Yunhua Luo

Precision study of DXA‐based patient‐specific finite element modeling for assessing hip fracture risk

Finite element (FE) modeling based on a patients hip dual energy X-ray absorptiometry (DXA) image is a promising tool for more accurately assessing hip fracture risk, as it is able to comprehensively consider effects from all the mechanical parameters affecting hip fracture. However, a number of factors influence the precision (also known as repeatability or reproducibility) of a DXA-based FE procedure, for example, subject positioning in DXA scanning. As a procedure is required to have adequately high precision in clinical application, we investigated the effects of the involved factors on the precision of a DXA-based patient-specific FE procedure developed by the authors, to provide insight into how the precision of the procedure can be improved so that it can meet the clinical standards. Fracture risk indices corresponding to initial and repeat DXA scans acquired in 30 typical clinical subjects were computed and compared to assess short term repeatability of the procedure. It was found that inconsistent positioning followed by manual segmentation of the projected femur contour induced significant variability in the predicted fracture risk indices. This research suggests that, to apply the DXA-based FE procedure in clinical assessment, it will be necessary to pay more strict attention to subject positioning in DXA scanning.

Long-Term Proton Pump Inhibitor Use Is Not Associated With Changes in Bone Strength and Structure

OBJECTIVES:Multiple studies have reported an association between proton pump inhibitor (PPI) use and fracture. However, the causality of this association is questionable, as there is not a well defined mechanism of action, nor is there evidence of an effect on PPIs on areal bone mineral density (aBMD) using dual photon X-ray absorptiometry (DXA). It is possible that PPIs may induce changes in bone structure which would predispose to fracture in the absence of changes in aBMD. We used three-dimensional quantitative computed tomography (3D-QCT) imaging to determine if long-term PPI use was associated with structural changes in bone independent of aBMD.METHODS:We enrolled a sample of long-term (≥5 years) PPI users matched to a similar cohort of persons with no PPI use in the previous 5 years. All subjects underwent assessment of aBMD using DXA, volumetric BMD using 3D-QCT, as well as markers of bone metabolism. Measures of bone strength, including buckling ratio and section modulus, were also compared between the two samples.RESULTS:104 subjects were enrolled (52 PPI users and 52 PPI non-users). There were no differences detected in standard BMD, volumetric BMD, markers of bone metabolism or measures of bone strength between the two groups.CONCLUSIONS:Long-term PPI use is not associated with any changes in bone mineral density or bone strength that would predispose to an increased risk of fracture. These findings provide further evidence that the association between PPI use and fracture is not causal.

A preliminary dual-energy X-ray absorptiometry-based finite element model for assessing osteoporotic hip fracture risk

To more accurately assess osteoporotic hip fracture risk in a specific patient, a dual-energy X-ray absorptiometry (DXA)-based finite element model was constructed from the patient’s femur DXA image. The outermost contour of the femur bone segmented from the DXA image was used to generate a finite element mesh. Bone mechanical properties, such as Young’s modulus, are correlated with areal bone mineral density (BMD) captured in the DXA image. A quasi-static loading condition representing a sideway fall was applied to the finite element model. Three fracture risk indices were introduced and expressed as ratios of internal forces caused by impact forces occurring in sideway fall to bone ultimate cross-section strength at the three critical locations, i.e. the femoral neck, the intertrochanteric region, and the subtrochanteric region. The proposed finite element modelling procedure was validated against six representative clinical cases extracted from the Manitoba BMD database, where initial and follow-up DXA images have been taken to monitor longitudinal variation of areal BMD in individual patients. It was found from the clinical validation that variations in the proposed fracture risk indices have the same trends as those indicated by the conventional areal BMD and T-score. In addition, by the three proposed fracture risk indices it is possible to further identify the specific fracture location. It was also found that for the same subject, the variations in the three fracture risk indices have quite different magnitudes, with intertrochanteric region the largest and subtrochanteric region the smallest, which is probably owing to the different content of trabecular and cortical bones in the three regions. With further development, it is promising that the proposed DXA-based finite element model will be a useful tool for accurate assessment of osteoporosis development and for treatment monitoring.

A generalized finite-difference method based on minimizing global residual

An improved generalized finite-difference method is proposed in this paper, as an alternative meshless method to solve differential equations. The method establishes discrete equations by minimizing a global residual. A general frame for constructing difference schemes is first described. As one choice the moving least square method is used in this paper. Compared with other generalized finite-difference methods, the improved method yields a set of discrete equations having the favorable properties such as symmetric, positive definite and well conditioned. Compared with meshless methods based on a variational principle or a weak form, the method described in this paper does not need a numerical integration and thus provides an alternative way to avoid the difficulties in implementing a numerical integration. In the proposed method there is no such inconvenience in applying essential boundary conditions as commonly encountered in other meshless methods. Numerical examples show that the improved method has a high convergence rate and can produce accurate results even with a coarse mesh.

A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture

Osteoporotic fracture has been found associated with many clinical risk factors, and the associations have been explored dominantly by evidence-based and case-control approaches. The major challenges emerging from the studies are the large number of the risk factors, the difficulty in quantification, the incomplete list, and the interdependence of the risk factors. A biomechanical sorting of the risk factors may shed lights on resolving the above issues. Based on the definition of load-strength ratio (LSR), we first identified the four biomechanical variables determining fracture risk, i.e., the risk of fall, impact force, bone quality, and bone geometry. Then, we explored the links between the FRAX clinical risk factors and the biomechanical variables by looking for evidences in the literature. To accurately assess fracture risk, none of the four biomechanical variables can be ignored and their values must be subject-specific. A clinical risk factor contributes to osteoporotic fracture by affecting one or more of the biomechanical variables. A biomechanical variable represents the integral effect from all the clinical risk factors linked to the variable. The clinical risk factors in FRAX mostly stand for bone quality. The other three biomechanical variables are not adequately represented by the clinical risk factors. From the biomechanical viewpoint, most clinical risk factors are interdependent to each other as they affect the same biomechanical variable(s). As biomechanical variables must be expressed in numbers before their use in calculating LSR, the numerical value of a biomechanical variable can be used as a gauge of the linked clinical risk factors to measure their integral effect on fracture risk, which may be more efficient than to study each individual risk factor.

A two-level subject-specific biomechanical model for improving prediction of hip fracture risk

BACKGROUND Sideways fall-induced hip fracture is a major worldwide health problem among the elderly population. However, all existing biomechanical models for predicting hip fracture mainly consider the femur related parameters. Their accuracy is limited as hip fracture is significantly affected by loading conditions as well. The objective of this study was to develop a biomechanical model for improving assessment of hip fracture risk by subject-specific prediction of fall-induced loading conditions. METHOD All information required to construct the models was extracted from the subjects whole-body and hip medical image in order to make the models subject-specific. Fall-induced hip fracture risk for eighty clinical cases was calculated under two sets of loading conditions: subject-specific determined by the proposed model, and non-subject-specific obtained from empirical functions. The predicted hip fracture risk indices were then compared with clinical observations. FINDINGS It was found that the subject-specific prediction of fall-induced loading conditions significantly improves the hip fracture risk assessment. Consistent to the clinical observations, the fracture risk predicted by the proposed model suggested that obesity is a protective factor for hip fracture and underweight subjects are more likely to experience a hip fracture. INTERPRETATIONS This study shows that hip fracture risk is affected by a number of factors, including body weight, body height, impact force, body mass index, hip soft tissue thickness, and bone quality. The proposed model provides a comprehensive, fast, accurate, and non-expensive method for prediction of hip fracture risk which should lead to more effective prevention of hip fractures.

Finite-element study of cerebrospinal fluid in mitigating closed head injuries.

The mechanism of cerebrospinal fluid in mitigating closed head injuries caused by mild impacts was investigated by finite-element modeling. Three biomechanical models were constructed. In these models, cerebrospinal fluid was considered as a soft solid material, an inviscid fluid without intracranial pressure, and an inviscid fluid with normal intracranial pressure, respectively, while other conditions such as the finite-element mesh, the impact, and the boundary conditions were kept the same. The recently developed nearest nodes finite-element method was adopted to deal with large deformations in brain tissue. Results obtained from the numerical studies showed that cerebrospinal fluid was able to remarkably reduce the maximum peak strains, especially the shear strains induced by impacts and transmitted to the brain. Cerebrospinal fluid with intracranial pressure was able to further buffer relative oscillations between the skull and the brain.

Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling

There is controversy about whether or not body parameters affect hip fracture in men and women in the same way. In addition, although bone mineral density (BMD) is currently the most important single discriminator of hip fracture, it is unclear if BMD alone is equally effective for men and women. The objective of this study was to quantify and compare the associations of hip fracture risk with BMD and body parameters in men and women using our recently developed two-level biomechanical model that combines a whole-body dynamics model with a proximal-femur finite element model. Sideways fall induced impact force of 130 Chinese clinical cases, including 50 males and 80 females, were determined by subject-specific dynamics modeling. Then, a DXA-based finite element model was used to simulate the femur bone under the fall-induced loading conditions and calculate the hip fracture risk. Body weight, body height, body mass index, trochanteric soft tissue thickness, and hip bone mineral density were determined for each subject and their associations with impact force and hip fracture risk were quantified. Results showed that the association between impact force and hip fracture risk was not strong enough in both men (r=-0.31,p<0.05) and women (r=0.42,p<0.001) to consider the force as a sole indicator of hip fracture risk. The correlation between hip BMD and hip fracture risk in men (r=-0.83,p<0.001) was notably stronger than that in women (r=-0.68,p<0.001). Increased body mass index was not a protective factor against hip fracture in men (r=-0.13,p>0.05), but it can be considered as a protective factor among women (r=-0.28,p<0.05). In contrast to men, trochanteric soft tissue thickness can be considered as a protective factor against hip fracture in women (r=-0.50,p<0.001). This study suggested that the biomechanical risk/protective factors for hip fracture are sex-specific. Therefore, the effect of body parameters should be considered differently for men and women in hip fracture risk assessment tools. These findings support further exploration of sex-specific preventive and protective measurements to reduce the incidence of hip fractures.

Prediction of backside micromotion in total knee replacements by finite element simulation

The micromotion at the interface between the polyethylene tibial insert and metal tibial tray, in modular total knee replacements, has been shown to contribute to wear particle-induced osteolysis and cause implant failure. Therefore, studying the design parameters that are involved in the backside wear process is an important task that may lead to improvement in new total knee replacements. In the present study, a finite element model was developed to predict the backside micromotion along the entire modular interface. Both the linear elastic constitutive model and non-linear J2-plasticity constitutive model were considered in the finite element model for polyethylene and were corroborated against published results obtained from displacement controlled knee simulator wear tests. The finite element simulation with the non-linear J2-plasticity constitutive model was able to more accurately predict backside micromotion, while the linear elastic constitutive model was not. The developed finite element model (including the non-linear J2-plasticity constitutive model) was then applied to assess the effects of the tibial tray locking mechanism design (dovetails versus full-peripheral design) and different levels of interference fit on insert micromotion. The developed finite element model, implementing the non-linear J2-plasticity constitutive model, was shown to successfully predict clinical amounts of backside micromotion and could be used for the design and development of total knee replacements for the reduction of backside micromotion and wear.

Study of DXA-derived lateral–medial cortical bone thickness in assessing hip fracture risk

The currently available clinical tools have limited accuracy in predicting hip fracture risk in individuals. We investigated the possibility of using normalized cortical bone thickness (NCBT) estimated from the patients hip DXA (dual energy X-ray absorptiometry) as an alternative predictor of hip fracture risk. Hip fracture risk index (HFRI) derived from subject-specific DXA-based finite element model was used as a guideline in constructing the mathematical expression of NCBT. We hypothesized that if NCBT has stronger correlations with HFRI than the single risk factors such as areal BMD (aBMD), then NCBT can be a better predictor. The hypothesis was studied using 210 clinical cases, including 60 hip fracture cases, obtained from the Manitoba Bone Mineral Density Database. The results showed that, in general HFRI has much stronger correlations with NCBT than any of the single risk factors; the strongest correlation was observed at the superior side of the narrowest femoral neck with r2 = 0.81 (p < 0.001), which is much higher than the correlation with femoral aBMD, r2 = 0.50 (p < 0.001). The capability of aBMD, NCBT, and HFRI in discriminating the hip fracture cases from the non-fracture ones, expressed as the area under the curve with 95% confidence interval, AUC (95% CI), is respectively 0.627 (0.593–0.657), 0.714 (0.644–0.784) and 0.839 (0.787–0.892). The short-term repeatability of aBMD, NCBT, and HFRI, measured by the coefficient of variation (CV, %), was found to be in the range of (0.64–1.22), (1.93–3.41), (3.10–4.16), respectively. We thus concluded that NCBT is potentially a better predictor of hip fracture risk.