Prediction of femoral fracture load: cross-sectional study of texture analysis and geometric measurements on plain radiographs versus bone mineral density

Using Texture Analysis of Neck Computed Tomography Images to Differentiate Primary Hyperparathyroidism From Normal Controls

OBJECTIVE

To investigate the utility of texture analysis in detecting osseous changes associated with hyperparathyroidism on neck CT examinations compared with control patients and to explore the best regions in the head and neck to evaluate changes in the trabecular architecture secondary to hyperparathyroidism.

METHODS

Patients with hyperparathyroidism who underwent a 4D CT of the neck with contrast were included in this study. Age-matched control patients with no history of hyperparathyroidism who underwent a contrast-enhanced neck CT were also included. Mandibular condyles, bilateral mandibular bodies, the body of the C4 vertebra, the manubrium of the sternum, and bilateral clavicular heads were selected for analysis, and oval-shaped regions of interest were manually placed. These segmented areas were imported into an in-house developed texture analysis program, and 41 texture analysis features were extracted. A mixed linear regression model was used to compare differences in the texture analysis features contoured at each of the osseous structures between patients with hyperparathyroidism and age-matched control patients.

RESULTS

A total of 30 patients with hyperparathyroidism and 30 age-matched control patients were included in this study. Statistically significant differences in texture features between patients with hyperparathyroidism and control patients in all 8 investigated osseous regions. The sternum showed the greatest number of texture features with statistically significant differences between these groups.

CONCLUSIONS

Some CT texture features demonstrated statistically significant differences between patients with hyperparathyroidism and control patients. The results suggest that texture features may discriminate changes in the osseous architecture of the head and neck in patients with hyperparathyroidism.

Reconstruction of massive bone defects after femoral tumor resection using two new-designed 3D-printed intercalary prostheses: a clinical analytic study with the cooperative utilization of multiple technologies

BACKGROUND

To reconstruct massive bone defects of the femoral diaphysis and proximal end with limited bilateral cortical bone after joint-preserving musculoskeletal tumor resections, two novel 3D-printed customized intercalary femoral prostheses were applied.

METHODS

A series of nine patients with malignancies who received these novel 3D-printed prostheses were retrospectively studied between July 2018 and November 2021. The proximal and diaphyseal femur was divided into three regions of interest (ROIs) according to anatomic landmarks, and anatomic measurements were conducted on 50 computed tomography images showing normal femurs. Based on the individual implant-involved ROIs, osteotomy level, and anatomical and biomechanical features, two alternative 3D-printed prostheses were designed. In each patient, Hounsfield Unit (HU) value thresholding and finite element analysis were conducted to identify the bone trabecula and calcar femorale and to determine the stress distribution, respectively. We described the characteristics of each prosthesis and surgical procedure and recorded the intraoperative data. All patients underwent regular postoperative follow-up, in which the clinical, functional and radiographical outcomes were evaluated.

RESULTS

With the ROI division and radiographic measurements, insufficient bilateral cortical bones for anchoring the traditional stem were verified in the normal proximal femur. Therefore, two 3D-printed intercalary endoprostheses, a Type A prosthesis with a proximal curved stem and a Type B prosthesis with a proximal anchorage-slot and corresponding locking screws, were designed. Based on HU value thresholding and finite element analysis, the 3D-printed proximal stems in all prostheses maximally preserved the trabecular bone and calcar femorale and optimized the biomechanical distribution, as did the proximal screws. With the 3D-printed osteotomy guide plates and reaming guide plates, all patients underwent the operation uneventfully with a satisfactory duration (325.00 ± 62.60 min) and bleeding volume (922.22 ± 222.36 ml). In the follow-up, Harris Hip and Musculoskeletal Tumor Society scores were ameliorated after surgery (P < 0.001 and P < 0.001, respectively), reliable bone ingrowth was observed, and no major complications occurred.

CONCLUSIONS

Two novel 3D-printed femoral intercalary prostheses, which achieved acceptable overall postoperative outcomes, were used as appropriate alternatives for oncologic patients with massive bone defects and limited residual bone and increased the opportunities for joint-preserving tumor resection. Several scientific methodologies utilized in this study may promote the clinical design proposals of 3D-printed implants.

Texture Parameters Measured by UHF-MRI and CT Scan Provide Information on Bone Quality in Addition to BMD: A Biomechanical Ex Vivo Study

The current definition of osteoporosis includes alteration of bone quality. The assessment of bone quality is improved by the development of new texture analysis softwares. Our objectives were to assess if proximal femoral trabecular bone texture measured in Ultra high field (UHF) 7 Tesla MRI and CT scan were related to biomechanical parameters, and if the combination of texture parameters and areal bone mineral density (aBMD) measured by dual-energy X-ray absorptiometry provided a better prediction of femoral failure than aBMD alone. The aBMD of 16 proximal femur ends from eight cadavers were investigated. Nineteen textural parameters were computed in three regions or volumes of interest for each specimen on UHF MRI and CT scan. Then, the corresponding failure load and failure stress were calculated thanks to mechanical compression test. aBMD was not correlated to failure load (R² = 0.206) and stress (R² = 0.153). The failure load was significantly correlated with ten parameters in the greater trochanter using UHF MRI, and with one parameter in the neck and the greater trochanter using CT scan. Eight parameters in the greater trochanter using UHF MRI combined with aBMD improved the failure load prediction, and seven parameters improved the failure stress prediction. Our results suggest that textural parameters provide additional information on the fracture risk of the proximal femur when aBMD is not contributive.

Adaptive Contrast for Image Regression in Computer-Aided Disease Assessment

Image regression tasks for medical applications, such as bone mineral density (BMD) estimation and left-ventricular ejection fraction (LVEF) prediction, play an important role in computer-aided disease assessment. Most deep regression methods train the neural network with a single regression loss function like MSE or L1 loss. In this paper, we propose the first contrastive learning framework for deep image regression, namely AdaCon, which consists of a feature learning branch via a novel adaptive-margin contrastive loss and a regression prediction branch. Our method incorporates label distance relationships as part of the learned feature representations, which allows for better performance in downstream regression tasks. Moreover, it can be used as a plug-and-play module to improve performance of existing regression methods. We demonstrate the effectiveness of AdaCon on two medical image regression tasks, i.e., bone mineral density estimation from X-ray images and left-ventricular ejection fraction prediction from echocardiogram videos. AdaCon leads to relative improvements of 3.3% and 5.9% in MAE over state-of-the-art BMD estimation and LVEF prediction methods, respectively.

Preoperative measures of bone mineral density from digital wrist radiographs

Aims

Assessment of bone mineral density (BMD) with dual-energy X-ray absorptiometry (DXA) is a well-established clinical technique, but it is not available in the acute trauma setting. Thus, it cannot provide a preoperative estimation of BMD to help guide the technique of fracture fixation. Alternative methods that have been suggested for assessing BMD include: 1) cortical measures, such as cortical ratios and combined cortical scores; and 2) aluminium grading systems from preoperative digital radiographs. However, limited research has been performed in this area to validate the different methods. The aim of this study was to investigate the evaluation of BMD from digital radiographs by comparing various methods against DXA scanning.

Methods

A total of 54 patients with distal radial fractures were included in the study. Each underwent posteroanterior (PA) and lateral radiographs of the injured wrist with an aluminium step wedge. Overall 27 patients underwent routine DXA scanning of the hip and lumbar spine, with 13 undergoing additional DXA scanning of the uninjured forearm. Analysis of radiographs was performed on ImageJ and Matlab with calculations of cortical measures, cortical indices, combined cortical scores, and aluminium equivalent grading.

Results

Cortical measures showed varying correlations with the forearm DXA results (range: Pearson correlation coefficient (r) = 0.343 (p = 0.251) to r = 0.521 (p = 0.068)), with none showing statistically significant correlations. Aluminium equivalent grading showed statistically significant correlations with the forearm DXA of the corresponding region of interest (p < 0.017).

Conclusion

Cortical measures, cortical indices, and combined cortical scores did not show a statistically significant correlation to forearm DXA measures. Aluminium-equivalent is an easily applicable method for estimation of BMD from digital radiographs in the preoperative setting.

Cite this article: Bone Joint Res 2021;10(12):830–839.

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.

Next-generation imaging of the skeletal system and its blood supply

Bone is organized in a hierarchical 3D architecture. Traditionally, analysis of the skeletal system was based on bone mass assessment by radiographic methods or on the examination of bone structure by 2D histological sections. Advanced imaging technologies and big data analysis now enable the unprecedented examination of bone and provide new insights into its 3D macrostructure and microstructure. These technologies comprise ex vivo and in vivo methods including high-resolution computed tomography (CT), synchrotron-based imaging, X-ray microscopy, ultra-high-field magnetic resonance imaging (MRI), light-sheet fluorescence microscopy, confocal and intravital two-photon imaging. In concert, these techniques have been used to detect and quantify a novel vascular system of trans-cortical vessels in bone. Furthermore, structures such as the lacunar network, which harbours and connects osteocytes, become accessible for 3D imaging and quantification using these methods. Next-generation imaging of the skeletal system and its blood supply are anticipated to contribute to an entirely new understanding of bone tissue composition and function, from macroscale to nanoscale, in health and disease. These insights could provide the basis for early detection and precision-type intervention of bone disorders in the future.

Texture analysis of intermediate-advanced hepatocellular carcinoma: prognosis and patients' selection of transcatheter arterial chemoembolization and sorafenib

Transcatheter arterial chemoembolization (TACE) and sorafenib combination treatment for unselected hepatocellular carcinoma (HCC) is controversial. We explored the potential of texture analysis for appropriate patient selection. There were 261 HCCs included (TACE group: n = 197; TACE plus sorafenib (TACE+Sorafenib) group n = 64). We applied a Gabor filter and wavelet transform with 3 band-width responses (filter 0, 1.0, and 1.5) to portal-phase computed tomography (CT) images of the TACE group. Twenty-one textural parameters per filter were extracted from the region of interests delineated around tumor outline. After testing survival correlations, the TACE group was subdivided according to parameter thresholds in receiver operating characteristic curves and compared to TACE+Sorafenib group survival. The Gabor-1-90 (filter 0) was most significantly correlated with TTP. The TACE group was accordingly divided into the TACE-1 (Gabor-1-90 ≤ 3.6190) and TACE-2 (Gabor-1-90 > 3.6190) subgroups; TTP was similar in the TACE-1 subgroup and TACE+Sorafenib group, but shorter in the TACE-2 subgroup. Only wavelet-3-D (filter 1.0) correlated with overall survival (OS), and was used for subgrouping. The TACE-5 (wavelet-3-D ≤ 12.2620) subgroup and the TACE+Sorafenib group showed similar OS, while the TACE-6 (wavelet-3-D > 12.2620) subgroup had shorter OS. Gabor-1-90 and wavelet-3-D were consistent.Independent of tumor number or size, CT textural parameters are correlated with TTP and OS. Patients with lower Gabor-1-90 (filter 0) and wavelet-3-D (filter 1.0) should be treated with TACE and sorafenib. Texture analysis holds promise for appropriate selection of HCCs for this combination therapy.

Prediction of Hip Failure Load: In Vitro Study of 80 Femurs Using Three Imaging Methods and Finite Element Models-The European Fracture Study (EFFECT)

Purpose To evaluate the performance of three imaging methods (radiography, dual-energy x-ray absorptiometry [DXA], and quantitative computed tomography [CT]) and that of a numerical analysis with finite element modeling (FEM) in the prediction of failure load of the proximal femur and to identify the best densitometric or geometric predictors of hip failure load. Materials and Methods Institutional review board approval was obtained. A total of 40 pairs of excised cadaver femurs (mean patient age at time of death, 82 years ± 12 [standard deviation]) were examined with (a) radiography to measure geometric parameters (lengths, angles, and cortical thicknesses), (b) DXA (reference standard) to determine areal bone mineral densities (BMDs), and (c) quantitative CT with dedicated three-dimensional analysis software to determine volumetric BMDs and geometric parameters (neck axis length, cortical thicknesses, volumes, and moments of inertia), and (d) quantitative CT-based FEM to calculate a numerical value of failure load. The 80 femurs were fractured via mechanical testing, with random assignment of one femur from each pair to the single-limb stance configuration (hereafter, stance configuration) and assignment of the paired femur to the sideways fall configuration (hereafter, side configuration). Descriptive statistics, univariate correlations, and stepwise regression models were obtained for each imaging method and for FEM to enable us to predict failure load in both configurations. Results Statistics reported are for stance and side configurations, respectively. For radiography, the strongest correlation with mechanical failure load was obtained by using a geometric parameter combined with a cortical thickness (r(2) = 0.66, P < .001; r(2) = 0.65, P < .001). For DXA, the strongest correlation with mechanical failure load was obtained by using total BMD (r(2) = 0.73, P < .001) and trochanteric BMD (r(2) = 0.80, P < .001). For quantitative CT, in both configurations, the best model combined volumetric BMD and a moment of inertia (r(2) = 0.78, P < .001; r(2) = 0.85, P < .001). FEM explained 87% (P < .001) and 83% (P < .001) of bone strength, respectively. By combining (a) radiography and DXA and (b) quantitative CT and DXA, correlations with mechanical failure load increased to 0.82 (P < .001) and 0.84 (P < .001), respectively, for radiography and DXA and to 0.80 (P < .001) and 0.86 (P < .001) , respectively, for quantitative CT and DXA. Conclusion Quantitative CT-based FEM was the best method with which to predict the experimental failure load; however, combining quantitative CT and DXA yielded a performance as good as that attained with FEM. The quantitative CT DXA combination may be easier to use in fracture prediction, provided standardized software is developed. These findings also highlight the major influence on femoral failure load, particularly in the trochanteric region, of a densitometric parameter combined with a geometric parameter. (©) RSNA, 2016 Online supplemental material is available for this article.

Skeletal deterioration following ovarian failure: can some features be a direct consequence of estrogen loss while others are more related to physical inactivity?

Findings on experimental animals show that ovarian failure is accompanied by a decrease in motor activity. As mechanical loading has a vital role in the maintenance of skeletal health, our aim was to determine to what extent this decrease in motor activity contributes to ovariectomy-induced bone loss. Thirty-two female Wistar rats were ovariectomized or sham-operated and housed in standard cages or with access to running wheels for 36 weeks with their running distance monitored. Markers of bone turnover were assayed in the serum, and bone geometry, trabecular and cortical bone microarchitecture, mineralization degree, and biomechanical properties were assessed in the femur. Differences between groups were determined by one-way ANOVA. Although reduced motor activity and sex steroid deficiency both resulted in decreases in trabecular bone volume, trabecular number decreases were mostly associated with sex steroid deficiency, whereas trabecular thickness decreases were mostly associated with sedentary behavior. Cortical bone appeared to be more sensitive to variations in motor activity, whereas bone turnover rate and bone tissue mineralization degree seemed to be primarily affected by sex steroid deficiency, even though they were further aggravated by sedentary behavior. Increases in femur length were mostly a consequence of sex steroid deficiency, whereas femoral neck length was also influenced by sedentary behavior. Differences in mechanical properties resulted mostly from differences in physical activity. Both the direct effect of sex steroid deficiency and the indirect effect of motor activity changes are implicated in bone loss following ovariectomy.

Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry

Background and Purpose. To evaluate the added value of MRI with respect to peripheral quantitative computed tomography (pQCT) and dual energy X-ray absorptiometry (DXA) for predicting femoral strength. Material and Methods. Bone mineral density (BMD) of eighteen femur specimens was assessed with pQCT, DXA, and MRI (using ultrashort echo times (UTE) and the MicroView software). Subsequently biomechanical testing was performed to assess failure load. Simple and multiple linear regression were used with failure load as the dependent variable. Results. Simple linear regression allowed a prediction of failure load with either pQCT, DXA, or MRI in an r² range of 0.41–0.48. Multiple linear regression with pQCT, DXA, and MRI yielded the best prediction (r² = 0.68). Conclusions. The accuracy of MRI, using UTE and MicroView software, to predict femoral strength compares well with that of pQCT or DXA. Furthermore, the inclusion of MRI in a multiple-regression model yields the best prediction.

Reusing cadaveric humeri for fracture testing after testing simulated rotator cuff tendon repairs

The financial cost of using human tissues in biomedical testing and surgical reconstruction is predicted to increase at a rate that is disproportionately greater than other materials used in biomechanical testing. Our first hypothesis is that cadaveric proximal humeri that had undergone monotonic failure testing of simulated rotator cuff repairs would not differ in ultimate fracture loads or in energy absorbed to fracture when compared to controls (i.e., bones without cuff repairs). Our second hypothesis is that there can be substantial cost savings if these cadaveric proximal humeri, with simulated cuff repairs, can be re-used for fracture testing. Results of fracture tests (conducted in a backwards fall configuration) and cost analysis support both hypotheses. Hence, the bones that had undergone monotonic failure tests of various rotator cuff repair techniques can be re-used in fracture tests because their load-carrying capacity is not significantly reduced.

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.

Image texture in dental panoramic radiographs as a potential biomarker of osteoporosis

Previous studies have shown an association between osteoporosis and automatic measurements of mandibular cortical width on dental panoramic radiographs (DPRs). In this study, we show that additional image texture features increase this association and propose the combined features as a potential biomarker for osteoporosis. We used an existing dataset of 663 DPRs of female patients with bone mineral density (BMD) measurements. The mandibular cortex was located using a previously described computer algorithm. Texture features, based on co-occurrence matrices and fractal dimension, were measured in the bone within the cortex and also in the superior basal bone above the cortex. These, augmented by cortical width measurements, were used by a random forest classifier to identify osteoporosis at femoral neck, total hip, and lumbar spine. Classification performance was assessed by ROC analysis. Area-under-curve (AUC) values for identifying osteoporosis at femoral neck were 0.830, 0.824, and 0.872 using, respectively, cortical width alone, cortical texture (co-occurrence matrix features) alone, and combined width and texture. At 80% sensitivity, these classifiers produced specificity values of 74.4%, 73.6%, and 80.0%, respectively. Fractal dimension was a less effective texture feature. Prediction of osteoporosis at the lumbar spine was poorer, but a combined width and superior basal bone texture classifier gave a significant improvement in AUC at over the use of width alone.

Advances in bone imaging for osteoporosis

The diagnosis and management of osteoporosis have been improved by the development of new quantitative methods of skeletal assessment and by the availability of an increasing number of therapeutic options, respectively. A number of imaging methods exist and all have advantages and disadvantages. Dual-energy X-ray absorptiometry (DXA) is the most widely available and commonly utilized method for clinical diagnosis of osteoporosis and will remain so for the foreseeable future. The WHO 10-year fracture risk assessment tool (FRAX(®)) will improve clinical use of DXA and the cost-effectiveness of therapeutic intervention. Improved reporting of radiographic features that suggest osteoporosis and the presence of vertebral fracture, which are powerful predictors of future fractures, could increase the frequency of appropriate DXA referrals. Quantitative CT remains predominantly a research tool, but has advantages over DXA--allowing measurement of volumetric density, separate measures of cortical and trabecular bone density, and evaluation of bone shape and size. High resolution imaging, using both CT and MRI, has been introduced to measure trabecular and cortical bone microstructure. Although these methods provide detailed insights into the effects of disease and therapies on bone, they are technically challenging and not widely available, so they are unlikely to be used in clinical practice.

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.

The interindividual variation in femoral neck width is associated with the acquisition of predictable sets of morphological and tissue-quality traits and differential bone loss patterns

A better understanding of femoral neck structure and age-related bone loss will benefit research aimed at reducing fracture risk. We used the natural variation in robustness (bone width relative to length) to analyze how adaptive processes covary traits in association with robustness, and whether the variation in robustness affects age-related bone loss patterns. Femoral necks from 49 female cadavers (29-93 years of age) were evaluated for morphological and tissue-level traits using radiography, peripheral quantitative computed tomography, micro-computed tomography, and ash-content analysis. Femoral neck robustness was normally distributed and varied widely with a coefficient of variation of 14.9%. Age-adjusted partial regression analysis revealed significant negative correlations (p < 0.05) between robustness and relative cortical area, cortical tissue-mineral density (Ct.TMD), and trabecular bone mineral density (Ma.BMD). Path analysis confirmed these results showing that a one standard deviation (SD) increase in robustness was associated with a 0.70 SD decrease in RCA, 0.47 SD decrease in Ct.TMD, and 0.43 SD decrease in Ma.BMD. Significantly different bone loss patterns were observed when comparing the most slender and most robust tertiles. Robust femora showed significant negative correlations with age for cortical area (R(2) = 0.29, p < 0.03), Ma.BMD (R(2) = 0.34, p < 0.01), and Ct.TMD (R(2) = 0.4, p < 0.003). However, slender femora did not show these age-related changes (R(2) < 0.09, p > 0.2). The results indicated that slender femora were constructed with a different set of traits compared to robust femora, and that the natural variation in robustness was a determinant of age-related bone loss patterns. Clinical diagnoses and treatments may benefit from a better understanding of these robustness-specific structural and aging patterns.

Recursive hierarchic segmentation analysis of bone mineral density changes on digital panoramic images

OBJECTIVE

The aim of this study was to demonstrate that histogram analysis and mathematical modeling of digital panoramic images (DPIs) processed using recursive hierarchic segmentation (RHSEG) discriminates normal, osteopenic, and osteoporotic cancellous bone.

STUDY DESIGN

Forty-seven DPIs of postmenopausal women were grouped into normal, osteopenic, and osteoporotic; dual-energy x-ray absorptiometry was the reference standard. RHSEG of the mandibular angle and canine/premolar trabecular regions of interest was performed. After histogram and histogram bin analysis and generation of relative intensity functions, generalized linear mixed model analysis was used to model the data and likelihood ratio testing used to assess group differences.

RESULTS

Histogram analyses discriminated among the groups. Receiver operating characteristic analysis of the canine/premolar data yielded area-under-the-curve accuracies of 0.78 for osteoporosis and 0.74 for osteopenia. Discrimination of osteoporosis required cubic analysis, discrimination of osteopenia required quartic analysis, and neither model alone discriminated among all groups.

CONCLUSIONS

Analyses and mathematical modeling of mandibular trabecular bone on RHSEG-processed DPIs discriminated normal, osteoporotic, and osteopenic patients.

Changes in proximal femur bone properties following ovariectomy and their association with resistance to fracture

Bone strength depends on several material and structural properties, but findings concerning the best predictors of bone mechanical performance are conflicting. The aim of this study was to investigate how a broad set of bone properties in the proximal femur are influenced by age and hormonal status, and how these properties together determine bone strength. Twenty-five Wistar rats were ovariectomized (OVX, n = 13) or sham operated (SHAM, n = 12) at 5 months of age, and killed after 9 months. Another group of rats was killed at 5 months as baseline control (BSL, n = 7). At sacrifice, serum 17β-estradiol and bone turnover marker concentrations were determined in the serum. Both femurs were collected for assessment of trabecular microarchitecture, femoral neck geometry, radiographic absorptiometry, calcium and phosphate content, and biomechanical properties. While stiffness was mostly associated with proximal femur trabecular microarchitecture and mineralization degree, bone strength was mostly linked to bone size and femoral neck geometry, which predicted almost 50% of its variance. Despite the decrease in cortical and trabecular bone as well as in mineralization degree following estrogen loss, bone strength was not reduced in OVX animals compared to BSL or sham-operated rats. This was due to a change in femoral neck geometry as well as to an increase in femur size in OVX, which apparently compensated their lower bone volume and mineral content, thereby preserving bone strength. Estrogen loss leads to a deterioration of bone tissue quality, but bone strength was preserved at the expense of geometric adaptations.

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.

MRI texture analysis of femoral neck: Detection of exercise load-associated differences in trabecular bone

PURPOSE

To assess the ability of co-occurrence matrix-based texture parameters to detect exercise load-associated differences in MRI texture at the femoral neck cross-section.

MATERIALS AND METHODS

A total of 91 top-level female athletes representing five differently loading sports and 20 referents participated in this cross-sectional study. Axial T1-weighted FLASH and T2*-weighted MEDIC sequence images of the proximal femur were obtained with a 1.5T MRI. The femoral neck trabecular bone at the level of the insertion of articular capsule was divided manually into regions of interest representing four anatomical sectors (anterior, posterior, superior, and inferior). Selected co-occurrence matrix-based texture parameters were used to evaluate differences in apparent trabecular structure between the exercise loading groups and anatomical sectors of the femoral neck.

RESULTS

Significant differences in the trabecular bone texture, particularly at the superior femoral neck, were observed between athletes representing odd-impact (soccer and squash) and high-magnitude exercise loading (power-lifting) groups and the nonathletic reference group.

CONCLUSION

MRI texture analysis provides a quantitative method for detecting and classifying apparent structural differences in trabecular bone that are associated with specific exercise loading.

Combination of radiograph-based trabecular and geometrical parameters can discriminate cervical hip fractures from controls in individuals with BMD in non-osteoporotic range

Majority of hip fractures occur in individuals with bone mineral density (BMD) in non-osteoporotic range. This suggests that factors other than BMD are associated with increased fracture risk in these individuals. The aim of this study was to investigate the combined ability of radiograph-based trabecular and geometrical parameters to discriminate cervical hip fractures from controls in individuals with non-osteoporotic BMD. A total of 39 postmenopausal females with non-pathologic cervical hip fracture were recruited to the study. Nineteen of the fracture patients (48.7%) had non-osteoporotic BMD and they constituted the fracture group. The control group consisted of 35 BMD-matched non-osteoporotic females. Several geometrical and trabecular parameters were extracted from plain pelvic radiographs, and their combined ability to discriminate fracture patients from controls was studied using a receiver operating characteristics (ROC) analysis. Significant differences in several radiograph-based geometrical and trabecular parameters were found between the fracture patients and controls, whereas no statistically significant difference in BMD was observed (p=0.92) between the groups. Area under the ROC curve was 0.993 (95% CI 0.977-1.008) for the combined multiple regression model, which included both trabecular and geometrical parameters as explanatory factors. Here, the sensitivity of 100% was achieved with the specificity of 94%. In a cross-validation of the model, 94.4% of the fracture patients, and 94.1% of the controls were classified correctly. The combination of radiograph-based trabecular and geometrical parameters was able to discriminate the cervical hip fracture cases from controls with similar BMD, showing that the method can provide additional information on bone structure and fracture risk beyond BMD.

Comparison of radiograph-based texture analysis and bone mineral density with three-dimensional microarchitecture of trabecular bone

PURPOSE

Hip fracture is a serious health problem and textural methods are being developed to assess bone quality. The authors aimed to perform textural analysis at femur on high-resolution digital radiographs compared to three-dimensional (3D) microarchitecture comparatively to bone mineral density.

METHODS

Sixteen cadaveric femurs were imaged with an x-ray device using a C-MOS sensor. One 17 mm square region of interest (ROI) was selected in the femoral head (FH) and one in the great trochanter (GT). Two-dimensional (2D) textural features from the co-occurrence matrices were extracted. Site-matched measurements of bone mineral density were performed. Inside each ROI, a 16 mm diameter core was extracted. Apparent density (Dapp) and bone volume proportion (BV/TV(Arch)) were measured from a defatted bone core using Archimedes' principle. Microcomputed tomography images of the entire length of the core were obtained (Skyscan 1072) at 19.8 microm of resolution and usual 3D morphometric parameters were computed on the binary volume after calibration from BV/TV(Arch). Then, bone surface/bone volume, trabecular thickness, trabecular separation, and trabecular number were obtained by direct methods without model assumption and the structure model index was calculated.

RESULTS

In univariate analysis, the correlation coefficients between 2D textural features and 3D morphological parameters reached 0.83 at the FH and 0.79 at the GT. In multivariate canonical correlation analysis, coefficients of the first component reached 0.95 at the FH and 0.88 at the GT.

CONCLUSIONS

Digital radiographs, widely available and economically viable, are an alternative method for evaluating bone microarchitectural structure.