Large-sliding contact elements accurately predict levels of bone-implant micromotion relevant to osseointegration

Primary stability is recognised as an important determinant in the aseptic loosening failure process of cementless implants. An accurate evaluation of the bone–implant relative micromotion is becoming important both in pre-clinical and clinical studies. If the biological threshold for micro-movements is in the range 100–200 μm then, in order to be discriminative, any method used to evaluate the primary stability should have an accuracy of 10–20 μm or better. Additionally, such method should also be able to report the relative micromotion at each point of the interface. None of the available experimental methods satisfies both requirements. Aim of the present study is to verify if any of the current finite element modelling techniques is sufficiently accurate in predicting the primary stability of a cementless prosthesis to be used to decide whether the micromotion may or may not jeopardise the implant osseointegration. The primary stability of an anatomic cementless stem, as measured in vitro, was used as a benchmark problem to comparatively evaluate different contact modelling techniques. Frictionless contact, frictional contact and press-fitted frictional contact conditions were modelled using alternatively node-to-node, node-to-face and face-to-face contact elements. The model based on face-to-face contact elements accounting for frictional contact and initial press-fit was able to predict the micromotion measured experimentally with an average (RMS) error of 10 μm and a peak error of 14 μm. All the other models presented errors higher than 20 μm assumed in the present study as an accuracy threshold.     

Mechanical testing of cancellous bone from the femoral head: experimental errors due to off-axis measurements

The aim of this study was to verify whether a misalignment between the testing direction and the trabecular main direction has a significant effect on the compressive behaviour of cancellous bone. Ten cylindrical specimens were extracted from femoral heads with a misalignment to the trabecular main direction of approximately 20 degrees. Each specimen was paired with a specimen extracted aligned with the main direction of the trabeculae on the basis of the closest bone volume fraction, obtaining two groups, one 'aligned' and one 'misaligned'. The average off-axis angle was 6.1 degrees and 21.6 degrees for the 'aligned' and 'misaligned' group, respectively. The specimens underwent micro-tomographic analysis, compressive testing, micro-indentation testing and ashing. No significant differences were found in histomorphometric parameters, hardness and ash density between the two groups, whereas significant differences were found in Young's modulus and ultimate stress: both parameters, measured for the 'misaligned' group, were about 40% lower than those measured for the 'aligned' group. These results demonstrate a great effect of the angle between the testing direction and the main direction of the trabecular structure on the compressive behaviour of cancellous bone. This angle should be reduced as much as possible (in the present work the average value was 6.6+/-3.3 degrees), in any case measured, and always reported together with the mechanical parameters of cancellous bone.     

Automatic generation of accurate subject-specific bone finite element models to be used in clinical studies

Most of the finite element models of bones used in orthopaedic biomechanics research are based on generic anatomies. However, in many cases it would be useful to generate from CT data a separate finite element model for each subject of a study group. In a recent study a hexahedral mesh generator based on a grid projection algorithm was found very effective in terms of accuracy and automation. However, so far the use of this method has been documented only on data collected in vitro and only for long bones. The present study was aimed at verifying if this method represents a procedure for the generation of finite element models of human bones from data collected in vivo, robust, accurate, automatic and general enough to be used in clinical studies. Robustness, automation and numerical accuracy of the proposed method were assessed on five femoral CT data sets of patients affected by various pathologies. The generality of the method was verified by processing a femur, an ileum, a phalanx, a proximal femur reconstruction, and the micro-CT of a small sample of spongy bone. The method was found robust enough to cope with the variability of the five femurs, producing meshes with a numerical accuracy and a computational weight comparable to those found in vitro. Even when the method was used to process the other bones the levels of mesh conditioning remained within acceptable limits. Thus, it may be concluded that the method presents a generality sufficient to cope with almost any orthopaedic application.     

Are spontaneous fractures possible? An example of clinical application for personalised,multiscale neuro-musculo-skeletal modelling

Elderly frequently present variable degrees of osteopenia, sarcopenia, and neuromotor control degradation. Severely osteoporotic patients sometime fracture their femoral neck when falling. Is it possible that such fractures might occur without any fall, but rather spontaneously while the patient is performing normal movements such as level walking? The aim of this study was to verify if such spontaneous fractures are biomechanically possible, and in such case, which conditions of osteoporosis, sarcopenia, and neuromotor degradation could produce them. To the purpose, a probabilistic multiscale body-organ model validated against controlled experiments was used to predict the risk of spontaneous fractures in a population of 80-years old women, with normal weight and musculoskeletal anatomy, and variable degree of osteopenia, sarcopenia, and neuromotor control degradation. A multi-body inverse dynamics sub-model, coupled to a probabilistic neuromuscular sub-model, and to a femur finite element sub-model, formed the multiscale model, which was run within a Monte Carlo stochastic scheme, where the various parameters were varied randomly according to well defined distributions. The model predicted that neither extreme osteoporosis, nor extreme neuromotor degradation alone are sufficient to predict spontaneous fractures. However, when the two factors are combined an incidence of 0.4% of spontaneous fractures is predicted for the simulated population, which is consistent with clinical reports. When the model represented only severely osteoporotic patients, the incidence of spontaneous fractures increased to 29%. Thus, is biomechanically possible that spontaneous femoral neck fractures occur during level walking, due to a combination of severe osteoporosis and severe neuromotor degradation.     

Dependence of mechanical compressive strength on local variations in microarchitecture in cancellous bone of proximal human femur

Human cancellous bone is a heterogeneous material. Despite this, most of the published studies report correlations between mechanical properties and morphometric parameters averaged on the whole specimen. This work investigated whether local variations in morphometric parameters were linked to the localized failure regions of cancellous bone. Additionally, it was examined whether local values of morphometric parameters can predict the ultimate stress better than the average bone volume fraction (BV/TV). Cylindrical cancellous bone specimens extracted along the primary compressive group of human femoral heads were studied. These were microCT-imaged to assess the morphometric parameters, compressed to determine the ultimate stress, and rescanned by microCT to visualize the failure region. Failure involved slightly less than half of the free height of the specimens. Significant differences were found in the morphometric parameters calculated in the failure and in the non-failure regions. The cross-sections containing minimum BV/TV values were those most often located inside the failure region (83%, p<0.001). Regression analysis confirmed that variations in BV/TV best describe variations in ultimate stress (R2=0.84) out of the averaged morphometric parameters. The prediction of ultimate stress increased when minimum or maximum values of the morphometric parameters were taken, with the highest prediction found by considering the minimum BV/TV (R2=0.95). In conclusion, due to the heterogeneity of cancellous bone, there may exist regions characterized by a different microarchitecture, where the bone is weaker and consequently is more likely to fail. These regions mostly contain minimum values in BV/TV, which were found to predict ultimate stress better than average BV/TV.     

Are Subject-Specific Musculoskeletal Models Robust to the Uncertainties in Parameter Identification?

Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be affected by an uncertainty in the same order of magnitude of its value, although this condition has low probability to occur.     

Mechanical validation of whole bone composite tibia models

Composite synthetic models of the human tibia have recently become commercially available as substitutes for cadaveric specimens. Their use is justified by the advantages they offer as a substitute for real tibias. The present investigation concentrated on an extensive experimental validation of the mechanical behaviour of the whole bone composite model, compared to human specimens for different loading conditions. The stiffness of the tibias was measured with a torsional load applied along the long axis, and with a bending load applied both in the latero-medial and in the antero-posterior direction. The bending stiffness of the composite tibias matched well with that of the cadaveric specimens. This was not true for the torsional stiffness. In fact, the composite tibias were much stiffer than the cadaveric specimens, possibly due to the structure of the reinforcement material. The inter-specimen variability for the composite tibias was much lower than that for the cadaveric specimens. Thus, it seems that the composite tibias are suitable to replace cadaveric specimens for certain types of test, whereas they might be unsuitable for others, depending on the loading regimen.     

Sensitivity of a subject-specific musculoskeletal model to the uncertainties on the joint axes location

Subject-specific musculoskeletal models have become key tools in the clinical decision-making process. However, the sensitivity of the calculated solution to the unavoidable errors committed while deriving the model parameters from the available information is not fully understood. The aim of this study was to calculate the sensitivity of all the kinematics and kinetics variables to the inter-examiner uncertainty in the identification of the lower limb joint models. The study was based on the computer tomography of the entire lower-limb from a single donor and the motion capture from a body-matched volunteer. The hip, the knee and the ankle joint models were defined following the International Society of Biomechanics recommendations. Using a software interface, five expert anatomists identified on the donor's images the necessary bony locations five times with a three-day time interval. A detailed subject-specific musculoskeletal model was taken from an earlier study, and re-formulated to define the joint axes by inputting the necessary bony locations. Gait simulations were run using OpenSim within a Monte Carlo stochastic scheme, where the locations of the bony landmarks were varied randomly according to the estimated distributions. Trends for the joint angles, moments, and the muscle and joint forces did not substantially change after parameter perturbations. The highest variations were as follows: (a) 11° calculated for the hip rotation angle, (b) 1% BW × H calculated for the knee moment and (c) 0.33 BW calculated for the ankle plantarflexor muscles and the ankle joint forces. In conclusion, the identification of the joint axes from clinical images is a robust procedure for human movement modelling and simulation.