Alterations of musculoskeletal models for a more accurate estimation of lower limb joint contact forces during normal gait: A systematic review

Musculoskeletal modeling and movement simulation for structural hip disorder research: A scoping review of methods, validation, and applications

Musculoskeletal modeling is a powerful tool to quantify biomechanical factors typically not feasible to measure in vivo, such as hip contact forces and deep muscle activations. While technological advancements in musculoskeletal modeling have increased accessibility, selecting the appropriate modeling approach for a specific research question, particularly when investigating pathological populations, has become more challenging. The purposes of this review were to summarize current modeling and simulation methods in structural hip disorder research, as well as evaluate model validation and study reproducibility. MEDLINE and Web of Science were searched to identify literature relating to the use of musculoskeletal models to investigate structural hip disorders (i.e., involving a bony abnormality of the pelvis, femur, or both). Forty-seven articles were included for analysis, which either compared multiple modeling methods or applied a single modeling workflow to answer a research question. Findings from studies comparing methods were summarized, such as the effect of generic versus patient-specific modeling techniques on model-estimated hip contact forces or muscle forces. The review also discussed limitations in validation practices, as only 11 of the included studies conducted a validation and used qualitative approaches only. Given the lack of information related to model validation, additional details regarding the development and validation of generic models were retrieved from references and modeling software documentation. To address the wide variability and under-reporting of data collection, data processing, and modeling methods highlighted in this review, we developed a template that researchers can complete and include as a table within the methodology section of their manuscripts. The use of this table will help increase transparency and reporting of essential details related to reproducibility and methods without being limited by word count restrictions. Overall, this review provides a comprehensive synthesis of modeling approaches that can help researchers make modeling decisions and evaluate existing literature.

Clinical and preclinical evidence on the bioeffects and movement-related implications of photobiomodulation in the orthodontic tooth movement: A systematic review

Photobiomodulation (PBM) has been demonstrated as a non-invasive and painless technique with great potential to accelerate orthodontic tooth movement (OTM). However, there is a great inconsistency among PBM protocols and reported outcomes, probably due to the poor translatability of preclinical knowledge into early clinical practice. Hence, this review aims to fill this gap by establishing the state-of-the-art on both preclinical and clinical applications of PBM, and by comprehensively discussing the most suitable stimulation protocols described in the literature. This review was conducted according to PRISMA guidelines. A bibliographic search was carried out in the PubMed, Scopus and Cochrane databases using a combination of keywords. Only studies written in English were eligible and no time limit was applied. A total of 69 studies were selected for this review. The revised literature describes that PBM can effectively reduce orthodontic treatment time and produce analgesic and anti-inflammatory effects. We found that PBM of 640 ± 25, 830 ± 20 and 960 ± 20 nm, delivered at a minimum energy density per irradiation point of 5 J/cm2 daily or every other day sessions is robustly associated with increased tooth movement rate. Pain relief seems to be achieved with lower irradiation doses compared to those required for OTM acceleration. For the first time, the bioeffects induced by PBM for the acceleration of OTM are comprehensively discussed from a translational point of view. Collectively, the evidence from preclinical and clinical trials supports the use of PBM as a coadjuvant in orthodontics for enhancing tooth movement and managing treatment-associated discomfort. Overall, the revised studies indicate that optimal PBM parameters to stimulate tissue remodelling are wavelengths of 830 ± 20 nm and energy densities of 5-70 J/cm2 applied daily or every other day can maximize the OTM rate, while lower doses (up to 16 J/cm2 per session) delivered in non-consecutive days seem to be optimal for inducing analgesic effects. Future research should focus on optimizing laser parameters and treatment protocols customized for tooth and movement type. By fine-tuning laser parameters, clinicians can potentially reduce treatment times, improve patient comfort and achieve more predictable outcomes, making orthodontic care more efficient and patient-friendly, thus consolidating PBM usage in orthodontics.

The Biomechanics of Musculoskeletal Tissues during Activities of Daily Living: Dynamic Assessment Using Quantitative Transmission-Mode Ultrasound Techniques

The measurement of musculoskeletal tissue properties and loading patterns during physical activity is important for understanding the adaptation mechanisms of tissues such as bone, tendon, and muscle tissues, particularly with injury and repair. Although the properties and loading of these connective tissues have been quantified using direct measurement techniques, these methods are highly invasive and often prevent or interfere with normal activity patterns. Indirect biomechanical methods, such as estimates based on electromyography, ultrasound, and inverse dynamics, are used more widely but are known to yield different parameter values than direct measurements. Through a series of literature searches of electronic databases, including Pubmed, Embase, Web of Science, and IEEE Explore, this paper reviews current methods used for the in vivo measurement of human musculoskeletal tissue and describes the operating principals, application, and emerging research findings gained from the use of quantitative transmission-mode ultrasound measurement techniques to non-invasively characterize human bone, tendon, and muscle properties at rest and during activities of daily living. In contrast to standard ultrasound imaging approaches, these techniques assess the interaction between ultrasound compression waves and connective tissues to provide quantifiable parameters associated with the structure, instantaneous elastic modulus, and density of tissues. By taking advantage of the physical relationship between the axial velocity of ultrasound compression waves and the instantaneous modulus of the propagation material, these techniques can also be used to estimate the in vivo loading environment of relatively superficial soft connective tissues during sports and activities of daily living. This paper highlights key findings from clinical studies in which quantitative transmission-mode ultrasound has been used to measure the properties and loading of bone, tendon, and muscle tissue during common physical activities in healthy and pathological populations.

Impact of model geometry and joint center locations on inverse kinematic/dynamic predictions: A comparative study of sexually dimorphic models

This work illustrates the sensitivity of demographically characteristic body segment inertial properties and subject-specific customization on model performance. One characteristic demographic, gender, and one subject-specific characteristic, hip joint center location, were represented with musculoskeletal modeling to evaluate how design decisions may alter model outputs. Generic sexually dimorphic musculoskeletal models were developed from the commonly used Rajagopal model using male and female data adapted by Dumas et al. Hip joint centers of these models were adjusted based on functional joint center testing. The kinematics and dynamics of 40 gait cycles from four subjects are predicted using these models. Two-way analysis of variance (ANOVA) was performed on the continuous time series data using statistical parametric mapping (SPM) to assess changes in kinematics/dynamics due to either choice in model (Rajagopal vs Dumas) or whether joint center adjustment was performed. The SPM based two-way ANOVA of the inverse dynamics found that differences in the Rajagopal and Dumas models resulted in significant differences in sagittal plane moments during swing (0.115 ± 0.032 Nm/kg difference in mean hip flexion moment during initial swing and a 0.077 ± 0.041 Nm/kg difference in mean hip extension moment during terminal swing), and differences between the models with and without hip joint center adjustment resulted in significant differences in hip flexion and abduction moments during stance (0.217 ± 0.055 Nm/kg increased mean hip abductive moment). By comparing the outputs of these differently constructed models with each other, the study finds that dynamic predictions of stance are sensitive to positioning of joint centers, and dynamic predictions of swing are more sensitive to segment mass/inertial properties.

Posterior tibial slope influences joint mechanics and soft tissue loading after total knee arthroplasty

As a solution to restore knee function and reduce pain, the demand for Total Knee Arthroplasty (TKA) has dramatically increased in recent decades. The high rates of dissatisfaction and revision makes it crucially important to understand the relationships between surgical factors and post-surgery knee performance. Tibial implant alignment in the sagittal plane (i.e., posterior tibia slope, PTS) is thought to play a key role in quadriceps muscle forces and contact conditions of the joint, but the underlying mechanisms and potential consequences are poorly understood. To address this biomechanical challenge, we developed a subject-specific musculoskeletal model based on the bone anatomy and precise implantation data provided within the CAMS-Knee datasets. Using the novel COMAK algorithm that concurrently optimizes joint kinematics, together with contact mechanics, and muscle and ligament forces, enabled highly accurate estimations of the knee joint biomechanics (RMSE <0.16 BW of joint contact force) throughout level walking and squatting. Once confirmed for accuracy, this baseline modelling framework was then used to systematically explore the influence of PTS on knee joint biomechanics. Our results indicate that PTS can greatly influence tibio-femoral translations (mainly in the anterior-posterior direction), while also suggesting an elevated risk of patellar mal-tracking and instability. Importantly, however, an increased PTS was found to reduce the maximum tibio-femoral contact force and improve efficiency of the quadriceps muscles, while also reducing the patellofemoral contact force (by approximately 1.5% for each additional degree of PTS during walking). This study presents valuable findings regarding the impact of PTS variations on the biomechanics of the TKA joint and thereby provides potential guidance for surgically optimizing implant alignment in the sagittal plane, tailored to the implant design and the individual deficits of each patient.

A novel computational workflow to holistically assess total knee arthroplasty biomechanics identifies subject-specific effects of joint mechanics on implant fixation

Computational studies of total knee arthroplasty (TKA) often focus on either joint mechanics (kinematics and forces) or implant fixation mechanics. However, such disconnect between joint and fixation mechanics hinders our understanding of overall TKA biomechanical function by preventing identification of key relationships between these two levels of TKA mechanics. We developed a computational workflow to holistically assess TKA biomechanics by integrating musculoskeletal and finite element (FE) models. For our initial study using the workflow, we investigated how tibiofemoral contact mechanics affected the risk of failure due to debonding at the implant-cement interface using the four available subjects from the Grand Challenge Competitions to Predict In Vivo Knee Loads. We used a musculoskeletal model with a 12 degrees-of-freedom knee joint to simulate the stance phase of gait for each subject. The computed tibiofemoral joint forces at each node in contact were direct inputs to FE simulations of the same subjects. We found that the peak risk of failure did not coincide with the peak joint forces or the extreme tibiofemoral contact positions. Moreover, despite the consistency of joint forces across subjects, we observed important variability in the profile of the risk of failure during gait. Thus, by a combined evaluation of the joint and implant fixation mechanics of TKA, we could identify subject-specific effects of joint kinematics and forces on implant fixation that would otherwise have gone unnoticed. We intend to apply our workflow to evaluate the impact of implant alignment and design on TKA biomechanics.

Subject-specific tribo-contact conditions in total knee replacements: a simulation framework across scales

Fundamental knowledge about in vivo kinematics and contact conditions at the articulating interfaces of total knee replacements are essential for predicting and optimizing their behavior and durability. However, the prevailing motions and contact stresses in total knee replacements cannot be precisely determined using conventional in vivo measurement methods. In silico modeling, in turn, allows for a prediction of the loads, velocities, deformations, stress, and lubrication conditions across the scales during gait. Within the scope of this paper, we therefore combine musculoskeletal modeling with tribo-contact modeling. In the first step, we compute contact forces and sliding velocities by means of inverse dynamics approach and force-dependent kinematic solver based upon experimental gait data, revealing contact forces during healthy/physiological gait of young subjects. In a second step, the derived data are employed as input data for an elastohydrodynamic model based upon the finite element method full-system approach taking into account elastic deformation, the synovial fluid's hydrodynamics as well as mixed lubrication to predict and discuss the subject-specific pressure and lubrication conditions.

Can a Musculoskeletal Model Adapted to Knee Implant Geometry Improve Prediction of 3D Contact Forces and Moments?

Tibiofemoral contact loads are crucial parameters in the onset and progression of osteoarthrosis. While contact loads are frequently estimated from musculoskeletal models, their customization is often limited to scaling musculoskeletal geometry or adapting muscle lines. Moreover, studies have usually focused on superior-inferior contact force without investigating three-dimensional contact loads. Using experimental data from six patients with instrumented total knee arthroplasty (TKA), this study customized a lower limb musculoskeletal model to consider the positioning and the geometry of the implant at knee level. Static optimization was performed to estimate tibiofemoral contact forces and contact moments as well as musculotendinous forces. Predictions from both a generic and a customized model were compared to the instrumented implant measurements. Both models accurately predict superior-inferior (SI) force and abduction-adduction (AA) moment. Notably, the customization improves prediction of medial-lateral (ML) force and flexion-extension (FE) moments. However, there is subject-dependent variability in the prediction of anterior-posterior (AP) force. The customized models presented here predict loads on all joint axes and in most cases improve prediction. Unexpectedly, this improvement was more limited for patients with more rotated implants, suggesting a need for further model adaptations such as muscle wrapping or redefinition of hip and ankle joint centers and axes.

Video-driven simulation of lower limb mechanical loading during aquatic exercises

Understanding the mechanical demands of an exercise on the musculoskeletal system is crucial to prescribe effective training or therapeutic interventions. Yet, that knowledge is currently limited in water, mostly because of the difficulty in evaluating external resistance. Here I reconcile recent advances in 3D markerless pose and mesh estimation, biomechanical simulations, and hydrodynamic modeling, to predict lower limb mechanical loading during aquatic exercises. Simulations are driven exclusively from a single video. Fluid forces were estimated within 12.5±4.1% of the peak forces determined through computational fluid dynamics analyses, at a speed three orders of magnitude greater. In silico hip and knee resultant joint forces agreed reasonably well with in vivo instrumented implant recordings (R²=0.74) downloaded from the OrthoLoad database, both in magnitude (RMSE =251±125 N) and direction (cosine similarity = 0.92±0.09). Hip flexors, glutes, adductors, and hamstrings were the main contributors to hip joint compressive forces (40.4±12.7%, 25.6±9.7%, 14.2±4.8%, 13.0±8.2%, respectively), while knee compressive forces were mostly produced by the gastrocnemius (39.1±15.9%) and vasti (29.4±13.7%). Unlike dry-land locomotion, non-hip- and non-knee-spanning muscles provided little to no offloading effect via dynamic coupling. This noninvasive method has the potential to standardize the reporting of exercise intensity, inform the design of rehabilitation protocols and improve their reproducibility.

Periarticular muscle status affects in vivo tibio-femoral joint loads after total knee arthroplasty

Background: Total knee arthroplasty (TKA) is a highly effective treatment for severe knee osteoarthritis that is increasingly performed in younger, more active patients. As postoperative muscular impairments may negatively affect surgical outcomes and implant longevity, functional muscle recovery gains increasing importance in meeting future patient demands. This study aimed to assess the status of periarticular muscles in the long-term follow-up after TKA and to evaluate its impact on in vivo tibio-femoral joint loads. Methods: A case series was created, with eight patients with knee osteoarthritis. All subjects received an instrumented knee implant in unilateral TKA. Native computed tomography scans, acquired pre and postoperatively, were used to evaluate distal muscle volumes and fatty infiltration. In vivo tibio-femoral joint loads were measured telemetrically during standing, walking, stair climbing and chair rising and were correlated to muscle status. Results: Postoperatively a reduction in fatty infiltration across all periarticular muscles was pronounced. High average peak loads acted in the tibio-femoral joint ranging from 264% during stand-to-sit activities up to 341% body weight (BW) during stair descent. Fatty infiltration of the m. quadriceps femoris and hamstrings were associated with increased tibio-femoral joint contact forces during walking (r = 0.542; 0.412 and 0.766). Conclusion: The findings suggest that a fatty infiltration of periarticular muscles may lead to increased tibio-femoral joint contact forces. However, we only observed weak correlations between these parameters. Improvements in functional mobility and the restoration of a pain-free joint likely explain the observed postoperative reductions in fatty infiltration. Perioperative rehabilitation approaches targeting residual impairments in muscle quality could, contribute to reduced tibio-femoral joint loads and improved long-term outcomes of TKA. However, it has to be pointed out that the study included a small number of patients, which may limit its validity.

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.

Altering the strength of the muscles crossing the lower limb joints only affects knee joint reaction forces

BACKGROUND

Generic musculoskeletal models based on literature data are often used to estimate joint reaction forces (JRFs) that otherwise could only be measured invasively. Estimated JRFs are sensitive to changes in maximum isometric force (F_iso) of the muscles, but these are normally simply scaled using a multiplicative coefficient. The impact of varying F_iso, or strength, of muscles crossing each lower limb joint on estimated JRFs has not been systematically explored in musculoskeletal models of the lower limb.

RESEARCH QUESTION

How do alterations in the strength of joint-crossing muscles influence the lower limb JRF magnitudes computed through a generic musculoskeletal model?

METHODS

By modifying F_iso of muscles crossing hip, knee, ankle, or all joints at once up to ± 40% in 10% increments, thirty-two models were created to simulate the gait of a patient with an instrumented tibial prosthesis (5^th Grand Challenge dataset). A standard workflow (inverse kinematics, static optimization, joint reaction analysis) was utilized to calculate JRFs. Both alterations in JRF magnitudes due to joint crossing muscles' strength modifications and their accuracy against in vivo knee loading measurements were quantified.

RESULTS

The knee JRF was the most sensitive force to changes in the joint-crossing muscles' strength (variations ranging from -37.9 ± 0.5% to +37.9 ± 3.2%), while the hip and ankle JRFs were almost unaffected (maximum variation: +6.1%). Reducing the strength of knee and ankle-crossing muscles and intensifying the strength of hip-crossing muscles lowered the knee JRF. The knee JRF was best estimated (peak error: 0.42 ± 0.15 body weight, root mean squared error: 0.37 ± 0.06 body weight, coefficient of determination: 0.76 ± 0.10) by the model with -40% weakened knee-crossing muscles.

SIGNIFICANCE

Altering strengths mainly affects knee JRF estimated with generic musculoskeletal models, suggesting that personalization of strength of joint-crossing muscles is required for accurate knee JRF estimations. Rehabilitation regimes meant to strengthen muscles crossing a joint should be carefully designed to avoid undesired effects on the other joints.

A Computationally Efficient Musculoskeletal Model of the Lower Limb for the Control of Rehabilitation Robots: Assumptions and Validation

We present and validate a computationally efficient lower limb musculoskeletal model for the control of a rehabilitation robot. It is a parametric model that allows the customization of joint kinematics, and it is able to operate in real time. Methods: Since the rehabilitation exercises corresponds to low-speed movements, a quasi-static model can be assumed, and then muscle force coefficients are position dependent. This enables their calculation in an offline stage. In addition, the concept of a single functional degree of freedom is used to minimize drastically the workspace of the stored coefficients. Finally, we have developed a force calculation process based on Lagrange multipliers that provides a closed-form solution; in this way, the problem of dynamic indeterminacy is solved without the need to use an iterative process. Results: The model has been validated by comparing muscle forces estimated by the model with the corresponding electromyography (EMG) values using squat exercise, in which the Spearman’s correlation coefficient is higher than 0.93. Its computational time is lower than 2.5 ms in a conventional computer using MATLAB. Conclusions: This procedure presents a good agreement with the experimental values of the forces, and it can be integrated into real time control systems.

Dependency of lower limb joint reaction forces on femoral version

BACKGROUND

Musculoskeletal (MSK) models based on literature data are meant to represent a generic anatomy and are a popular tool employed by biomechanists to estimate the internal loads occurring in the lower limb joints, such as joint reaction forces (JRFs). However, since these models are normally just linearly scaled to an individual's anthropometry, it is unclear how their estimations would be affected by the personalization of key features of the MSK anatomy, one of which is the femoral version angle.

RESEARCH QUESTION

How are the lower limb JRF magnitudes computed through a generic MSK model affected by changes in the femoral version?

METHODS

We developed a bone-deformation tool in MATLAB (shared at https://simtk.org/projects/bone_deformity) and used it to create a set of seven OpenSim models spanning from 2˚ femoral retroversion to 40˚ anteversion. We used these models to simulate the gait of an elderly individual with an instrumented prosthesis implanted at their knee joint (5th Grand Challenge dataset) and quantified both the changes in JRFs magnitude due to varying the skeletal anatomy and their accuracy against the correspondent in vivo measurements at the knee joint.

RESULTS

Hip and knee JRF magnitudes were affected by the femoral version with variations from the unmodified generic model up to 17.9 ± 4.5% at the hip and 43.4 ± 27.1% at the knee joint. The ankle joint was unaffected by the femoral geometry. The MSK models providing the most accurate knee JRFs (root mean squared error: 0.370 ± 0.068 body weight, coefficient of determination: 0.757 ± 0.104, peak error range: 0.09-0.42 body weight) were those with femoral anteversion angle closer to that measured on the segmented bone of the individual.

SIGNIFICANCE

Femoral version substantially affects hip and knee JRFs estimated with generic MSK models, suggesting that personalizing key MSK anatomical features might be necessary for accurate estimation of JRFs with these models.

Contribution of passive moments to inter-segmental moments during gait: A systematic review

Inter-segmental moments computed by inverse dynamic during gait come from active moments, due to muscle contraction, but also from passive moments, resulting from the resistance of the periarticular structures to their deformation. The evaluation of the proportion of the inter-segmental moments that can be attributed to passive moments has led to divergent results. Thus, the purpose of this study was to systematically search and synthesize the evidence of the contribution of passive moments to inter-segmental moments during healthy and pathological gait. A broad systematic search was performed including four databases. Thirteen studies met all inclusion criteria. Results showed that passive moments participate to inter-segmental moments during gait in a non-negligible way. For the ankle, the evaluation of the proportion of inter-segmental moment attributed to passive structures is 5-20% around the push-off. For the knee, this proportion is 40-98% during late swing and 10-80% during the single support phase. For the hip, it is 20-50% at push-off. For pathological population, it has been shown that this contribution may sometimes be more important, either due to a smaller inter-segmental moment or a larger passive moment. These results suggest that passive mechanisms can contribute substantially to normal human gait, facilitating the propulsion or the braking of the joint. Passive structures, acting as elastic springs, thus help to reduce the energy cost of gait. For pathological gait, studying the contribution of passive moments to inter-segmental moments can help to better understand the aetiology of the pathology.

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.

Biomechanical Study of a Tricompartmental Unloader Brace for Patellofemoral or Multicompartment Knee Osteoarthritis

Objective: Off-loader knee braces have traditionally focused on redistributing loads away from either the medial or lateral tibiofemoral (TF) compartments. In this article, we study the potential of a novel "tricompartment unloader" (TCU) knee brace intended to simultaneously unload both the patellofemoral (PF) and TF joints during knee flexion. Three different models of the TCU brace are evaluated for their potential to unload the knee joint. Methods: A sagittal plane model of the knee was used to compute PF and TF contact forces, patellar and quadriceps tendon forces, and forces in the anterior and posterior cruciate ligaments during a deep knee bend (DKB) test using motion analysis data from eight participants. Forces were computed for the observed (no brace) and simulated braced conditions. A sensitivity and validity analysis was conducted to determine the valid output range for the model, and Statistical Parameter Mapping was used to quantify the effectual region of the different TCU brace models. Results: PF and TF joint force calculations were valid between ~0 and 100 degrees of flexion. All three simulated brace models significantly (p < 0.001) reduced predicted knee joint loads (by 30-50%) across all structures, at knee flexion angles >~30 degrees during DKB. Conclusions: The TCU brace is predicted to reduce PF and TF knee joint contact loads during weight-bearing activity requiring knee flexion angles between 30 and 100 degrees; this effect may be clinically beneficial for pain reduction or rehabilitation from common knee injuries or joint disorders. Future work is needed to assess the range of possible clinical and prophylactic benefits of the TCU brace.

Computational Modelling of the Bioheat Transfer Process in Human Skin Subjected to Direct Heating and/or Cooling Sources: A Systematic Review

The purpose of this systematic review is to analyze characteristics and methodologies utilized in bioheat transfer models of human skin to provide state-of-the-art knowledge on the topic. This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. PubMed, EMBASE and Web of Science databases were searched up to May 30th, 2019 for bioheat transfer models focusing on direct contact between skin and temperature (heat and/or cold) source. Ten studies were included. A 16-item checklist was used to assess their methodological quality. Four studies analyzed healthy skin and six included pathological conditions. All determined skin's thermal behavior, and studies including pathological conditions also analyzed burn damage. Studies did not present a wide variety of mathematical formulation, emphasizing on modelling equations of well-established models from the literature, such as the Pennes' bioheat transfer equation, and the Henriques and Moritz model to quantify skin damage. Reporting of modelling characteristics and formulation of the computational models is not standardized and there is shortage of implementation of validation procedures, hindering representative conclusions. The lack of validation procedures led to low methodological quality. However, all studies provided strategies and parameters as starting points for future developments in this research area.

Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling

We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to the segmentation label. We evaluated the performance of the proposed method using two data sets: 20 fully annotated CTs of the hip and thigh regions and 18 partially annotated CTs that are publicly available from The Cancer Imaging Archive (TCIA) database. The experiments showed a Dice coefficient (DC) of 0.891±0.016 (mean±std) and an average symmetric surface distance (ASD) of 0.994±0.230 mm over 19 muscles in the set of 20 CTs. These results were statistically significant improvements compared to the state-of-the-art hierarchical multi-atlas method which resulted in 0.845 ± 0.031 DC and 1.556 ± 0.444 mm ASD. We evaluated validity of the uncertainty metric in the multi-class organ segmentation problem and demonstrated a correlation between the pixels with high uncertainty and the segmentation failure. One application of the uncertainty metric in active-learning is demonstrated, and the proposed query pixel selection method considerably reduced the manual annotation cost for expanding the training data set. The proposed method allows an accurate patient-specific analysis of individual muscle shapes in a clinical routine. This would open up various applications including personalization of biomechanical simulation and quantitative evaluation of muscle atrophy.

Gait alteration strategies for knee osteoarthritis: a comparison of joint loading via generic and patient-specific musculoskeletal model scaling techniques

Gait modifications and laterally wedged insoles are non-invasive approaches used to treat medial compartment knee osteoarthritis. However, the outcome of these alterations is still a controversial topic. This study investigates how gait alteration techniques may have a unique effect on individual patients; and furthermore, the way we scale our musculoskeletal models to estimate the medial joint contact force may influence knee loading conditions. Five patients with clinical evidence of medial knee osteoarthritis were asked to walk at a normal walking speed over force plates and simultaneously 3D motion was captured during seven conditions (0°-, 5°-, 10°-insoles, shod, toe-in, toe-out, and wide stance). We developed patient-specific musculoskeletal models, using segmentations from magnetic resonance imaging to morph a generic model to patient-specific bone geometries and applied this morphing to estimate muscle insertion sites. Additionally, models were created of these patients using a simple linear scaling method. When examining the patients' medial compartment contact force (peak and impulse) during stance phase, a 'one-size-fits-all' gait alteration aimed to reduce medial knee loading did not exist. Moreover, the different scaling methods lead to differences in medial contact forces; highlighting the importance of further investigation of musculoskeletal modeling methods prior to use in the clinical setting.

Inverse dynamic estimates of muscle recruitment and joint contact forces are more realistic when minimizing muscle activity rather than metabolic energy or contact forces

BACKGROUND

Assessment of contact forces is essential for a better understanding of mechanical factors affecting progression of osteoarthritis. Since contact forces cannot be measured non-invasively, computer simulations are often used to assess joint loading. Contact forces are to a large extent determined by muscle forces. These muscle forces are computed using optimization techniques that solve the muscle redundancy problem by assuming that muscles are coordinated in a way that optimizes performance (e.g., minimizes muscle activity or metabolic energy). However, it is unclear which of the many proposed performance criteria best describes muscle coordination.

RESEARCH QUESTION

Which performance criterion best describes muscle recruitment patterns and knee contact forces recorded using electromyography (EMG) and load cell instrumented prostheses?.

METHODS

We solved the muscle redundancy problem based on six different groups of performance criteria: muscle activations, volume-scaled activations, forces, stresses, metabolic energy, and joint contact forces. Computed muscle excitations and knee contact forces during over-ground walking were validated against recorded EMG signals and measured contact forces for four subjects with instrumented knee prostheses in the "Grand Challenge Competition to Predict in Vivo Knee Loads" dataset.

RESULTS

Performance criteria based on either stress or muscle activation (either unscaled or scaled by muscle volume), both to a power of 3 or 4, resulted in the best agreement between measured and simulated values. These performance criteria outperformed all other criteria in terms of agreement between simulated muscle excitations and EMG, whereas good agreement between measured and predicted contact forces was also observed for minimization of contact forces and metabolic energy.

SIGNIFICANCE

Given the large differences in accuracy obtained with different performance criteria (e.g., root mean square errors of contact forces differed up to 0.45 body weight), the results of our study are important to improve the validity of in silico assessment of joint loading.

Can a reduction approach predict reliable joint contact and musculo-tendon forces?

Musculoskeletal models generally solve the muscular redundancy by numerical optimisation. They have been extensively validated using instrumented implants. Conversely, a reduction approach considers only one flexor or extensor muscle group at the time to equilibrate the inter-segmental joint moment. It is not clear if such models can still predict reliable joint contact and musculo-tendon forces during gait. Tibiofemoral contact force and gastrocnemii, quadriceps, and hamstrings musculo-tendon forces were estimated using a reduction approach for five subjects walking with an instrumented prosthesis. The errors in the proximal-distal tibiofemoral contact force fell in the range (0.3-0.9 body weight) reported in the literature for musculoskeletal models using numerical optimisation. The musculo-tendon forces were in agreement with the EMG envelops and appeared comparable to the ones reported in the literature with generic musculoskeletal models. Although evident simplifications and limitations, it seems that the reduction approach can provided quite reliable results. It can be a useful pedagogical tool in biomechanics, e.g. to illustrate the theoretical differences between inter-segmental and contact forces, and can provide a first estimate of the joint loadings in subjects with limited musculoskeletal deformities and neurological disorders.

Evaluation of predicted patellofemoral joint kinematics with a moving-axis joint model

The main objectives of this study were to expand the moving-axis joint model concept to the patellofemoral joint and evaluate the patellar motion against experimental patellofemoral kinematics. The experimental data was obtained through 2D-to-3D bone reconstruction of EOS images and segmented MRI data utilizing an iterative closest point optimization technique. Six knee model variations were developed using the AnyBody Modeling System and subject-specific bone geometries. These models consisted of various combinations of tibiofemoral (hinge, moving-axis, and interpolated) and patellofemoral (hinge and moving-axis) joint types. The newly introduced interpolated tibiofemoral joint is calibrated from the five EOS quasi-static lunge positions. The patellofemoral axis of the hinge model was defined by performing surface fits to the patellofemoral contact area; and the moving-axis model was defined based upon the position of the patellofemoral joint at 0° and 90° tibiofemoral-flexion. In between these angles, the patellofemoral axis moved linearly as a function of tibiofemoral-flexion, while outside these angles, the axis remained fixed. When using a moving-axis tibiofemoral joint, a hinge patellofemoral joint offers (-5.12 ± 1.23 mm, 5.81 ± 0.97 mm, 14.98 ± 2.30°, -4.35 ± 1.95°) mean differences (compared to EOS) while a moving-axis patellofemoral model provides (-2.69 ± 1.04 mm, 1.13 ± 0.80 mm, 12.63 ± 2.03°, 1.74 ± 1.46°) in terms of lateral-shift, superior translation, patellofemoral-flexion, and patellar-rotation, respectively. Furthermore, the model predictive capabilities increased as a direct result of adding more calibrated positions to the tibiofemoral model (hinge-1, moving-axis-2, and interpolated-5). Overall, a novel subject-specific moving-axis patellofemoral model has been established; that produces realistic patellar motion and is computationally fast enough for clinical applications.

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.

On the biomechanical relationship between applied hip, knee and ankle joint moments and the internal knee compressive forces

Mechanical devices are common treating methods for knee osteoarthritis. It has the purpose of reducing the internal joint forces and unloading the damaged structure. The reduction is often achieved by alterations in the frontal plan, shifting the contact force from one compartment to the other, leaving the total compressive force unchanged. The aim of this study was to investigate how internal knee joint forces depend on applied external moments during gait. Musculoskeletal models of the gait of 10 healthy subjects were developed in the AnyBody Modelling System and used to simulate applied joint moments about different axes (load cases), each with the magnitude to compensate the net moment about the respective axis by a specified percentage. For each load case, the total, medial and lateral knee compressive force were computed and compared with a baseline case with no external moments applied. Among the investigated moments, hip flexion-extension, knee flexion-extension and ankle plantarflexion-dorsiflexion moment compensations have the most positive impact on the total knee joint compressive force, and combining the 3, each with a 40% compensation of the muscle moments, reduced the first peak by 23.6%, the second by 30.6% and the impulse by 28.6% with respect to no applied moments.