Consideration of multiple load cases is critical in modelling orthotropic bone adaptation in the femur

Functional adaptation of the femur has been investigated in several studies by embedding bone remodelling algorithms in finite element (FE) models, with simpli- fications often made to the representation of bone’s material symmetry and mechanical environment. An orthotropic strain-driven adaptation algorithm is proposed in order to predict the femur’s volumetric material property distribution and directionality of its internal structures within a continuum. The algorithm was applied to a FE model of the femur, with muscles, ligaments and joints included explicitly. Multiple load cases representing distinct frames of two activities of daily living (walking and stair climbing) were considered. It is hypothesised that low shear moduli occur in areas of bone that are simply loaded and high shear moduli in areas subjected to complex loading conditions. In addition, it is investigated whether material properties of different femoral regions are stimulated by different activities. The loading and boundary conditions were considered to provide a physiological mechanical environment. The resulting volumetric material property distribution and directionalities agreed with ex vivo imaging data for the whole femur. Regions where non-orthogonal trabecular crossing has been documented coincided with higher values of predicted shear moduli. The topological influence of the different activities modelled was analysed. The influence of stair climbing on the properties of the femoral neck region is highlighted. It is recommended that multiple load cases should be considered when modelling bone adaptation. The orthotropic model of the complete femur is released with this study

Generative deep learning applied to biomechanics: creating an infinite number of realistic walking data for modelling and data augmentation purposes

Our work using generative deep learning models to generate synthetic human movement data to augment existing datasets was presented at the 9th World Congress of Biomechanics

Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.

A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par

Simulating the effect of muscle weakness and contracture on neuromuscular control of normal gait in children

Altered neural control of movement and musculoskeletal deficiencies are common in children with spastic cerebral palsy (SCP), with muscle weakness and contracture commonly experienced. Both neural and musculoskeletal deficiencies are likely to contribute to abnormal gait, such as equinus gait (toe-walking), in children with SCP. However, it is not known whether the musculoskeletal deficiencies prevent normal gait or if neural control could be altered to achieve normal gait. This study examined the effect of simulated muscle weakness and contracture of the major plantarflexor/dorsiflexor muscles on the neuromuscular requirements for achieving normal walking gait in children. Initial muscle-driven simulations of walking with normal musculoskeletal properties by typically developing children were undertaken. Additional simulations with altered musculoskeletal properties were then undertaken; with muscle weakness and contracture simulated by reducing the maximum isometric force and tendon slack length, respectively, of selected muscles. Muscle activations and forces required across all simulations were then compared via waveform analysis. Maintenance of normal gait appeared robust to muscle weakness in isolation, with increased activation of weakened muscles the major compensatory strategy. With muscle contracture, reduced activation of the plantarflexors was required across the mid-portion of stance suggesting a greater contribution from passive forces. Increased activation and force during swing was also required from the tibialis anterior to counteract the increased passive forces from the simulated dorsiflexor muscle contracture. Improvements in plantarflexor and dorsiflexor motor function and muscle strength, concomitant with reductions in plantarflexor muscle stiffness may target the deficits associated with SCP that limit normal gait

Effects of hip joint centre mislocation on gait kinematics of children with cerebral palsy calculated using patient-specific direct and inverse kinematic models

Joint kinematics can be calculated by Direct Kinematics (DK), which is used in most clinical gait laboratories, or Inverse Kinematics (IK), which is mainly used for musculoskeletal research. In both approaches, joint centre locations are required to compute joint angles. The hip joint centre (HJC) in DK models can be estimated using predictive or functional methods, while in IK models can be obtained by scaling generic models. The aim of the current study was to systematically investigate the impact of HJC location errors on lower limb joint kinematics of a clinical population using DK and IK approaches. Subject-specific kinematic models of eight children with cerebral palsy were built from magnetic resonance images and used as reference models. HJC was then perturbed in 6mm steps within a 60mm cubic grid, and kinematic waveforms were calculated for the reference and perturbed models. HJC perturbations affected only hip and knee joint kinematics in a DK framework, but all joint angles were affected when using IK. In the DK model, joint constraints increased the sensitivity of joint range-of-motion to HJC location errors. Mean joint angle offsets larger than 5° were observed for both approaches (DK and IK), which were larger than previously reported for healthy adults. In the absence of medical images to identify the HJC, predictive or functional methods with small errors in anterior-posterior and medial-lateral directions and scaling procedures minimizing HJC location errors in the anterior-posterior direction should be chosen to minimize the impact on joint kinematics

Muscle recruitment strategies can reduce joint loading during level walking

Joint inflammation, with consequent cartilage damage and pain, typically reduces functionality and affects activities of daily life in a variety of musculoskeletal diseases. Since mechanical loading is an important determinant of the disease process, a possible conservative treatment is the unloading of joints. In principle, a neuromuscular rehabilitation program aimed to promote alternative muscle recruitments could reduce the loads on the lower-limb joints during walking. The extent of joint load reduction one could expect from this approach remains unknown. Furthermore, assuming significant reductions of the load on the affected joint can be achieved, it is unclear whether, and to what extent, the other joints will be overloaded. Using subject-specific musculoskeletal models of four different participants, we computed the muscle recruitment strategies that minimised the hip, knee and ankle contact force, and predicted the contact forces such strategies induced at the other joints. Significant reductions of the peak force and impulse at the knee and hip were obtained, while only a minimal effect was found at the ankle joint. Adversely, the peak force and the impulse in non-targeted joints increased when aiming to minimize the load in an adjacent joint. These results confirm the potential of alternative muscle recruitment strategies to reduce the loading at the knee and the hip, but not at the ankle. Therefore, neuromuscular rehabilitation can be targeted to reduce the loading at affected joints but must be considered carefully in patients with multiple joints affected due to the potential adverse effects in non-targeted joints

Automatic generation of personalised skeletal models of the lower limb from three-dimensional bone geometries

The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken

Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: effect of differences between models

Total knee replacement (TKR) is one of the most performed orthopedic surgeries to treat knee joint diseases in the elderly population. Although the survivorship of knee implants may extend beyond two decades, the poor outcome rate remains considerable. A recent computational approach used to better understand failure modes and improve TKR outcomes is based on the combination of musculoskeletal (MSK) and finite element models. This combined multiscale modeling approach is a promising strategy in the field of computational biomechanics; however, some critical aspects need to be investigated. In particular, the identification and quantification of the uncertainties related to the boundary conditions used as inputs to the finite element model due to a different definition of the MSK model are crucial. Therefore, the aim of this study is to investigate this problem, which is relevant for the model credibility assessment process. Three different generic MSK models available in the OpenSim platform were used to simulate gait, based on the experimental data from the fifth edition of the “Grand Challenge Competitions to Predict in vivo Knee Loads.” The outputs of the MSK analyses were compared in terms of relative kinematics of the knee implant components and joint reaction (JR) forces and moments acting on the tibial insert. Additionally, the estimated knee JRs were compared with those measured by the instrumented knee implant so that the “global goodness of fit” was quantified for each model. Our results indicated that the different kinematic definitions of the knee joint and the muscle model implemented in the different MSK models influenced both the motion and the load history of the artificial joint. This study demonstrates the importance of examining the influence of the model assumptions on the output results and represents the first step for future studies that will investigate how the uncertainties in the MSK models propagate on disease-specific finite element model results