Statistical shape and appearance models for fast and automated estimation of proximal femur fracture load using 2D finite element models

Estimating the risk of osteoporotic fractures is an important diagnostic step that needs to be taken before medicinal treatment. Densitometry-based criteria are normally used in clinical practice for this purpose. However, densitometry-based techniques could not explain all low-energy fractures. As patient-specific finite element (FE) models allow for consideration of other parameters (e.g. load conditions) that are known to be associated with fracture, they are considered promising candidates for more accurate fracture risk estimation. Nevertheless, they are often time consuming, expensive, and complex to build and may need the type of expertise that is not normally available in clinical settings. In this study, we report the development of an automated platform for estimating proximal femur fracture loads using patient-specific 2D FE models generated using dual-energy x-ray absorptiometry (DXA) scans. First, a statistical shape and appearance model (SSAM) is built using DXA scans of patients screened for osteoporosis following a low energy fracture. SSAM is then used together with Active Appearance Models (AAM) for automated segmentation of the proximal femur from new unseen DXA scans. The mean point-to-curve error of the automated procedure, i.e. 1.2–1.4 mm, is shown to be only slightly larger than the intra-observer variability of manual segmentation, i.e. 1.0 mm. Moreover, the developed platform automatically meshes the segmented shape, assigns density-based mechanical properties, assigns loads and boundary conditions, submits the 2D FE model for solution, and performs post-processing of the 2D FE simulation data to determine fracture loads. The fracture loads predicted using the manually generated and automatically generated 2D FE models are shown to be very close with a mean difference of around 8.8%. Repeated measures ANOVA showed no significant differences between the fracture loads calculated using FE models manually generated by three independent observers and those calculated using the automatically generated FE models (p>0.05).     

Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments

Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.     

Accounting for spatial variation of trabecular anisotropy with subject-specific finite element modeling moderately improves predictions of local subchondral bone stiffness at the proximal tibia

IntroductionPreviously, a finite element (FE) model of the proximal tibia was developed and validated against experimentally measured local subchondral stiffness. This model indicated modest predictions of stiffness (R² = 0.77, normalized root mean squared error (RMSE%) = 16.6%). Trabecular bone though was modeled with isotropic material properties despite its orthotropic anisotropy. The objective of this study was to identify the anisotropic FE modeling approach which best predicted (with largest explained variance and least amount of error) local subchondral bone stiffness at the proximal tibia.MethodsLocal stiffness was measured at the subchondral surface of 13 medial/lateral tibial compartments using in situ macro indentation testing. An FE model of each specimen was generated assuming uniform anisotropy with 14 different combinations of cortical- and tibial-specific density-modulus relationships taken from the literature. Two FE models of each specimen were also generated which accounted for the spatial variation of trabecular bone anisotropy directly from clinical CT images using grey-level structure tensor and Cowin’s fabric-elasticity equations. Stiffness was calculated using FE and compared to measured stiffness in terms of R² and RMSE%.ResultsThe uniform anisotropic FE model explained 53–74% of the measured stiffness variance, with RMSE% ranging from 12.4 to 245.3%. The models which accounted for spatial variation of trabecular bone anisotropy predicted 76–79% of the variance in stiffness with RMSE% being 11.2–11.5%.ConclusionsOf the 16 evaluated finite element models in this study, the combination of Synder and Schneider (for cortical bone) and Cowin’s fabric-elasticity equations (for trabecular bone) best predicted local subchondral bone stiffness.     

Distal skeletal tibia assessed by HR-pQCT is highly correlated with femoral and lumbar vertebra failure loads

Dual energy X-ray absorptiometry (DXA) is the standard for assessing fragility fracture risk using areal bone mineral density (aBMD), but only explains 60–70% of the variation in bone strength. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides 3D-measures of bone microarchitecture and volumetric bone mineral density (vBMD), but only at the wrist and ankle. Finite element (FE) models can estimate bone strength with 86–95% precision. The purpose of this study is to determine how well vBMD and FE bone strength at the wrist and ankle relate to fracture strength at the hip and spine, and to compare these relationships with DXA measured directly at those axial sites. Cadaveric samples (radius, tibia, femur and L4 vertebra) were compared within the same body. The radius and tibia specimens were assessed using HR-pQCT to determine vBMD and FE failure load. aBMD from DXA was measured at the femur and L4 vertebra. The femur and L4 vertebra specimens were biomechanically tested to determine failure load. aBMD measures of the axial skeletal sites strongly correlated with the biomechanical strength for the L4 vertebra (r = 0.77) and proximal femur (r = 0.89). The radius correlated significantly with biomechanical strength of the L4 vertebra for vBMD (r = 0.85) and FE-derived strength (r = 0.72), but not with femur strength. vBMD at the tibia correlated significantly with femoral biomechanical strength (r = 0.74) and FE-estimated strength (r = 0.83), and vertebral biomechanical strength for vBMD (r = 0.97) and FE-estimated strength (r = 0.91). The higher correlations at the tibia compared to radius are likely due to the tibia’s weight-bearing function.     

Development of a surrogate model based on patient weight,bone mass and geometry to predict femoral neck strains and fracture loads

Osteoporosis and related bone fractures are an increasing global burden in our ageing society. Areal bone mineral density assessed through dual energy X-ray absorptiometry (DEXA), the clinically accepted and most used method, is not sufficient to assess fracture risk individually. Finite element (FE) modelling has shown improvements in prediction of fracture risk, better than aBMD from DEXA, but is not practical for widespread clinical use. The aim of this study was to develop an adaptive neural network (ANN)-based surrogate model to predict femoral neck strains and fracture loads obtained from a previously developed population-based FE model. The surrogate model performance was assessed in simulating two loading conditions: the stance phase of gait and a fall.The surrogate model successfully predicted strains estimated by FE (r² = 0.90–0.98 for level gait load case, r² = 0.92–0.96 for the fall load case). Moreover, an ANN model based on three measurements obtainable in clinics (femoral neck length (level gait) or maximum femoral neck diameter (fall), femoral neck bone mass, body weight) was able to give reasonable predictions (r² = 0.84–0.94) for all of the strain metrics and the estimated femoral neck fracture load. Overall, the surrogate model has potential for clinical applications as they are based on simple measures of geometry and bone mass which can be derived from DEXA images, accurately predicting FE model outcomes, with advantages over FE models as they are quicker and easier to perform.     

Does a micro-grooved trunnion stem surface finish improve fixation and reduce fretting wear at the taper junction of total hip replacements? A finite element evaluation

The generation of particulate debris at the taper junction of total hip replacements (THRs), can cause failure of the artificial hip. The taper surfaces of femoral heads and trunnions of femoral stems are generally machined to a certain roughness to enhance fixation. However, the effect of the surface roughness of these surfaces on the fixation, wear and consequently clinical outcomes of the design is largely unknown. In this study, we asked whether a micro-grooved trunnion surface finish (1) improves the fixation and (2) reduces the wear rate at the taper junction of THRs. We used 3D finite element (FE) models of THRs to, firstly, investigate the effect of initial fixation of a Cobalt-Chromium femoral head with a smooth taper surface mated with a Titanium (1) micro-grooved and (2) smooth, trunnion surface finishes. Secondly, we used a computational FE wear model to compare the wear evolution between the models, which was then validated against wear measurements of the taper surface of explanted femoral heads. The fixation at the taper junction was found to be better for the smooth couplings. Over a 7 million load cycle analysis in-silico, the linear wear depth and the total material loss was around 3.2 and 1.4 times higher for the femoral heads mated with micro-grooved trunnions. It was therefore concluded that smooth taper and trunnion surfaces will provide better fixation at the taper junction and reduce the volumetric wear rates.     

Predicting the permeability of trabecular bone by micro-computed tomography and finite element modeling

The intrinsic permeability of bone plays an important role in the transport of nutrients and minerals within the tissue, and affects the mechanical stimuli that are related to the fate of the stem cells. The objective of this study was to establish a method to assess trabecular bone permeability using experimental and finite element (FE) modeling approaches based on micro computed tomography (µCT) images. Human cadaveric tibia cube specimens (N=23) were scanned with µCT. The permeability was measured experimentally using a custom-developed constant-head permeameter, and computationally by a poroelastic formulation to simulate the fluid flow within the discretized bone matrix and pore phase. The average of the experimentally measured permeability was 4.84×10⁻¹⁰ m² with a standard deviation of 3.70×10⁻¹⁰ m². A regression model of the µCT determined that the maximum bone area to total area ratio (maxBA/TA) for all slices that are perpendicular to the direction of fluid flow explained 84% of the variability of the natural logarithm of the experimentally measured permeability. The 2D measure of maxBA/TA performed better than 3D measures in general, although some parameters were reasonably well associated with permeability such as bone volume ratio (BV/TV, r=−0.71), the bone surface/bone volume (BS/BV, r=0.73), and the trabecular thickness (TbTh, r=−0.71). The correlation between the permeability predicted with FE models and experimentally measured permeability was reasonable (r=0.69), but the FE approach did not accurately represent the wide variability of permeability measured experimentally. The results of this study suggest that the changes in the trabecular bone microarchitecture have an exponential relationship with permeability, and the use of µCT-based 2D measurement of maxBA/TA performs well at predicting permeability, thus providing a convenient approach to measure this important aspect affecting biomechanical functions in the tissue.     

Femoral strength is better predicted by finite element models than QCT and DXA.

Clinicians and patients would benefit if accurate methods of predicting and monitoring bone strength in-vivo were available. A group of 51 human femurs (age range 21-93; 23 females, 28 males) were evaluated for bone density and geometry using quantitative computed tomography (QCT) and dual energy X-ray absorptiometry (DXA). Regional bone density and dimensions obtained from QCT and DXA were used to develop statistical models to predict femoral strength ex vivo. The QCT data also formed the basis of a three-dimensional finite element (FE) models to predict structural stiffness. The femurs were separated into two groups; a model training set (n = 25) was used to develop statistical models to predict ultimate load, and a test set (n = 26) was used to validate these models. The main goal of this study was to test the ability of DXA, QCT and FE techniques to predict fracture load non-invasively, in a simple load configuration which produces predominantly femoral neck fractures. The load configuration simulated the single stance phase portion of normal gait; in 87% of the specimens, clinical appearing sub-capital fractures were produced. The training/test study design provided a tool to validate that the predictive models were reliable when used on specimens with "unknown" strength characteristics. The FE method explained at least 20% more of the variance in strength than the DXA models. Planned refinements of the FE technique are expected to further improve these results. Three-dimensional FE models are a promising method for predicting fracture load, and may be useful in monitoring strength changes in vivo.     

The mesh-matching algorithm: an automatic 3D mesh generator for finite element structures

Several authors have employed finite element analysis for stress and strain analysis in orthopaedic biomechanics. Unfortunately, the definition of three-dimensional models is time consuming (mainly because of the manual 3D meshing process) and consequently the number of analyses to be performed is limited. The authors have investigated a new patient-specific method allowing automatically 3D mesh generation for structures as complex as bone for example. This method, called the mesh-matching (M-M) algorithm, generated automatically customized 3D meshes of anatomical structures from an already existing model. The M-M algorithm has been used to generate FE models of 10 proximal human femora from an initial one which had been experimentally validated. The automatically generated meshes seemed to demonstrate satisfying results.     

Experimental and finite element analysis of the mouse caudal vertebrae loading model: prediction of cortical and trabecular bone adaptation

In this study, we attempt to predict cortical and trabecular bone adaptation in the mouse caudal vertebrae loading model using knowledge of bone’s local mechanical environment at the onset of loading. In a previous study, we demonstrated appreciable 25.9 and 11% increases in both trabecular and cortical bone volume density, respectively, when subjecting the fifth caudal vertebrae (C5) of C57BL/6 (B6) mice to an acute loading regime (amplitude of 8N, 3000 cycles, 10 Hz, 3 times a week for 4 weeks). We have also established a validated finite element (FE) model of the C5 vertebra using micro-computed tomography (micro-CT), which characterizes, in 3D, the micro-mechanical strains present in both cortical and trabecular compartments due to the applied loads. To investigate the relationship between load-induced bone adaptation and mechanical strains in-vivo and in-silico data sets were compared. Using data from the previous cross-sectional study, we divided cortical and trabecular compartments into 15 subregions and determined, for each region, a bone formation parameter ΔBV/BS (a cross-sectional measure of the bone volume added to cortical and trabecular surfaces following the described loading regime). Linear regression was then used to correlate mean regional values of ΔBV/BS with mean values of mechanical strains derived from the FE models which were similarly regionalized. The mechanical parameters investigated were strain energy density (SED), the orthogonal strains (e _x , e _y , e _z ) and the three shear strains (e _xy , e _yz , e _zx ). For cortical regions, regression analysis showed SED to correlate extremely well with ΔBV/BS (R ² =?0.82) and e _z (R ²?=?0.89). Furthermore, SED was found to predict expansion of the cortical shell correlating significantly with the regional percentage increases in cortical tissue volume (R ² = 0.92), cortical marrow volume (R ² =?0.91) and cortical thickness (R ² = 0.56). For trabecular regions, FE parameters were found not to correlate with load-induced trabecular bone morphology. These results indicate that load-induced cortical morphology can be predicted from population data, whereas the prediction of trabecular morphology requires subject-specific micro- architecture.     

Strain energy in the femoral neck during exercise

Physical activity is recommended to mitigate the incidence of hip osteoporotic fractures by improving femoral neck strength. However, results from clinical studies are highly variable and unclear about the effects of physical activity on femoral neck strength. We ranked physical activities recommended for promoting bone health based on calculations of strain energy in the femoral neck. According to adaptive bone-remodeling theory, bone formation occurs when the strain energy (S) exceeds its homeostatic value by 75%. The potential effectiveness of activity type was assessed by normalizing strain energy by the applied external load. Tensile strain provided an indication of bone fracture. External force and joint motion data for 15 low- and high-load weight-bearing and resistance-based activities were used. High-load activities included weight-bearing activities generating a ground force above 1 body-weight and maximal resistance exercises about the hip and the knee. Calculations of femoral loads were based on musculoskeletal and finite-element models. Eight of the fifteen activities were likely to trigger bone formation, with isokinetic hip extension (ΔS=722%), one-legged long jump (ΔS=572%), and isokinetic knee flexion (ΔS=418%) inducing the highest strain energy increase. Knee flexion induced approximately ten times the normalized strain energy induced by hip adduction. Strain and strain energy were strongly correlated with the hip-joint reaction force (R²=0.90–0.99; p<0.05) for all activities, though the peak load location was activity-dependent. None of the exercises was likely to cause fracture. Femoral neck mechanics is activity-dependent and maximum isokinetic hip-extension and knee-flexion exercises are possible alternative solutions to impact activities for improving femoral neck strength.     

Impaired bone formation and osteopenia in heterozygous β<Superscript>IVSII-654</Superscript> knockin thalassemic mice

β-thalassemia caused by the C→T mutation at nucleotide 654 of the intron 2 (β^IVSII-654) results in aberrant splicing of β-globin RNA, leading to an almost absence of β-globin synthesis. Although trabecular and cortical bone loss was previously reported in β-thalassemic mice with deletion of β-globin gene, the microscopic changes in trabecular structure in β^IVSII-654 thalassemic mice remained elusive. Here, we investigated the macroscopic and microscopic bone changes in 12-week-old β^IVSII-654 knockin thalassemic mice by dual-energy X-ray absorptiometry (DXA) and histomorphometric analysis, respectively. DXA revealed a decrease in bone mineral density in the lumbar vertebrae and tibial metaphysis, but not in the femoral diaphysis, suggesting that β^IVSII-654 thalassemia predominantly led to osteopenia at the trabecular site, but not the cortical site. Further histomorphometric analysis of the tibial secondary spongiosa showed that trabecular bone volume was significantly decreased with the expansion of marrow cavity. Decreases in osteoblast surface, osteoid surface, mineral apposition rate, mineralizing surface, and mineralized volume were also observed. Moreover, trabecular bone resorption was markedly enhanced as indicated by increases in the osteoclast surface and eroded surface. It could be concluded that β^IVSII-654 thalassemia impaired bone formation and enhanced bone resorption, thereby leading to osteopenia especially at the trabecular sites, such as the tibial metaphysis.     

The effect of resorption cavities on bone stiffness is site dependent

Resorption cavities formed during the bone remodelling cycle change the structure and thus the mechanical properties of trabecular bone. We tested the hypotheses that bone stiffness loss due to resorption cavities depends on anatomical location, and that for identical eroded bone volumes, cavities would cause more stiffness loss than homogeneous erosion. For this purpose, we used beam–shell finite element models. This new approach was validated against voxel-based FE models. We found an excellent agreement for the elastic stiffness behaviour of individual trabeculae in axial compression (R² = 1.00) and in bending (R²>0.98), as well as for entire trabecular bone samples to which resorption cavities were digitally added (R² = 0.96, RMSE = 5.2%). After validation, this new method was used to model discrete cavities, with dimensions taken from a statistical distribution, on a dataset of 120 trabecular bone samples from three anatomical sites (4th lumbar vertebra, femoral head, iliac crest). Resorption cavities led to significant reductions in bone stiffness. The largest stiffness loss was found for samples from the 4th lumbar vertebra, the lowest for femoral head samples. For all anatomical sites, resorption cavities caused significantly more stiffness loss than homogeneous erosion did. This novel technique can be used further to evaluate the impact of resorption cavities, which are known to change in several metabolic bone diseases and due to treatment, on bone competence.     

Embedding of human vertebral bodies leads to higher ultimate load and altered damage localisation under axial compression

Computer tomography (CT)-based finite element (FE) models of vertebral bodies assess fracture load in vitro better than dual energy X-ray absorptiometry, but boundary conditions affect stress distribution under the endplates that may influence ultimate load and damage localisation under post-yield strains. Therefore, HRpQCT-based homogenised FE models of 12 vertebral bodies were subjected to axial compression with two distinct boundary conditions: embedding in polymethylmethalcrylate (PMMA) and bonding to a healthy intervertebral disc (IVD) with distinct hyperelastic properties for nucleus and annulus. Bone volume fraction and fabric assessed from HRpQCT data were used to determine the elastic, plastic and damage behaviour of bone. Ultimate forces obtained with PMMA were 22% higher than with IVD but correlated highly (R² = 0.99). At ultimate force, distinct fractions of damage were computed in the endplates (PMMA: 6%, IVD: 70%), cortex and trabecular sub-regions, which confirms previous observations that in contrast to PMMA embedding, failure initiated underneath the nuclei in healthy IVDs. In conclusion, axial loading of vertebral bodies via PMMA embedding versus healthy IVD overestimates ultimate load and leads to distinct damage localisation and failure pattern.     

Development of patient-specific 3D models from histopathological samples for applications in radiation therapy

The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry.Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples.The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively.Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.     

Bone Analysis Using Trabecular Bone Score and Dual-Energy X-Ray Absorptiometry-Based 3-Dimensional Modeling in Postmenopausal Women With Primary Hyperparathyroidism

ObjectivePredominance of bone loss in cortical sites with relative preservation of trabecular bone, even in postmenopausal women, has been described in primary hyperparathyroidism (PHPT). The aim of this study was to evaluate bone microarchitectural differences using dual-energy x-ray absorptiometry (DXA), trabecular bone score (TBS), and DXA-based 3-dimensional (3D) modeling (3D-DXA) between postmenopausal women diagnosed with PHPT (PM-PHPT) and healthy postmenopausal controls.MethodsThis retrospective study included 44 women with PM-PHPT (9 of whom had fractures) and 48 healthy women matched by age, body mass index, and years since menopause treated at Hospital Universitario Fundación Jiménez Díaz between 2008 and 2017. The bone mineral density (BMD) of the lumbar spine (LS), femoral neck, total hip (TH), and 1/3 radius was assessed using DXA, and trabecular volumetric BMD (vBMD), cortical vBMD, integral vBMD, cortical thickness, and cortical surface BMD at TH were assessed using a 3D-DXA software and TBS at LS.ResultsThe mean adjusted BMD values at LS, the femoral neck, and TH; TBS at LS; and TH 3D-DXA parameters (trabecular vBMD, integral vBMD, cortical thickness, and cortical surface BMD) were significantly reduced in women with PM-PHPT compared with those in the controls. However, differences in mean cortical vBMD were not statistically significant (P = .078). There were no significant differences in mean BMD, TBS, or the 3D-DXA parameters between patients with fractures and those without fractures. The 25-hydroxyvitamin D level appeared to be associated with TBS but not with DXA and 3D-DXA measurements.ConclusionPM-PHPT has significant involvement of the trabecular and cortical compartments of the bone, as determined by DXA, TBS, and 3D-DXA.     

The Associations Between Hypovitaminosis D,Higher Pth Levels With Bone Mineral Densities,And Risk Of The 10-Year Probability Of Major Osteoporotic Fractures In Chinese Patients With T2Dm

Objective: In the current study, we investigated the vitamin D status, and its relationships with parathyroid hormone (PTH) levels, bone mineral density (BMD), and the 10-year probability of fractures in Chinese patients with type 2 diabetes mellitus (T2DM).Methods: This was a cross-sectional study of 785 patients. BMDs at the lumbar spine (L2-4), femoral neck (FN), and total hip (TH) were measured by dual-energy X-ray absorptiometry (DXA). Serum levels of 25-hydroxyvitamin D (25(OH)D) and intact PTH were also quantified. The 10-year probability of fracture risk (major osteoporotic fracture &lsqb;MOF] and hip fracture &lsqb;HF]) was assessed using the fracture risk assessment tool (FRAX).Results: The prevalence of vitamin D deficiency was 82.3%, and the mean 25(OH)D level was 36.9 ± 15.2 nmol/L. The adequate group had higher BMDs at the FN and TH and lower MOF risk than the inadequate groups. Lower 25(OH)D was associated with higher PTH (r = -0.126, P<.001). PTH was negatively correlated with BMDs at 3 sites and positively correlated with MOF and HF, but this relationship disappeared in the adequate subgroup. Multivariate stepwise regression analysis revealed that PTH was the determinant of MOF (standard β = 0.073, P = .010) and HF (standard β = 0.094, P = .004).Conclusion: Our results identified a significantly high rate of vitamin D deficiency among Chinese patients with T2DM. PTH is an important risk factor responsible for the higher 10-year probability of osteoporotic fractures in diabetic patients, especially in those with lower vitamin D levels.Abbreviations: AKP = alkaline phosphatase; ALB = serum albumin; BMD = bone mineral density; BMI = body mass index; Ca = calcium; CKD = chronic kidney disease; Cr = creatinine; FN = femoral neck; FRAX = fracture risk assessment tool; HbA1c = glycated hemoglobin A1c; HF = hip fracture; L2-4 = lumbar spine; MOF = major osteoporotic fracture; 25(OH)D = 25-hydroxyvitamin D; P = phosphorus; PTH = parathyroid hormone; T2DM = type 2 diabetes mellitus; TH = total hip; UA = uric acid     

Experimental validation of finite element predicted bone strain in the human metatarsal

Metatarsal stress fracture is a common injury observed in athletes and military personnel. Mechanical fatigue is believed to play an important role in the etiology of stress fracture, which is highly dependent on the resulting bone strain from the applied load. The purpose of this study was to validate a subject-specific finite element (FE) modeling routine for bone strain prediction in the human metatarsal. Strain gauge measurements were performed on 33 metatarsals from seven human cadaveric feet subject to cantilever bending, and subject-specific FE models were generated from computed tomography images. Material properties for the FE models were assigned using a published density-modulus relationship as well as density-modulus relationships developed from optimization techniques. The optimized relationships were developed with a ‘training set’ of metatarsals (n = 17) and cross-validated with a ‘test set’ (n = 16). The published and optimized density elasticity equations provided FE-predicted strains that were highly correlated with experimental measurements for both the training (r² ≥ 0.95) and test (r² ≥ 0.94) sets; however, the optimized equations reduced the maximum error by 10% to 20% relative to the published equation, and resulted in an X = Y type of relationship between experimental measurements and FE predictions. Using a separate optimized density-modulus equation for trabecular and cortical bone did not improve strain predictions when compared to a single equation that spanned the entire bone density range. We believe that the FE models with optimized material property assignment have a level of accuracy necessary to investigate potential interventions to minimize metatarsal strain in an effort to prevent the occurrence of stress fracture.     

Geometry and bone mineral density determinants of femoral neck strength changes following exercise

Physical exercise induces spatially heterogeneous adaptation in bone. However, it remains unclear where the changes in BMD and geometry have the greatest impact on femoral neck strength. The aim of this study was to determine the principal BMD-and-geometry changes induced by exercise that have the greatest effect on femoral neck strength. Pre- and post-exercise 3D-DXA images of the proximal femur were collected of male participants from the LIFTMOR-M exercise intervention trial. Meshes with element-by-element correspondence were generated by morphing a template mesh to each bone to calculate changes in BMD and geometry. Finite element (FE) models predicted femoral neck strength changes under single-leg stance and sideways fall load. Partial least squares regression (PLSR) models were developed with BMD-only, geometry-only, and BMD-and-geometry changes to determine the principal modes that explained the greatest variation in neck strength changes. The PLSR models explained over 90% of the strength variation with 3 PLS components using BMD-only (R² > 0.92, RMSE < 0.06 N) and 8 PLS components with geometry-only (R² > 0.93, RMSE < 0.06 N). Changes in the superior neck and distal cortex were most important during single-leg stance while the superior neck, medial head, and lateral trochanter were most important during a sideways fall. Local changes in femoral neck and head geometry could differentiate the exercise groups from the control group. Exercise interventions may target BMD changes in the superior neck, inferior neck, and greater trochanter for improved femoral neck strength in single-leg stance and sideways fall.

     

Local irradiation alters bone morphology and increases bone fragility in a mouse model

Insufficiency fracture following radiation therapy (RTx) is a challenging clinical problem and typical bone mass measures fail to predict these fractures. The goals of this research were to develop a mouse model that results in reduced bone strength following focal irradiation, quantify morphological and strength changes occurring over time, and determine if a positive correlation between bone morphology and strength is retained after irradiation. Right hind limbs of 13 week-old female Balb/c mice were irradiated (5 or 20 Gy) using a therapeutic X-ray unit. Left limbs served as control. Animals were euthanized at 2, 6, 12, or 26 weeks. Axial compression tests of the distal femur were used to quantify whole bone strength. Specimen-specific, non-linear finite element (FE) analyses of the mechanical tests were performed using voxel-based meshes with two different material failure models: a linear bone density–strength relationship and a non-linear ‘embrittled’ relationship. Radiation resulted in a dose dependent increase in cortical bone density and marked loss of trabecular bone, measured using micro-CT. An early (2 week) increase in bone volume was associated with an increase in bone strength following irradiation; at 12 weeks there was a loss of bone strength despite higher bone volume for irradiated limbs. There was a positive correlation between bone volume bone and strength in control (r²=0.63) but not irradiated femora (r²=0.08). FE analysis with a constant strain failure model resulted in improved prediction of bone strength for irradiated limbs (r²=0.34) and this was improved further with the embrittled material model (r²=0.46). In summary, focal irradiation leads to substantial changes in bone morphology and strength with time, where there is a decreased bone strength following irradiation in the face of increasing bone mass; FE models with a non-linear embrittled material model were most successful in simulating these experimental findings.