EMG-Assisted Muscle Force Driven Finite Element Model of the Knee Joint with Fibril-Reinforced Poroelastic Cartilages and Menisci

Computational modelling of articular joints with biphasic cartilage: recent advances, challenges and opportunities

Biphasic models have been widely used to simulate the time-dependent biomechanical response of soft tissues. Modelling techniques of joints with biphasic weight-bearing soft tissues have been markedly improved over the last decade, enhancing our understanding of the function, degenerative mechanism and outcomes of interventions of joints. This paper reviews the recent advances, challenges and opportunities in computational models of joints with biphasic weight-bearing soft tissues. The review begins with an introduction of the function and degeneration of joints from a biomechanical aspect. Different constitutive models of articular cartilage, in particular biphasic materials, are illustrated in the context of the study of contact mechanics in joints. Approaches, advances and major findings of biphasic models of the hip and knee are presented, followed by a discussion of the challenges awaiting to be addressed, including the convergence issue, high computational cost and inadequate validation. Finally, opportunities and clinical insights in the areas of subject-specific modeling and tissue engineering are provided and discussed.

Model Properties and Clinical Application in the Finite Element Analysis of Knee Joint: A Review

The knee is the most complex joint in the human body, including bony structures like the femur, tibia, fibula, and patella, and soft tissues like menisci, ligaments, muscles, and tendons. Complex anatomical structures of the knee joint make it difficult to conduct precise biomechanical research and explore the mechanism of movement and injury. The finite element model (FEM), as an important engineering analysis technique, has been widely used in many fields of bioengineering research. The FEM has advantages in the biomechanical analysis of objects with complex structures. Researchers can use this technology to construct a human knee joint model and perform biomechanical analysis on it. At the same time, finite element analysis can effectively evaluate variables such as stress, strain, displacement, and rotation, helping to predict injury mechanisms and optimize surgical techniques, which make up for the shortcomings of traditional biomechanics experimental research. However, few papers introduce what material properties should be selected for each anatomic structure of knee FEM to meet different research purposes. Based on previous finite element studies of the knee joint, this paper summarizes various modeling strategies and applications, serving as a reference for constructing knee joint models and research design.

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.

Effects of gait modifications on tissue-level knee mechanics in individuals with medial tibiofemoral osteoarthritis: A proof-of-concept study towards personalized interventions

Gait modification is a common nonsurgical approach to alter the mediolateral distribution of knee contact forces, intending to decelerate or postpone the progression of mechanically induced knee osteoarthritis (KOA). Nevertheless, the success rate of these approaches is controversial, with no studies conducted to assess alterations in tissue-level knee mechanics governing cartilage degradation response in KOA patients undertaking gait modifications. Thus, here we investigated the effect of different conventional gait conditions and modifications on tissue-level knee mechanics previously suggested as indicators of collagen network damage, cell death, and loss of proteoglycans in knee cartilage. Five participants with medial KOA were recruited and musculoskeletal finite element analyses were conducted to estimate subject-specific tissue mechanics of knee cartilages during two gait conditions (i.e., barefoot and shod) and six gait modifications (i.e., 0°, 5°, and 10° lateral wedge insoles, toe-in, toe-out, and wide stance). Based on our results, the optimal gait modification varied across the participants. Overall, toe-in, toe-out, and wide stance showed the greatest reduction in tissue mechanics within medial tibial and femoral cartilages. Gait modifications could effectually alter maximum principal stress (~20 ± 7%) and shear strain (~9 ± 4%) within the medial tibial cartilage. Nevertheless, lateral wedge insoles did not reduce joint- and tissue-level mechanics considerably. Significance: This proof-of-concept study emphasizes the importance of the personalized design of gait modifications to account for biomechanical risk factors associated with cartilage degradation.

Development of a three-dimensional muscle-driven lower limb model developed using an improved CFD-FE method

Analysis of the musculoskeletal movements (gait analysis) is needed in many scenarios. The in vivo method has some difficulties. For example, recruiting human subjects for the gait analysis is challenging due to many issues. In addition, when plenty of subjects are required, the follow-up experiments take a long period and the dropout of subjects always occurs. An efficient and reliable in silico simulation platform for gait analysis has been desired for a long time. Therefore, a technique using three-dimensional (3D) muscle modeling to drive the 3D musculoskeletal model was developed and the application of the technique in the simulation of lower limb movements was demonstrated. A finite element model of the lower limb with anatomically high fidelity was developed from the MRI data, where the main muscles, the bones, the subcutaneous tissues, and the skin were reconstructed. To simulate the active behavior of 3D muscles, an active, fiber-reinforced hyperelastic muscle model was developed using the user-defined material (VUMAT) model. Two typical movements, that is, hip abduction and knee lifting, were simulated by activating the responsible muscles. The results show that it is reasonable to use the improved CFD-FE method proposed in the present study to simulate the active contraction of the muscle, and it is feasible to simulate the movements by activating the relevant muscles. The results from the present technique closely match the physiological scenario and thus the technique developed has a great potential to be used in the in silico human simulation platform for many purposes.

Biomechanical effects of typical lower limb movements of Chen-style Tai Chi on knee joint

The load and stress distribution on cartilage and meniscus of the knee joint in typical lower limb movements of Chen-style Tai Chi (TC) and deep squat (DS) were analyzed using finite element (FE) analysis. The loadings for this analysis consisted of muscle forces and ground reaction force (GRF), which were calculated through the inverse dynamic approach based on kinematics and force plate measurements obtained from motion capture experiments. Thirteen experienced practitioners performed four typical TC movements, namely, single whip (SW), brush knee and twist step (BKTS), stretch down (SD), and part the wild horse's mane (PWHM), which exhibit lower posture and greater lower limb force compared to other TC styles. The results indicated that TC required greater lower limb muscle strength than DS, resulting in greater knee joint forces. The stress on the medial cartilage in SW and BKTS fell within a range conductive to maintaining the balance between anabolism and catabolism of cartilage matrix. This was due to the fact that SW and BKTS reduce the medial to total tibiofemoral contact force ratios through knee abduction, which may effectively alleviate mild medial knee osteoarthritis (KOA). However, the greater medial contact force ratios observed in SD and PWHM resulted in great contact stresses that may aggravate the pain of patients with KOA. To mitigate these effects, practitioners should consider elevating their postures appropriately to reduce knee flexion angles, especially during the single-leg support phase. This adjustment can decrease the required muscle strength, load and stress on the knee joint.

Sensitivity of simulated knee joint mechanics to selected human and bovine fibril-reinforced poroelastic material properties

Fibril-reinforced poroviscoelastic material models are considered state-of-the-art in modeling articular cartilage biomechanics. Yet, cartilage material parameters are often based on bovine tissue properties in computational knee joint models, although bovine properties are distinctly different from those of humans. Thus, we aimed to investigate how cartilage mechanical responses are affected in the knee joint model during walking when fibril-reinforced poroviscoelastic properties of cartilage are based on human data instead of bovine. We constructed a finite element knee joint model in which tibial and femoral cartilages were modeled as fibril-reinforced poroviscoelastic material using either human or bovine data. Joint loading was based on subject-specific gait data. The resulting mechanical responses of knee cartilage were compared between the knee joint models with human or bovine fibril-reinforced poroviscoelastic cartilage properties. Furthermore, we conducted a sensitivity analysis to determine which fibril-reinforced poroviscoelastic material parameters have the greatest impact on cartilage mechanical responses in the knee joint during walking. In general, bovine cartilage properties yielded greater maximum principal stresses and fluid pressures (both up to 30%) when compared to the human cartilage properties during the loading response in both femoral and tibial cartilage sites. Cartilage mechanical responses were very sensitive to the collagen fibril-related material parameter variations during walking while they were unresponsive to proteoglycan matrix or fluid flow-related material parameter variations. Taken together, human cartilage material properties should be accounted for when the goal is to compare absolute mechanical responses of knee joint cartilage as bovine material parameters lead to substantially different cartilage mechanical responses.

Signatures of disease progression in knee osteoarthritis: insights from an integrated multi-scale modeling approach, a proof of concept

Introduction: Knee osteoarthritis (KOA) is characterized by articular cartilage degeneration. It has been widely accepted that the mechanical joint environment plays a significant role in the onset and progression of this disease. In silico models have been used to study the interplay between mechanical loading and cartilage degeneration, hereby relying mainly on two key mechanoregulatory factors indicative of collagen degradation and proteoglycans depletion. These factors are the strain in collagen fibril direction (SFD) and maximum shear strain (MSS) respectively. Methods: In this study, a multi-scale in silico modeling approach was used based on a synergy between musculoskeletal and finite element modeling to evaluate the SFD and MSS. These strains were evaluated during gait based on subject-specific gait analysis data collected at baseline (before a 2-year follow-up) for a healthy and progressive early-stage KOA subject with similar demographics. Results: The results show that both SFD and MSS factors allowed distinguishing between a healthy subject and a KOA subject, showing progression at 2 years follow-up, at the instance of peak contact force as well as during the stance phase of the gait cycle. At the peak of the stance phase, the SFD were found to be more elevated in the KOA patient with the median being 0.82% higher in the lateral and 0.4% higher in the medial compartment of the tibial cartilage compared to the healthy subject. Similarly, for the MSS, the median strains were found to be 3.6% higher in the lateral and 0.7% higher in the medial tibial compartment of the KOA patient compared to the healthy subject. Based on these intersubject SFD and MSS differences, we were additionally able to identify that the tibial compartment of the KOA subject at risk of progression. Conclusion/discussion: We confirmed the mechanoregulatory factors as potential biomarkers to discriminate patients at risk of disease progression. Future studies should evaluate the sensitivity of the mechanoregulatory factors calculated based on this multi-scale modeling workflow in larger patient and control cohorts.

Computational assessment on the impact of collagen fiber orientation in cartilages on healthy and arthritic knee kinetics/kinematics

BACKGROUND

The inhomogeneous distribution of collagen fiber in cartilage can substantially influence the knee kinematics. This becomes vital for understanding the mechanical response of soft tissues, and cartilage deterioration including osteoarthritis (OA). Though the conventional computational models consider geometrical heterogeneity along with fiber reinforcements in the cartilage model as material heterogeneity, the influence of fiber orientation on knee kinetics and kinematics is not fully explored. This work examines how the collagen fiber orientation in the cartilage affects the healthy (intact knee) and arthritic knee response over multiple gait activities like running and walking.

METHODS

A 3D finite element knee joint model is used to compute the articular cartilage response during the gait cycle. A fiber-reinforced porous hyper elastic (FRPHE) material is used to model the soft tissue. A split-line pattern is used to implement the fiber orientation in femoral and tibial cartilage. Four distinct intact cartilage models and three OA models are simulated to assess the impact of the orientation of collagen fibers in a depth wise direction. The cartilage models with fibers oriented in parallel, perpendicular, and inclined to the articular surface are investigated for multiple knee kinematics and kinetics.

FINDINGS

The comparison of models with fiber orientation parallel to articulating surface for walking and running gait has the highest elastic stress and fluid pressure compared with inclined and perpendicular fiber-oriented models. Also, the maximum contact pressure is observed to be higher in the case of intact models during the walking cycle than for OA models. In contrast, the maximum contact pressure is higher during running in OA models than in intact models. Additionally, parallel-oriented models produce higher maximum stresses and fluid pressure for walking and running gait than proximal-distal-oriented models. Interestingly, during the walking cycle, the maximum contact pressure with intact models is approximately three times higher than on OA models. In contrast, the OA models exhibit higher contact pressure during the running cycle.

INTERPRETATION

Overall, the study indicates that collagen orientation is crucial for tissue responsiveness. This investigation provides insights into the development of tailored implants.

[Innovative image-based planning in musculoskeletal surgery]

BACKGROUND

For the preparation of surgical procedures in orthopedics and trauma surgery, precise knowledge of imaging and the three-dimensional imagination of the surgeon are of outstanding importance. Image-based, preoperative two-dimensional planning is the gold standard in arthroplasty today. In complex cases, further imaging such as computed tomography (CT) or magnetic resonance imaging is also performed, generating a three-dimensional model of the body region and helping the surgeon in the planning of the surgical treatment. Four-dimensional, dynamic CT studies have also been reported and are available as a complementary tool.

DIGITAL AIDS

Furthermore, digital aids should generate an improved representation of the pathology to be treated and optimize the surgeon's imagination. The finite element method allows patient-specific and implant-specific parameters to be taken into account in preoperative surgical planning. Intraoperatively, relevant information can be provided by augmented reality without significantly influencing the surgical workflow.

Validation of a Finite Element Simulation for Predicting Individual Knee Joint Kinematics

Goal: We introduce an in-vivo validated finite element (FE) simulation approach for predicting individual knee joint kinematics. Our vision is to improve clinicians' understanding of the complex individual anatomy and potential pathologies to improve treatment and restore physiological joint kinematics. Methods: Our 3D FE modeling approach for individual human knee joints is based on segmentation of anatomical structures extracted from routine static magnetic resonance (MR) images. We validate the predictive abilities of our model using static MR images of the knees of eleven healthy volunteers in dedicated knee poses, which are achieved using a customized MR-compatible pneumatic loading device. Results: Our FE simulations reach an average translational accuracy of 2 mm and an average angular accuracy of 1[Formula: see text] compared to the reference knee pose. Conclusions: Reaching high accuracy, our individual FE model can be used in the decision-making process to restore knee joint stability and functionality after various knee injuries.

Injury-related cell death and proteoglycan loss in articular cartilage: Numerical model combining necrosis, reactive oxygen species, and inflammatory cytokines

Osteoarthritis (OA) is a common musculoskeletal disease that leads to deterioration of articular cartilage, joint pain, and decreased quality of life. When OA develops after a joint injury, it is designated as post-traumatic OA (PTOA). The etiology of PTOA remains poorly understood, but it is known that proteoglycan (PG) loss, cell dysfunction, and cell death in cartilage are among the first signs of the disease. These processes, influenced by biomechanical and inflammatory stimuli, disturb the normal cell-regulated balance between tissue synthesis and degeneration. Previous computational mechanobiological models have not explicitly incorporated the cell-mediated degradation mechanisms triggered by an injury that eventually can lead to tissue-level compositional changes. Here, we developed a 2-D mechanobiological finite element model to predict necrosis, apoptosis following excessive production of reactive oxygen species (ROS), and inflammatory cytokine (interleukin-1)-driven apoptosis in cartilage explant. The resulting PG loss over 30 days was simulated. Biomechanically triggered PG degeneration, associated with cell necrosis, excessive ROS production, and cell apoptosis, was predicted to be localized near a lesion, while interleukin-1 diffusion-driven PG degeneration was manifested more globally. Interestingly, the model also showed proteolytic activity and PG biosynthesis closer to the levels of healthy tissue when pro-inflammatory cytokines were rapidly inhibited or cleared from the culture medium, leading to partial recovery of PG content. The numerical predictions of cell death and PG loss were supported by previous experimental findings. Furthermore, the simulated ROS and inflammation mechanisms had longer-lasting effects (over 3 days) on the PG content than localized necrosis. The mechanobiological model presented here may serve as a numerical tool for assessing early cartilage degeneration mechanisms and the efficacy of interventions to mitigate PTOA progression.

A Musculoskeletal Model for Estimating Hip Contact Pressure During Walking

Cartilage contact pressures are major factors in osteoarthritis etiology and are commonly estimated using finite element analysis (FEA). FEA models often include subject-specific joint geometry, but lack subject-specific joint kinematics and muscle forces. Musculoskeletal models use subject-specific kinematics and muscle forces but often lack methods for estimating cartilage contact pressures. Our objective was to adapt an elastic foundation (EF) contact model within OpenSim software to predict hip cartilage contact pressures and compare results to validated FEA models. EF and FEA models were built for five subjects. In the EF models, kinematics and muscle forces were applied and pressure was calculated as a function of cartilage overlap depth. Cartilage material properties were perturbed to find the best match to pressures from FEA. EF models with elastic modulus = 15 MPa and Poisson's ratio = 0.475 yielded results most comparable to FEA, with peak pressure differences of 4.34 ± 1.98 MPa (% difference = 39.96 ± 24.64) and contact area differences of 3.73 ± 2.92% (% difference = 13.4 ± 11.3). Peak pressure location matched between FEA and EF for 3 of 5 subjects, thus we do not recommend this model if the location of peak contact pressure is critically important to the research question. Contact area magnitudes and patterns matched reasonably between FEA and EF, suggesting that this model may be useful for questions related to those variables, especially if researchers desire inclusion of subject-specific geometry, kinematics, muscle forces, and dynamic motion in a computationally efficient framework.

Computational biomechanics of human knee joint in stair ascent: Muscle-ligament-contact forces and comparison with level walking

About a third of knee joint disorders originate from the patellofemoral (PF) site that makes stair ascent a difficult activity for patients. A detailed finite element model of the knee joint is coupled to a lower extremity musculoskeletal model to simulate the stance phase of stair ascent. It is driven by the mean of measurements on the hip-knee-ankle moments-angles as well as ground reaction forces reported in healthy individuals. Predicted muscle activities compare well to the recorded electromyography data. Peak forces in quadriceps (3.87 BW, body weight, at 20% instance in our 607 N subject), medial hamstrings (0.77 BW at 20%), and gastrocnemii (1.21 BW at 80%) are estimated. Due to much greater flexion angles-moments in the first half of stance, large PF contact forces (peak of 3.1 BW at 20% stance) and stresses (peak of 4.83 MPa at 20% stance) are estimated that exceed their peaks in level walking by fourfold and twofold, respectively. Compared with level walking, ACL forces diminish in the first half of stance but substantially increase later in the second half (peak of 0.76 BW at 75% stance). Under nearly similar contact forces at 20% of stance, the contact stress on the tibiofemoral (TF) medial plateau reaches a peak (9.68 MPa) twice that on the PF joint suggesting the vulnerability of both joints. Compared with walking, stair ascent increases peak ACL force and both peak TF and PF contact stresses. Reductions in the knee flexion moment and/or angle appear as a viable strategy to mitigate internal loads and pain.

Intra-Articular Biomechanical Changes of the Meniscus and Ligaments During Stance Phase of Gait Circle after Different Anterior Cruciate Ligament Reconstruction Surgical Procedures: A Finite Element Analysis

OBJECTIVE

The debate on the superiority of single- or double-bundle for anterior cruciate ligament reconstruction has not ceased. The comparative studies on intra-articular biomechanics after different surgical reconstructions are rare. This study is to evaluate the biomechanical stress distribution intra-knee after single- and double-bundle anterior cruciate ligament reconstruction by three-dimensional finite element analysis, and to observe the change of stress concentration under the condition of vertical gradient loads.

METHODS

In this study, magnetic resonance imaging data were extracted from patients and healthy controls for biomechanical analysis. Patients included in the three models were matched in age and sex. The strength and distribution of induced stresses were analyzed in two frequently used procedures, anatomical single-bundle anterior cruciate ligament reconstruction and anatomical double-bundle anterior cruciate ligament reconstruction, using femoral-graft-tibial system under different loads, to mimic a post-operation mechanical motion. The three-dimensional finite-element models for normal ligament and two surgical methods were applied. A vertical force simulating daily walking was performed on the models to assess the interfacial stresses and displacements of intra-articular tissues and ligaments. The evaluation results mainly included the stress of each part of ligament and meniscus. The stress values of different parts of three models were extracted and compared.

RESULTS

The stress of ligament/graft at femoral side of three finite-element models was significantly higher than at tibial side, while the highest level was observed in single-bundle reconstruction finite-element model. With the increase of force, the maximum stress in the medial (7.1-7.1 MPa) and lateral (4.9-7.4 MPa) meniscus of single-bundle reconstruction finite-element model shifted from the anterior horn to the central area (p = 0.0161, 0.0479, respectively). The stress was shown to be at a lower level at femoral side and posterior cruciate ligament of intra-knee in two reconstruction finite-element models than that in normal finite-element models, while presented higher level at the tibial side than normal knee (p = 0.3528). The displacement of the femoral side and intra-knee areas in reconstruction finite-element models was greater than that in normal finite-element model (p = 0.0855).

CONCLUSION

Compared with the single-bundle technique, the graft of double-bundle anterior cruciate ligament reconstruction has better stress dissipation effect and can prevent postoperative meniscus tear more effectively.

Biomechanical effects of medial meniscus radial tears on the knee joint during gait: A concurrent finite element musculoskeletal framework investigation

The biomechanical variation in the knee during walking that accompanies medial meniscal radial tears stemming from knee osteoarthritis (OA) has not been explored. This study introduced a finite element musculoskeletal model using concurrent lower limb musculoskeletal dynamics and knee joint finite element analysis in a single framework and expanded the models to include knees with medial meniscal radial tears and total medial meniscectomy. The radial tears involved three locations: anterior horn, midbody, and posterior horn with grades of 33%, 50%, and 83% of the meniscus width. The shear and hoop stresses of the tear meniscus and tibial cartilage contact load, accompanying tears, and postmeniscectomy were evaluated during the stance phase of the gait cycle using the models. In the 83% width midbody tear group, shear stress at the end of the tear was significantly greater than in the intact meniscus and other tear groups, and the maximum shear stress was increased by 310% compared to the intact meniscus. A medial meniscus radial tear has a much smaller effect on the tibial cartilage load (even though in the 83% width tear, the cartilage/total load ratio increased by only 9%). However, the contact force on the tibial cartilage with total postmeniscectomy was increased by 178.93% compared with a healthy intact meniscus, and the peak contact pressure after meniscectomy increased from 11.94 to 12.45 MPa to 17.64 and 13.76 MPa, at the maximum weight acceptance and push-off, respectively. Our study shows that radial tears with larger medial meniscus widths are prone to high stress concentrations at the end of the tears, leading to the potential risk of complete meniscal rupture. Furthermore, although the tears did not change the cartilage load distribution, they disrupted the circumferential stress-transmitting function of the meniscus, thus greatly increasing the likelihood of the onset of knee OA. The significant increase in the tibial cartilage load with total postmeniscectomy indicates a potential risk of OA flare-ups. This study contributes to a better understanding of meniscal tear-induced OA biomechanical changes during human activities and offers some potential directions for surgical guidance of meniscectomies and the prophylaxis and treatment of OA.

A developed multibody knee model for unloading knee with cartilage penetration depth control

Unloader knee braces could relieve pain by decreasing the medial knee loading. Particularly for knee osteoarthritis (KOA) patients, this study investigates the relevance of the knee model after identifying the most influential parameter. Since KOA causes the cartilage in a joint to lose its elasticity and thickness, the lack of normal bone-to-bone separation can be painful. We believe that cartilage penetration depth control is an impactful strategy in this research. Moreover, the knee contact force in KOA is fewer than in healthy knees, confirming that the contact force control cannot be a straight factor. Therefore, a biomechanical human knee model is developed, and a generic procedure for dynamic analysis of contact problems in combination with the musculoskeletal model is introduced. The developed model includes the geometric expression of collision curves and an algorithm for determining collision points. This presentation addresses cartilage penetration depth and contact force calculation through nonlinear discontinuous contact law. In view of this, femur and tibia’s relative motion is analyzed through the combined collision reactions of cartilage and bone in the knee. In the simulation, maximum penetration depth in a healthy knee is reported to be 0.795 mm, while in a 75% KOA is 0.521 mm, including 0.5 mm cartilage-cartilage contact and 0.021 mm bone-bone contact. The top unloading 852 N is achieved, reducing penetration depth to 0.45 mm, avoiding bone-bone contact. This proposed procedure with low computation gives us a suitable analysis method for designing knee assistive devices.

Techniques to determine knee joint contact forces during squatting: A systematic review

This review article provides an overview of techniques used to determine human knee joint contact forces during squatting. The main two approaches are experimental and theoretical. Thigh calf contact has a significant effect on knee forces and should not be neglected. In this study, data were searched electronically and organized by techniques to find knee joint contact force during squatting theoretically and experimentally. There was a large variation in peak tibiofemoral (CV = 0.45) and patellofemoral (CV = 0.38) contact forces predicted theoretically. However, very little variation was observed between peak tibiofemoral contact forces (CV = 0.12) measured in vivo experimentally but measured knee joint force is available up to a limited knee flexion angle. There was a reduction in knee joint contact forces due to thigh calf contact. Literature of knee joint contact force prediction theoretically during squatting incorporating thigh calf contact force is very limited.

A Parameter Sensitivity Analysis on Multiple Finite Element Knee Joint Models

The reproducibility of computational knee joint modeling is questionable, with models varying depending on the modeling team. The influence of model variations on simulation outcomes should be investigated, since knowing the sensitivity of the model outcomes to model parameters could help determine which parameters to calibrate and which parameters could potentially be standardized, improving model reproducibility. Previous sensitivity analyses on finite element knee joint models have typically used one model, with a few parameters and ligaments represented as line segments. In this study, a parameter sensitivity analysis was performed using multiple finite element knee joint models with continuum ligament representations. Four previously developed and calibrated models of the tibiofemoral joint were used. Parameters of the ligament and meniscus material models, the cartilage contact formulation, the simulation control and the rigid cylindrical joints were studied. Varus-valgus simulations were performed, changing one parameter at a time. The sensitivity on model convergence, valgus kinematics, articulating cartilage contact pressure and contact pressure location were investigated. A scoring system was defined to categorize the parameters as having a “large,” “medium” or “small” influence on model output. Model outcomes were sensitive to the ligament prestretch factor, Young’s modulus and attachment condition parameters. Changes in the meniscus horn stiffness had a “small” influence. Of the cartilage contact parameters, the penalty factor and Augmented Lagrangian setting had a “large” influence on the cartilage contact pressure. In the rigid cylindrical joint, the largest influence on the outcome parameters was found by the moment penalty parameter, which caused convergence issues. The force penalty and gap tolerance had a “small” influence at most. For the majority of parameters, the sensitivity was model-dependent. For example, only two models showed convergence issues when changing the Quasi-Newton update method. Due to the sensitivity of the model parameters being model-specific, the sensitivity of the parameters found in one model cannot be assumed to be the same in other models. The sensitivity of the model outcomes to ligament material properties confirms that calibration of these parameters is critical and using literature values may not be appropriate.

Evaluation of anterior cruciate ligament surgical reconstruction through finite element analysis

Anterior cruciate ligament (ACL) tear is one of the most common knee injuries. The ACL reconstruction surgery aims to restore healthy knee function by replacing the injured ligament with a graft. Proper selection of the optimal surgery parameters is a complex task. To this end, we developed an automated modeling framework that accepts subject-specific geometries and produces finite element knee models incorporating different surgical techniques. Initially, we developed a reference model of the intact knee, validated with data provided by the Open Knee(s) project. This helped us evaluate the effectiveness of estimating ligament stiffness directly from MRI. Next, we performed a plethora of “what-if” simulations, comparing responses with the reference model. We found that (a) increasing graft pretension and radius reduces relative knee displacement, (b) the correlation of graft radius and tension should not be neglected, (c) graft fixation angle of 20\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document}∘ can reduce knee laxity, and (d) single-versus double-bundle techniques demonstrate comparable performance in restraining knee translation. In most cases, these findings confirm reported values from comparative clinical studies. The numerical models are made publicly available, allowing for experimental reuse and lowering the barriers for meta-studies. The modeling approach proposed here can complement orthopedic surgeons in their decision-making.

Towards Tailored Rehabilitation by Implementation of a Novel Musculoskeletal Finite Element Analysis Pipeline

Tissue-level mechanics (e.g., stress and strain) are important factors governing tissue remodeling and development of knee osteoarthritis (KOA), and hence, the success of physical rehabilitation. To date, no clinically feasible analysis toolbox has been introduced and used to inform clinical decision making with subject-specific in-depth joint mechanics of different activities. Herein, we utilized a rapid state-of-the-art electromyography-assisted musculoskeletal finite element analysis toolbox with fibril-reinforced poro(visco)elastic cartilages and menisci to investigate knee mechanics in different activities. Tissue mechanical responses, believed to govern collagen damage, cell death, and fixed charge density loss of proteoglycans, were characterized within 15 patients with KOA while various daily activities and rehabilitation exercises were performed. Results showed more inter-participant variation in joint mechanics during rehabilitation exercises compared to daily activities. Accordingly, the devised workflow may be used for designing subject-specific rehabilitation protocols. Further, results showed the potential to tailor rehabilitation exercises, or assess capacity for daily activity modifications, to optimally load knee tissue, especially when mechanically-induced cartilage degeneration and adaptation are of interest.

An EMG-assisted muscle-force driven finite element analysis pipeline to investigate joint- and tissue-level mechanical responses in functional activities: towards a rapid assessment toolbox

Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising MS-FE models to research applications with few participants and makes the models impractical for clinical assessments. Also, these previously developed MS-FE models have not been used to assess activities other than gait. This study introduces and verifies a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography- (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was verified by comparing the estimated muscle activations and joint mechanics to existing experimental data. To determine the importance of EMG-assisted MS approach, results were compared to those from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments compared to the static-optimization-based MS-FE pipeline. Importantly, the developed pipeline showed great potential as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA. The template FE model of the study is freely available here.

Axial alignment is a critical regulator of knee osteoarthritis

Although osteoarthritis (OA), a leading cause of disability, has been associated with joint malalignment, scientific translational evidence for this link is lacking. In a clinical case study, we provide evidence of osteochondral recovery upon unloading symptomatic isolated medial tibiofemoral knee OA associated with varus malalignment. By mapping response correlations at high resolution, we identify spatially complex degenerative changes in cartilage after overloading in a clinically relevant ovine model. We further report that unloading diminishes OA cartilage degeneration and alterations of critical parameters of the subchondral bone plate in a similar topographic fashion. Last, therapeutic unloading shifted the articular cartilage and subchondral bone phenotype to normal and restored several physiological correlations disturbed in neutral and varus OA, suggesting a protective effect on the integrity of the entire osteochondral unit. Collectively, these findings identify modifiable trajectories with considerable translational potential to reduce the burden of human OA.

Apparatus for In Vivo Knee Laxity Assessment Using High-Speed Stereo Radiography

Computational modeling is of growing importance in orthopedics and biomechanics as a tool to understand differences in pathology and predict outcomes from surgical interventions. However, the computational models of the knee have historically relied on in vitro data to create and calibrate model material properties due to the unavailability of accurate in vivo data. This work demonstrates the design and use of a custom device to quantify anterior-posterior (AP) and internal-external (IE) in vivo knee laxity, with an accuracy similar to existing in vitro methods. The device uses high-speed stereo radiography (HSSR) tracking techniques to accurately measure the resulting displacements of the femur, tibia, and patella bones during knee laxity assessment at multiple loads and knee flexion angles. The accuracy of the knee laxity apparatus was determined by comparing laxity data from two cadaveric specimens between the knee laxity apparatus and an existing in vitro robotic knee joint simulator. The accuracy of the knee laxity apparatus was within 1 mm (0.04 in.) for AP and 2.5 deg for IE. Additionally, two living subjects completed knee laxity testing to confirm the laboratory use of the novel apparatus. This work demonstrates the ability to use custom devices in HSSR to collect accurate data, in vivo, for calibration of computational models.

Total Knee Replacement: Subject-Specific Modeling, Finite Element Analysis, and Evaluation of Dynamic Activities

This study presents a semi-automatic framework to create subject-specific total knee replacement finite element models, which can be used to analyze locomotion patterns and evaluate knee dynamics. In recent years, much scientific attention was attracted to pre-clinical optimization of customized total knee replacement operations through computational modeling to minimize post-operational adverse effects. However, the time-consuming and laborious process of developing a subject-specific finite element model poses an obstacle to the latter. One of this work's main goals is to automate the finite element model development process, which speeds up the proposed framework and makes it viable for practical applications. This pipeline's reliability was ratified by developing and validating a subject-specific total knee replacement model based on the 6th SimTK Grand Challenge data set. The model was validated by analyzing contact pressures on the tibial insert in relation to the patient's gait and analysis of tibial contact forces, which were found to be in accordance with the ones provided by the Grand Challenge data set. Subsequently, a sensitivity analysis was carried out to assess the influence of modeling choices on tibial insert's contact pressures and determine possible uncertainties on the models produced by the framework. Parameters, such as the position of ligament origin points, ligament stiffness, reference strain, and implant-bone alignment were used for the sensitivity study. Notably, it was found that changes in the alignment of the femoral component in reference to the knee bones significantly affect the load distribution at the tibiofemoral joint, with an increase of 206.48% to be observed at contact pressures during 5° internal rotation. Overall, the models produced by this pipeline can be further used to optimize and personalize surgery by evaluating the best surgical parameters in a simulated manner before the actual surgery.

Osteoarthritis year in review 2020: mechanics

The mechanical environment of the joint during dynamic activity plays a significant role in osteoarthritis processes. Understanding how the magnitude, pattern and duration of joint-specific loading features contribute to osteoarthritis progression and response to treatment is a topic of on-going relevance. This narrative review synthesizes evidence from recent papers that have contributed to knowledge related to three identified emerging subthemes: 1) the role of the joint mechanical environment in osteoarthritis pathogenesis, 2) joint biomechanics as an outcome to arthroplasty treatment of osteoarthritis, and 3) methodological trends for advancing our knowledge of the role of biomechanics in osteoarthritis. Rather than provide an exhaustive review of a broad area of research, we have focused on evidence this year related to these subthemes. New research this year has indicated significant interest in using biomechanics investigations to understand structural vs clinical progression of osteoarthritis, the role and interaction in the three-dimensional loading environment of the joint, and the contribution of muscle activation and forces to osteoarthritis progression. There is ongoing interest in understanding how patient variability with respect to gait biomechanics influences arthroplasty surgery outcomes, and subgroup analyses have provided evidence for the potential utility in tailored treatment approaches. Finally, we are seeing a growing trend in the application of translational biomechanics tools such as wearable inertial measurement units for improved integration of biomechanics into clinical decision-making and outcomes assessment for osteoarthritis.

Human locomotion with reinforcement learning using bioinspired reward reshaping strategies

Recent learning strategies such as reinforcement learning (RL) have favored the transition from applied artificial intelligence to general artificial intelligence. One of the current challenges of RL in healthcare relates to the development of a controller to teach a musculoskeletal model to perform dynamic movements. Several solutions have been proposed. However, there is still a lack of investigations exploring the muscle control problem from a biomechanical point of view. Moreover, no studies using biological knowledge to develop plausible motor control models for pathophysiological conditions make use of reward reshaping. Consequently, the objective of the present work was to design and evaluate specific bioinspired reward function strategies for human locomotion learning within an RL framework. The deep deterministic policy gradient (DDPG) method for a single-agent RL problem was applied. A 3D musculoskeletal model (8 DoF and 22 muscles) of a healthy adult was used. A virtual interactive environment was developed and simulated using opensim-rl library. Three reward functions were defined for walking, forward, and side falls. The training process was performed with Google Cloud Compute Engine. The obtained outcomes were compared to the NIPS 2017 challenge outcomes, experimental observations, and literature data. Regarding learning to walk, simulated musculoskeletal models were able to walk from 18 to 20.5 m for the best solutions. A compensation strategy of muscle activations was revealed. Soleus, tibia anterior, and vastii muscles are main actors of the simple forward fall. A higher intensity of muscle activations was also noted after the fall. All kinematics and muscle patterns were consistent with experimental observations and literature data. Regarding the side fall, an intensive level of muscle activation on the expected fall side to unbalance the body was noted. The obtained outcomes suggest that computational and human resources as well as biomechanical knowledge are needed together to develop and evaluate an efficient and robust RL solution. As perspectives, current solutions will be extended to a larger parameter space in 3D. Furthermore, a stochastic reinforcement learning model will be investigated in the future in scope with the uncertainties of the musculoskeletal model and associated environment to provide a general artificial intelligence solution for human locomotion learning. Graphical abstract.

12 Degrees of Freedom Muscle Force Driven Fibril-Reinforced Poroviscoelastic Finite Element Model of the Knee Joint

Accurate knowledge of the joint kinematics, kinetics, and soft tissue mechanical responses is essential in the evaluation of musculoskeletal (MS) disorders. Since in vivo measurement of these quantities requires invasive methods, musculoskeletal finite element (MSFE) models are widely used for simulations. There are, however, limitations in the current approaches. Sequentially linked MSFE models benefit from complex MS and FE models; however, MS model's outputs are independent of the FE model calculations. On the other hand, due to the computational burden, embedded (concurrent) MSFE models are limited to simple material models and cannot estimate detailed responses of the soft tissue. Thus, first we developed a MSFE model of the knee with a subject-specific MS model utilizing an embedded 12 degrees of freedom (DoFs) knee joint with elastic cartilages in which included both secondary kinematic and soft tissue deformations in the muscle force estimation (inverse dynamics). Then, a muscle-force-driven FE model with fibril-reinforced poroviscoelastic cartilages and fibril-reinforced poroelastic menisci was used in series to calculate detailed tissue mechanical responses (forward dynamics). Second, to demonstrate that our workflow improves the simulation results, outputs were compared to results from the same FE models which were driven by conventional MS models with a 1 DoF knee, with and without electromyography (EMG) assistance. The FE model driven by both the embedded and the EMG-assisted MS models estimated similar results and consistent with experiments from literature, compared to the results estimated by the FE model driven by the MS model with 1 DoF knee without EMG assistance.