interesting tool for evaluating bone structure, in association with biological parameters and DXA.