Sensitivity of subject-specific models to errors in musculo-skeletal geometry

A three-dimensional musculoskeletal model of the pelvis and lower limb of Australopithecus afarensis

OBJECTIVES

Musculoskeletal modeling is a powerful approach for studying the biomechanics and energetics of locomotion. Australopithecus (A.) afarensis is among the best represented fossil hominins and provides critical information about the evolution of musculoskeletal design and locomotion in the hominin lineage. Here, we develop and evaluate a three-dimensional (3-D) musculoskeletal model of the pelvis and lower limb of A. afarensis for predicting muscle-tendon moment arms and moment-generating capacities across lower limb joint positions encompassing a range of locomotor behaviors.

MATERIALS AND METHODS

A 3-D musculoskeletal model of an adult A. afarensis pelvis and lower limb was developed based primarily on the A.L. 288-1 partial skeleton. The model includes geometric representations of bones, joints and 35 muscle-tendon units represented using 43 Hill-type muscle models. Two muscle parameter datasets were created from human and chimpanzee sources. 3-D muscle-tendon moment arms and isometric joint moments were predicted over a wide range of joint positions.

RESULTS

Predicted muscle-tendon moment arms generally agreed with skeletal metrics, and corresponded with human and chimpanzee models. Human and chimpanzee-based muscle parameterizations were similar, with some differences in maximum isometric force-producing capabilities. The model is amenable to size scaling from A.L. 288-1 to the larger KSD-VP-1/1, which subsumes a wide range of size variation in A. afarensis.

DISCUSSION

This model represents an important tool for studying the integrated function of the neuromusculoskeletal systems in A. afarensis. It is similar to current human and chimpanzee models in musculoskeletal detail, and will permit direct, comparative 3-D simulation studies.

Intra and inter-rater variability in the construction of patient-specific musculoskeletal model

BACKGROUND

Variations observed in biomechanical studies might be attributed to errors made by operators during the construction of musculoskeletal models, rather than being solely attributed to patient-specific geometry.

RESEARCH QUESTION

What is the impact of operator errors on the construction of musculoskeletal models, and how does it affect the estimation of muscle moment arms and hip joint reaction forces?

METHODS

Thirteen independent operators participated in defining the muscle model, while a single operator performed 13 repetitions to define the muscle model based on 3D bone geometry. For each model, the muscle moment arms relative to the hip joint center of rotation was evaluated. Additionally, the hip joint reaction force during one-legged stance was assessed using static inverse optimization.

RESULTS

The results indicated high levels of consistency, as evidenced by the intra- rater and inter-rater agreement measured by the Intraclass Correlation Coefficient (ICC), which yielded values of 0.95 and 0.99, respectively. However, the estimated muscle moment arms exhibited an error of up to 16 mm compared to the reference musculoskeletal model. It was found that muscles attached to prominent anatomical landmarks were specified with greater accuracy than those attached over larger areas. Furthermore, the variability in estimated moment arms contributed to variations of up to 12% in the hip joint reaction forces.

SIGNIFICANCE

Both moment arm and muscle force demonstrated significantly lower variability when assessed by a single operator, suggesting the preference for employing a single operator in the creation of musculoskeletal models for clinical biomechanical studies.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

On the estimation of hip joint loads through musculoskeletal modeling

Noninvasive estimation of joint loads is still an open challenge in biomechanics. Although musculoskeletal modeling represents a solid resource, multiple improvements are still necessary to obtain accurate predictions of joint loads and to translate such potential into practical utility. The present study, focused on the hip joint, is aimed at reviewing the state-of-the-art literature on the estimation of hip joint reaction forces through musculoskeletal modeling. Our literature inspection, based on well-defined selection criteria, returned seventeen works, which were compared in terms of methods and results. Deviations between predicted and in vivo measured hip joint loads, taken from the OrthoLoad database, were assessed through quantitative deviation indices. Despite the numerous modeling and computational improvements made over the last two decades, predicted hip joint loads still deviate from their experimental counterparts and typically overestimate them. Several critical aspects have emerged that affect muscle force estimation, hence joint loads. Among them, the physical fidelity of the musculoskeletal model, with its parameters and geometry, plays a crucial role. Also, predicted joint loads are markedly affected by the selected muscle recruitment strategy, which reflects the underlying motor control policy. Practical guidelines for researchers interested in noninvasive estimation of hip joint loads are also provided.

A statistical shape model of the tibia-fibula complex: sexual dimorphism and effects of age on reconstruction accuracy from anatomical landmarks

A statistical shape model was created for a young adult population and used to predict tibia and fibula geometries from bony landmarks. Reconstruction errors with respect to CT data were quantified and compared to isometric scaling. Shape differences existed between sexes. The statistical shape model estimated tibia-fibula geometries from landmarks with high accuracy (RMSE = 1.51-1.62 mm), improving upon isometric scaling (RMSE = 1.78 mm). Reconstruction errors increased when the model was applied to older adults (RMSE = 2.11-2.17 mm). Improvements in geometric accuracy with shape model reconstruction changed hamstring moment arms 25-35% (1.0-1.3 mm) in young adults.

Subject-Specific Modeling of Femoral Torsion Influences the Prediction of Hip Loading During Gait in Asymptomatic Adults

Hip osteoarthritis may be caused by increased or abnormal intra-articular forces, which are known to be related to structural articular cartilage damage. Femoral torsional deformities have previously been correlated with hip pain and labral damage, and they may contribute to the onset of hip osteoarthritis by exacerbating the effects of existing pathoanatomies, such as cam and pincer morphologies. A comprehensive understanding of the influence of femoral morphotypes on hip joint loading requires subject-specific morphometric and biomechanical data on the movement characteristics of individuals exhibiting varying degrees of femoral torsion. The aim of this study was to evaluate hip kinematics and kinetics as well as muscle and joint loads during gait in a group of adult subjects presenting a heterogeneous range of femoral torsion by means of personalized musculoskeletal models. Thirty-seven healthy volunteers underwent a 3D gait analysis at a self-selected walking speed. Femoral torsion was evaluated with low-dosage biplanar radiography. The collected motion capture data were used as input for an inverse dynamics analysis. Personalized musculoskeletal models were created by including femoral geometries that matched each subject’s radiographically measured femoral torsion. Correlations between femoral torsion and hip kinematics and kinetics, hip contact forces (HCFs), and muscle forces were analyzed. Within the investigated cohort, higher femoral antetorsion led to significantly higher anteromedial HCFs during gait (medial during loaded stance phase and anterior during swing phase). Most of the loads during gait are transmitted through the anterior/superolateral quadrant of the acetabulum. Correlations with hip kinematics and muscle forces were also observed. Femoral antetorsion, through altered kinematic strategies and different muscle activations and forces, may therefore lead to altered joint mechanics and pose a risk for articular damage. The method proposed in this study, which accounts for both morphological and kinematic characteristics, might help in identifying in a clinical setting patients who, as a consequence of altered femoral torsional alignment, present more severe functional impairments and altered joint mechanics and are therefore at a higher risk for cartilage damage and early onset of hip osteoarthritis.

Development of An Anybody Musculoskeletal Model of The Thoroughbred Forelimb

Musculoskeletal injuries in horses are the main cause of retirement, rest, and death. To understand these injuries, it is necessary to study loads in muscles, tendons and ligaments. A musculoskeletal model makes it possible to consider all structures simultaneously and avoids invasive measurements. At present, most computational models of the equine limb described in the literature have been limited to the distal limb. The aim of this study was to create a preliminary musculoskeletal model of the whole equine forelimb and to run it with kinematic data collected during gait. The model was developed with the AnyBody Modelling System. It includes six limb segments, 11 muscle groups and 17 ligaments. Kinematic data were collected from the right forelimb of four Thoroughbreds at trot, right and left lead canter, and were then used in the model to compute sagittal plane joint excursions and ligament and tendon strains. The modelled joint excursions were in reasonable agreement with previous reports in the literature despite breed, gait and surface differences. Strain patterns of the tendons of the suspensory apparatus agreed with the literature, with maxima in mid-stance or at the end of stance. Strains in the distal palmar ligaments peaked in mid-stance, while strain in lacertus fibrosus peaked at the stance-swing transition. Tendon and ligament strains at canter were greatest when the measured forelimb was the trailing limb. Strain amplitudes varied against earlier models and these differences are discussed in relation to variations in methods, and especially in relation to attachment points of tendons and ligaments.

Biomechanical evaluation of total ankle arthroplasty. Part I: Joint loads during simulated level walking

In total ankle arthroplasty, the interaction at the joint between implant and bone is driven by a complex loading environment. Unfortunately, little is known about the loads at the ankle during daily activities since earlier attempts use two- or three-dimensional models to explore simplified joint mechanics. Our goal was to develop a framework to calculate multi-axial loads at the joint during simulated level walking following total ankle arthroplasty. To accomplish this, we combined robotic simulations of level walking at one-quarter bodyweight in three cadaveric foot and ankle specimens with musculoskeletal modeling to calculate the multi-axial forces and moments at the ankle during the stance phase. The peak compressive forces calculated were between 720 and 873 N occurring around 77%-80% of stance. The peak moment, which was the internal moment for all specimens, was between 6.1 and 11.6 N m and occurred between 72% and 88% of the stance phase. The peak moment did not necessarily occur with the peak force. The ankle joint loads calculated in this study correspond well to previous attempts in the literature; however, our robotic simulator and framework provide an opportunity to resolve the resultant three-dimensional forces and moments as others have not in previous studies. The framework may be useful to calculate ankle joint loads in cadaveric specimens as the first step in evaluating bone-implant interactions in total ankle replacement using specimen specific inputs. This approach also provides a unique opportunity to evaluate changes in joint loads and kinematics following surgical interventions of the foot and ankle.

Tibiofemoral helical axis of motion during the full gait cycle measured using biplane radiography

The helical axis of motion (HAM), which describes the simultaneous multiplanar translations and rotations that occur within a joint, has been proposed as a single measure to characterize dynamic joint function. The objective of this study was to determine the tibiofemoral HAM during 5 discrete phases of gait. Thirty-nine knees from 20 healthy adults were imaged using high-speed biplane radiography during treadmill walking. The primary outcome measures were the intersection of the HAM with the sagittal plane of the femur, and the direction of the HAM. The intersection point translated an average of 12.7 ± 5.5% of femur condyle depth in the anterior-posterior direction and 28.6 ± 13.3% of femur condyle height in the proximal-distal direction during gait. The anterior/posterior and proximal/distal components of the HAM vector were greater during stance (5.6°±3.8° and 11.1°±5.0°, respectively) than during swing (2.0°±1.1° and 6.4°±3.8°, respectively) (p<0.001) reflecting greater coupled rotations during stance. No significant side-to-side differences in intersection point location or HAM orientation were found during any of the 5 phases of gait (max difference 4.1 ± 3.4% of femur condyle depth and 13.1 ± 16.7% of femur condyle height; 12.7°±12.3° proximal/distal and 4.2°±4.5° anterior/posterior direction). Loading significantly affected HAM location and orientation (p<0.001). Knowledge of healthy knee HAM and typical side-to-side differences during gait can serve as a baseline for evaluating knee motion after clinical interventions.

Soft tissue artifact causes underestimation of hip joint kinematics and kinetics in a rigid-body musculoskeletal model

Rigid body musculoskeletal models have been applied to study kinematics, moments, muscle forces, and joint reaction forces in the hip. Most often, models are driven with segment motions calculated through optical tracking of markers adhered to the skin. One limitation of optical tracking is soft tissue artifact (STA), which occurs due to motion of the skin surface relative to the underlying skeleton. The purpose of this study was to quantify differences in musculoskeletal model outputs when tracking body segment positions with skin markers as compared to bony landmarks measured by direct imaging of bone motion with dual fluoroscopy (DF). Eleven asymptomatic participants with normally developed hip anatomy were imaged with DF during level treadmill walking at a self-selected speed. Hip joint kinematics and kinetics were generated using inverse kinematics, inverse dynamics, static optimization and joint reaction force analysis. The effect of STA was assessed by comparing the difference in estimates from simulations based on skin marker positions (SM) versus virtual markers on bony landmarks from DF. While patterns were similar, STA caused underestimation of kinematics, range of motion (ROM), moments, and reaction forces at the hip, including flexion-extension ROM, maximum internal rotation joint moment and peak joint reaction force magnitude. Still, kinetic differences were relatively small, and thus they may not be relevant nor clinically meaningful.

Influence of glenohumeral joint muscle insertion on moment arms using a finite element model

Accurate muscle geometry is essential to estimate moment arms in musculoskeletal models. Given the complex interactions between shoulder structures, we hypothesized that finite element (FE) modelling is suitable to obtain physiological muscle trajectory. A FE glenohumeral joint model was developed based on medical imaging. Moment arms were computed and compared to literature and MRI-based estimation. Our FE model produces moment arms consistent with the literature and with MRI data (max 17 mm differences). The inferior and superior fibres of a same muscle can have opposite action; predictions of moment arms are sensitive to muscle insertion (up to 20 mm variation).

Development and Evaluation of a Subject-Specific Lower Limb Model With an Eleven-Degrees-of-Freedom Natural Knee Model Using Magnetic Resonance and Biplanar X-Ray Imaging During a Quasi-Static Lunge

Musculoskeletal (MS) models can be used to study the muscle, ligament, and joint mechanics of natural knees. However, models that both capture subject-specific geometry and contain a detailed joint model do not currently exist. This study aims to first develop magnetic resonance image (MRI)-based subject-specific models with a detailed natural knee joint capable of simultaneously estimating in vivo ligament, muscle, tibiofemoral (TF), and patellofemoral (PF) joint contact forces and secondary joint kinematics. Then, to evaluate the models, the predicted secondary joint kinematics were compared to in vivo joint kinematics extracted from biplanar X-ray images (acquired using slot scanning technology) during a quasi-static lunge. To construct the models, bone, ligament, and cartilage structures were segmented from MRI scans of four subjects. The models were then used to simulate lunges based on motion capture and force place data. Accurate estimates of TF secondary joint kinematics and PF translations were found: translations were predicted with a mean difference (MD) and standard error (SE) of 2.13 ± 0.22 mm between all trials and measures, while rotations had a MD ± SE of 8.57 ± 0.63 deg. Ligament and contact forces were also reported. The presented modeling workflow and the resulting knee joint model have potential to aid in the understanding of subject-specific biomechanics and simulating the effects of surgical treatment and/or external devices on functional knee mechanics on an individual level.

Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge

Purpose

Modern statistics and higher computational power have opened novel possibilities to complex data analysis. While gait has been the utmost described motion in quantitative human motion analysis, descriptions of more challenging movements like the squat or lunge are currently lacking in the literature. The hip and knee joints are exposed to high forces and cause high morbidity and costs. Pre-surgical kinetic data acquisition on a patient-specific anatomy is also scarce in the literature. Studying the normal inter-patient kinetic variability may lead to other comparable studies to initiate more personalized therapies within the orthopedics.

Methods

Trials are performed by 50 healthy young males who were not overweight and approximately of the same age and activity level. Spatial marker trajectories and ground reaction force registrations are imported into the Anybody Modeling System based on subject-specific geometry and the state-of-the-art TLEM 2.0 dataset. Hip and knee joint reaction forces were obtained by a simulation with an inverse dynamics approach. With these forces, a statistical model that accounts for inter-subject variability was created. For this, we applied a principal component analysis in order to enable variance decomposition. This way, noise can be rejected and we still contemplate all waveform data, instead of using deduced spatiotemporal parameters like peak flexion or stride length as done in many gait analyses. In addition, this current paper is, to the authors’ knowledge, the first to investigate the generalization of a kinetic model data toward the population.

Results

Average knee reaction forces range up to 7.16 times body weight for the forwarded leg during lunge. Conversely, during squat, the load is evenly distributed. For both motions, a reliable and compact statistical model was created. In the lunge model, the first 12 modes accounts for 95.26% of inter-individual population variance. For the maximal-depth squat, this was 95.69% for the first 14 modes. Model accuracies will increase when including more principal components.

Conclusion

Our model design was proved to be compact, accurate, and reliable. For models aimed at populations covering descriptive studies, the sample size must be at least 50.

Influence of musculotendon geometry variability in muscle forces and hip bone-on-bone forces during walking

Inverse dynamics problems are usually solved in the analysis of human gait to obtain reaction forces and moments at the joints. However, these actions are not the actual forces and moments supported by the joint structure, because they do not consider the forces of the muscles acting across the joint. Therefore, to analyse bone-on bone forces it is necessary to estimate those muscle forces. Usually, this problem is addressed by means of optimization algorithms. One of the parameters required to solve this problem is the musculotendon geometry. These data are usually taken from cadavers or MRI data from several subjects, different from the analysed subject. Then, the model is scaled to the subject morphology. This procedure constitutes a source of error. The goals of this work were two. First, to perform a sensitivity analysis of the influence of muscle insertion locations on the muscle forces acting on the hip joint and on the hip joint bone-on-bone forces. Second, to compare the hip joint bone-on-bone forces during gait cycle obtained through muscle insertion locations taken from a musculoskeletal model template and a scaling procedure to those obtained from a subject-specific model using an MRI of the subject. The problem was solved using OpenSim. Results showed that anatomical variability should be analysed from two perspectives. One the one hand, throughout the gait cycle, in a global way. On the other hand, at a characteristic instant of the gait cycle. Variations of ±1 cm in the position of the attachment points of certain muscles caused variations of up to 14.21% in averaged deviation of the muscle forces and 58.96% in the peak force in the modified muscle and variations up to 57.23% in the averaged deviation of the muscle force and up to 117.23% in the peak force in the rest of muscles. Then, the influence of that variability on muscle activity patterns and hip bone-on-bone forces could be described more precisely. A biomechanical analysis of a subject-specific musculoskeletal model was carried out. Using MRI data, variations up to 5 cm in the location of the insertion points were introduced. These modifications showed significant differences between the baseline model and the customized model: within the range [-12%, 10%] for muscle forces and around 35% of body weight for hip bone-on-bone forces.

Individual Differences in Women During Walking Affect Tibial Response to Load Carriage: The Importance of Individualized Musculoskeletal Finite-Element Models

Subject-specific features can contribute to the susceptibility of an individual to stress fracture. Here, we incorporated tibial morphology and material properties into a standard musculoskeletal finite-element (M/FE) model and investigated how load carriage influences joint kinetics and tibial mechanics in women. We obtained the morphology and material properties of the tibia from computed tomography images for women of three distinctly different heights, 1.51 m (short), 1.63 m (medium), and 1.75 m (tall), and developed individualized M/FE models for each. Then, we calculated joint and muscle forces, and subsequently, tibial stress/strain for each woman walking at 1.3 m/s under various load conditions (0, 11.3, or 22.7 kg). Among the subjects investigated, using individualized and standard M/FE models, the joint reaction forces (JRFs) differed by up to 4 (hip), 22 (knee), and 26% (ankle), and the 90th percentile von Mises stress by up to 30% (tall woman). Load carriage evoked distinct biomechanical responses, with a 22.7-kg load decreasing the peak hip JRF during late stance by ∼18% in the short woman, while increasing it by ∼39% in the other two women. It also increased peak knee and ankle JRFs by up to ∼48 (tall woman) and ∼36% (short woman). The same load increased the 90th percentile von Mises stress (and corresponding cumulative stress) by 31 (28), 22 (30), and 27% (32%) in the short, medium, and tall woman, respectively. Our findings highlight the critical role of individualized M/FE models to assess mechanical loading in different individuals performing the same physical activity.

A screening method to analyse the sensitivity of a lower limb multibody kinematic model

The study presents a screening method used to identify the influential parameters of a lower limb model including ligaments, at low numerical cost. Concerning multibody kinematics optimisation, the ligament parameters (isometric length) were found the most influential ones in a previous study. The screening method tested if they remain influential with minimised length variations. The most important parameters for tibiofemoral kinematics were the skin markers, segment lengths and joint parameters, including two ligaments. This was confirmed by a quantitative sensitivity analysis. The screening method has the potential to be used as a stand-alone procedure for a sensitivity analysis.

Refining muscle geometry and wrapping in the TLEM 2 model for improved hip contact force prediction

Musculoskeletal models represent a powerful tool to gain knowledge on the internal forces acting at the joint level in a non-invasive way. However, these models can present some errors associated with the level of detail in their geometrical representation. For this reason, a thorough validation is necessary to prove the reliability of their predictions. This study documents the development of a generic musculoskeletal model and proposes a working logic and simulation techniques for identifying specific model features in need of refinement; as well as providing a quantitative validation for the prediction of hip contact forces (HCF). The model, implemented in the AnyBody Modeling System and based on the cadaveric dataset TLEM 2.0, was scaled to match the anthropometry of a patient fitted with an instrumented hip implant and to reproduce gait kinematics based on motion capture data. The relative contribution of individual muscle elements to the HCF and joint moments was analyzed to identify critical geometries, which were then compared to muscle magnetic resonance imaging (MRI) scans and, in case of inconsistencies, were modified to better match the volumetric scans. The predicted HCF showed good agreement with the overall trend and timing of the measured HCF from the instrumented prosthesis. The average root mean square error (RMSE), calculated for the total HCF was found to be 0.298*BW. Refining the geometries of the muscles thus identified reduced RMSE on HCF magnitudes by 17% (from 0.359*BW to 0.298*BW) over the whole gait cycle. The detailed study of individual muscle contributions to the HCF succeeded in identifying muscles with incorrect anatomy, which would have been difficult to intuitively identify otherwise. Despite a certain residual over-prediction of the final hip contact forces in the stance phase, a satisfactory level of geometrical accuracy of muscle paths has been achieved with the refinement of this model.

How sensitive are predicted muscle and knee contact forces to normalization factors and polynomial order in the muscle recruitment criterion formulation?

Musculoskeletal modeling is an important tool to estimate knee loads. In these models, anatomical muscles are frequently sub-divided to account for wide origin/insertion areas. The specific sub-division has been shown to affect some muscle recruitment criteria and it has been suggested that normalization factors should be incorporated into models. The primary aim of this study was to investigate the effect of different muscle normalization factors in the muscle recruitment criterion and polynomial order on the estimated muscle and total, medial and lateral knee contact forces during gait. These were evaluated on three different musculoskeletal models with increasing levels of patient-specificity and knee joint model complexity for one subject from the Grand Challenge data set and evaluated against measured forces. The results showed that the introduction of the muscle normalization factors affected the estimated forces and that this effect was most pronounced when a polynomial of order two was applied. Additionally, mainly the second contact force peak was affected. Secondary investigations revealed that the predicted forces can vary substantially as a function of the knee flexor and extensor muscle strength with over one body weight difference in predicted total compressive force between 100% and 40% of the strength. Additionally, the predicted second peak during gait was found to be sensitive to the position of the pelvic skin marker positions in the model. These results imply that caution should be taken when a normalization factor is introduced to account for sub-divided muscles especially for second-order recruitment criteria.

Sensitivity analysis of the estimated muscle forces during gait with respect to the musculoskeletal model parameters and dynamic simulation techniques

The purpose of the current study was to investigate the robustness of dynamic simulation results in the presence of uncertainties resulting from application of a scaled-generic musculoskeletal model instead of a subject-specific model as well as the effect of the choice of simulation method on the obtained muscle forces. The performed sensitivity analysis consisted of the following multibody parameter modifications: maximum isometric muscle forces, number of muscles, the hip joint centre location, segment masses as well as different dynamic simulation methods, namely static optimization with three different criteria and a computed muscle control algorithm (hybrid approach combining forward and inverse dynamics). Twenty-four different models and fifty-five resultant dynamic simulation data sets were analysed. The effects of model perturbation on the magnitude and profile of muscle forces were compared. It has been shown that estimated muscle forces are very sensitive to model parameters. The greatest impact was observed in the case of the force magnitude of the muscles generating high forces during gait (regardless of the modification introduced). However, the force profiles of those muscles were preserved. Relatively large differences in muscle forces were observed for different simulation techniques, which included both magnitude and profile of muscle forces. Personalization of model parameters would affect the resultant muscle forces and seems to be necessary to improve general accuracy of the estimated parameters. However, personalization alone will not ensure high accuracy due to the still unresolved muscle force sharing problem.

Sensitivity of a juvenile subject-specific musculoskeletal model of the ankle joint to the variability of operator-dependent input

Subject-specific musculoskeletal modelling is especially useful in the study of juvenile and pathological subjects. However, such methodologies typically require a human operator to identify key landmarks from medical imaging data and are thus affected by unavoidable variability in the parameters defined and subsequent model predictions. The aim of this study was to thus quantify the inter- and intra-operator repeatability of a subject-specific modelling methodology developed for the analysis of subjects with juvenile idiopathic arthritis. Three operators each created subject-specific musculoskeletal foot and ankle models via palpation of bony landmarks, adjustment of geometrical muscle points and definition of joint coordinate systems. These models were then fused to a generic Arnold lower limb model for each of three modelled patients. The repeatability of each modelling operation was found to be comparable to those previously reported for the modelling of healthy, adult subjects. However, the inter-operator repeatability of muscle point definition was significantly greater than intra-operator repeatability (p < 0.05) and predicted ankle joint contact forces ranged by up to 24% and 10% of the peak force for the inter- and intra-operator analyses, respectively. Similarly, the maximum inter- and intra-operator variations in muscle force output were 64% and 23% of peak force, respectively. Our results suggest that subject-specific modelling is operator dependent at the foot and ankle, with the definition of muscle geometry the most significant source of output uncertainty. The development of automated procedures to prevent the misplacement of crucial muscle points should therefore be considered a particular priority for those developing subject-specific models.

Subject-specific shoulder muscle attachment region prediction using statistical shape models: A validity study

Subject-specific musculoskeletal models can predict accurate joint and muscle biomechanics thereby helping clinicians and surgeons. Current modeling strategies do not incorporate accurate subject-specific muscle parameters. This study reports a statistical shape model (SSM) based method to predict subject-specific muscle attachment regions on shoulder bones and illustrates the concurrent validity of the predictions. Augmented SSMs of scapula and humerus bones were built using bone meshes and five muscle attachment (origin/insertion) regions which play important role in the shoulder motion and function. Muscle attachments included Subscapularis, Supraspinatus, Infraspinatus, Teres Major and Teres Minor on both the bones. The regions were represented by subset of vertices on the bone meshes and were tracked using vertex identifiers. Subject-specific muscle attachment regions were predicted using external set of bones not used in building the SSMs. Validity of predictions was determined by visual inspection and also by using four similarity measures between predicted and manually segmented regions. Excellent concurrent validity was found indicating the higher accuracy of predictions. This method can be effectively employed in modeling pipelines or in automatic segmentation of medical images. Further validations are warranted on all the muscles of the shoulder complex.

Development of a biomechanical model of the wrist joint for patient-specific model guided surgical therapy planning: Part 1

An enhanced musculoskeletal biomechanical model of the wrist joint is presented in this article. The developed computational model features the two forearm bones radius and ulna, the eight wrist bones, the five metacarpal bones, and a soft tissue apparatus. Validation of the model was based on information taken from the literature as well as own experimental passive in vitro motion analysis of eight cadaver specimens. The computational model is based on the multi-body simulation software AnyBody. A comprehensive ligamentous apparatus was implemented allowing the investigation of ligament function. The model can easily patient specific personalized on the basis of image information. The model enables simulation of individual wrist motion and predicts trends correctly in the case of changing kinematics. Therefore, patient-specific multi-body simulation models are potentially valuable tools for surgeons in pre- and intraoperative planning of implant placement and orientation.

Prediction of In Vivo Knee Joint Loads Using a Global Probabilistic Analysis

Musculoskeletal models are powerful tools that allow biomechanical investigations and predictions of muscle forces not accessible with experiments. A core challenge modelers must confront is validation. Measurements of muscle activity and joint loading are used for qualitative and indirect validation of muscle force predictions. Subject-specific models have reached high levels of complexity and can predict contact loads with surprising accuracy. However, every deterministic musculoskeletal model contains an intrinsic uncertainty due to the high number of parameters not identifiable in vivo. The objective of this work is to test the impact of intrinsic uncertainty in a scaled-generic model on estimates of muscle and joint loads. Uncertainties in marker placement, limb coronal alignment, body segment parameters, Hill-type muscle parameters, and muscle geometry were modeled with a global probabilistic approach (multiple uncertainties included in a single analysis). 5-95% confidence bounds and input/output sensitivities of predicted knee compressive loads and varus/valgus contact moments were estimated for a gait activity of three subjects with telemetric knee implants from the "Grand Challenge Competition." Compressive load predicted for the three subjects showed confidence bounds of 333 ± 248 N, 408 ± 333 N, and 379 ± 244 N when all the sources of uncertainty were included. The measured loads lay inside the predicted 5-95% confidence bounds for 77%, 83%, and 76% of the stance phase. Muscle maximum isometric force, muscle geometry, and marker placement uncertainty most impacted the joint load results. This study demonstrated that identification of these parameters is crucial when subject-specific models are developed.

Subject-specific musculoskeletal loading of the tibia: Computational load estimation

The systematic development of subject-specific computer models for the analysis of personalized treatments is currently a reality. In fact, many advances have recently been developed for creating virtual finite element-based models. These models accurately recreate subject-specific geometries and material properties from recent techniques based on quantitative image analysis. However, to determine the subject-specific forces, we need a full gait analysis, typically in combination with an inverse dynamics simulation study. In this work, we aim to determine the subject-specific forces from the computer tomography images used to evaluate bone density. In fact, we propose a methodology that combines these images with bone remodelling simulations and artificial neural networks. To test the capability of this novel technique, we quantify the personalized forces for five subject-specific tibias using our technique and a gait analysis. We compare both results, finding that similar vertical loads are estimated by both methods and that the dominant part of the load can be reliably computed. Therefore, we can conclude that the numerical-based technique proposed in this work has great potential for estimating the main forces that define the mechanical behaviour of subject-specific bone.

Muscle Activity during Walking Measured Using 3D MRI Segmentations and [18F]-Fluorodeoxyglucose in Combination with Positron Emission Tomography

PURPOSE

This study aimed to determine the contribution of each muscle of the lower limb to walking using positron emission tomography (PET) with [F]-fluorodeoxyglucose (FDG). Furthermore, we compared our results obtained using volumetric analysis of entire muscles with those obtained using a more traditional approach considering the uptake in only one slice in each segment.

METHODS

Ten healthy subjects walked on a treadmill at self-selected comfortable walking speed for 90 min, 60 min before and 30 min after intravenous injection of 50-MBq FDG. A PET/computerized tomography scan of the lower limb was made subsequently. The three-dimensional contours of 39 muscles in the left lower limb were semiautomatically determined from magnetic resonance imaging scans. After nonrigidly registering the magnetic resonance imaging to the computerized tomography scans, we superimposed the muscle contours on the PET scans.

RESULTS

The muscles with the highest median FDG uptake among all subjects were the soleus, gluteus maximus, vastus lateralis, gastrocnemius medialis, and adductor magnus. We found a wide range of FDG uptake values among subjects, including in some of the most important muscles involved in walking (e.g., soleus, gluteus medius, gastrocnemius medialis). Compared with the volumetric analysis, the single slice analysis did not yield an accurate estimate of the FDG uptake in many of the most active muscles, including the gluteus medius and minimus (overestimated) as well as all the thigh muscles (underestimated).

CONCLUSIONS

The distribution of FDG among the muscles varied between subjects, suggesting that each subject had a unique activation pattern. The FDG uptake as estimated from single slices did not correspond well to the uptake obtained from volumetric analysis, which illustrates the added value of our novel three-dimensional image analysis techniques.

ASSESSMENT OF PARAMETER UNCERTAINTY IN RIGID MUSCULOSKELETAL SIMULATION USING A PROBABILISTIC APPROACH

Experimental investigation coupled with numerical simulations is commonly used for solving multi-physical problems. In the field of biomechanics, in which the aim is to understand the mechanics of living system, the main difficulties are to provide experimental data reflecting the multi-physical behavior of the system of interest. These experimental data are used as input data for numerical simulations to quantify output responses through physical and/or biological laws expressed by constitutive mathematical equations. However, uncertainties on the experimentally available data exist from factors such as human variability and differences in protocols parameters and techniques. Thus, the true values of these data could never be experimentally measured. The objective of this study was to develop a modeling workflow to assess and account for the parameter uncertainty in rigid musculoskeletal simulation. A generic musculoskeletal model was used. Data uncertainties of the right thigh mass, physiological cross-sectional area (pCSA) and muscle tension coefficient of the rectus femoris were accounted to estimate their effect on the joint moment and muscle force computing, respectively. A guideline was developed to fuse data from multiple sources into a sample variation space leading to establish input data distribution. Uncertainty propagation was performed using Monte Carlo and most probable point methods. A high degree of sensitivity of 0.98 was noted for the effect of thigh mass uncertainty on the hip joint moment using inverse dynamics method. A strong deviation of rectus femoris muscle force (around 260 N) was found under effect of pCSA and muscle tension coefficient on the force estimation using static optimization method. Accounting parameter uncertainty into rigid musculoskeletal simulation plays an essential role in the evaluation of the confidence in the model outputs. Thus, simulation outcome may be computed and represented in a more reliable manner with a global range of plausible values.

A Novel Approach for Dynamic Testing of Total Hip Dislocation under Physiological Conditions

Constant high rates of dislocation-related complications of total hip replacements (THRs) show that contributing factors like implant position and design, soft tissue condition and dynamics of physiological motions have not yet been fully understood. As in vivo measurements of excessive motions are not possible due to ethical objections, a comprehensive approach is proposed which is capable of testing THR stability under dynamic, reproducible and physiological conditions. The approach is based on a hardware-in-the-loop (HiL) simulation where a robotic physical setup interacts with a computational musculoskeletal model based on inverse dynamics. A major objective of this work was the validation of the HiL test system against in vivo data derived from patients with instrumented THRs. Moreover, the impact of certain test conditions, such as joint lubrication, implant position, load level in terms of body mass and removal of muscle structures, was evaluated within several HiL simulations. The outcomes for a normal sitting down and standing up maneuver revealed good agreement in trend and magnitude compared with in vivo measured hip joint forces. For a deep maneuver with femoral adduction, lubrication was shown to cause less friction torques than under dry conditions. Similarly, it could be demonstrated that less cup anteversion and inclination lead to earlier impingement in flexion motion including pelvic tilt for selected combinations of cup and stem positions. Reducing body mass did not influence impingement-free range of motion and dislocation behavior; however, higher resisting torques were observed under higher loads. Muscle removal emulating a posterior surgical approach indicated alterations in THR loading and the instability process in contrast to a reference case with intact musculature. Based on the presented data, it can be concluded that the HiL test system is able to reproduce comparable joint dynamics as present in THR patients.

A Patient-Specific Foot Model for the Estimate of Ankle Joint Forces in Patients with Juvenile Idiopathic Arthritis

Juvenile idiopathic arthritis (JIA) is the leading cause of childhood disability from a musculoskeletal disorder. It generally affects large joints such as the knee and the ankle, often causing structural damage. Different factors contribute to the damage onset, including altered joint loading and other mechanical factors, associated with pain and inflammation. The prediction of patients’ joint loading can hence be a valuable tool in understanding the disease mechanisms involved in structural damage progression. A number of lower-limb musculoskeletal models have been proposed to analyse the hip and knee joints, but juvenile models of the foot are still lacking. This paper presents a modelling pipeline that allows the creation of juvenile patient-specific models starting from lower limb kinematics and foot and ankle MRI data. This pipeline has been applied to data from three children with JIA and the importance of patient-specific parameters and modelling assumptions has been tested in a sensitivity analysis focused on the variation of the joint reaction forces. This analysis highlighted the criticality of patient-specific definition of the ankle joint axes and location of the Achilles tendon insertions. Patient-specific detection of the Tibialis Anterior, Tibialis Posterior, and Peroneus Longus origins and insertions were also shown to be important.

Unilateral total hip replacement patients with symptomatic leg length inequality have abnormal hip biomechanics during walking

BACKGROUND

Symptomatic leg length inequality accounts for 8.7% of total hip replacement related claims made against the UK National Health Service Litigation authority. It has not been established whether symptomatic leg length inequality patients following total hip replacement have abnormal hip kinetics during gait.

METHODS

Hip kinetics in 15 unilateral total hip replacement patients with symptomatic leg length inequality during gait was determined through multibody dynamics and compared to 15 native hip healthy controls and 15 'successful' asymptomatic unilateral total hip replacement patients.

FINDING

More significant differences from normal were found in symptomatic leg length inequality patients than in asymptomatic total hip replacement patients. The leg length inequality patients had altered functions defined by lower gait velocity, reduced stride length, reduced ground reaction force, decreased hip range of motion, reduced hip moment and less dynamic hip force with a 24% lower heel-strike peak, 66% higher mid-stance trough and 37% lower toe-off peak. Greater asymmetry in hip contact force was also observed in leg length inequality patients.

INTERPRETATION

These gait adaptions may affect the function of the implant and other healthy joints in symptomatic leg length inequality patients. This study provides important information for the musculoskeletal function and rehabilitation of symptomatic leg length inequality patients.

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.

Hip contact forces in asymptomatic total hip replacement patients differ from normal healthy individuals: Implications for preclinical testing

BACKGROUND

Preclinical durability testing of hip replacement implants is standardised by ISO-14242-1 (2002) which is based on historical inverse dynamics analysis using data obtained from a small sample of normal healthy individuals. It has not been established whether loading cycles derived from normal healthy individuals are representative of loading cycles occurring in patients following total hip replacement.

METHODS

Hip joint kinematics and hip contact forces derived from multibody modelling of forces during normal walking were obtained for 15 asymptomatic total hip replacement patients and compared to 38 normal healthy individuals and to the ISO standard for pre-clinical testing.

FINDINGS

Hip kinematics in the total hip replacement patients were comparable to the ISO data and the hip contact force in the normal healthy group was also comparable to the ISO cycles. Hip contact forces derived from the asymptomatic total hip replacement patients were comparable for the first part of the stance period but exhibited 30% lower peak loads at toe-off.

INTERPRETATION

Although the ISO standard provides a representative kinematic cycle, the findings call into question whether the hip joint contact forces in the ISO standard are representative of those occurring in the joint following total hip replacement.

Transformation methods for estimation of subject-specific scapular muscle attachment sites

The parameters that describe the soft tissue structures are among the most important anatomical parameters for subject-specific biomechanical modelling. In this paper, we study one of the soft tissue parameters, namely muscle attachment sites. Two new methods are proposed for transformation of the muscle attachment sites of any reference scapula to any destination scapula based on four palpable bony landmarks. The proposed methods as well as one previously proposed method have been applied for transformation of muscle attachment sites of one reference scapula to seven other scapulae. The transformation errors are compared among the three methods. Both proposed methods yield significantly less (p < 0.05) prediction error as compared to the currently available method. Furthermore, we investigate whether there exists a reference scapula that performs significantly better than other scapulae when used for transformation of muscle attachment sites. Seven different scapulae were used as reference scapula and their resulting transformation errors were compared with each other. In the considered statistical population, no such a thing as an ideal scapula was found. There was, however, one outlier scapula that performed significantly worse than the other scapulae when used as a reference. The effect of perturbations in both muscle attachment sites and other muscle properties is studied by comparing muscle force predictions of a musculoskeletal model between perturbed and non-perturbed versions of the model. It is found that 10 mm variations in muscle attachments have more significant effect on muscle force predictions than 10% variations in any of the other four analysed muscle properties.