Workflow assessing the effect of gait alterations on stresses in the medial tibial cartilage - combined musculoskeletal modelling and finite element analysis

Sensitivity of knee cartilage biomechanics in finite element analysis to selected Musculoskeletal models

Knee joint kinematics and kinetics analyzed by musculoskeletal (MS) modeling are often utilized in finite element (FE) models, estimating tissue-level mechanical responses. We compared knee cartilage stresses, strains, and centers of pressure of FE models driven by two widely used MS models, implemented in AnyBody and OpenSim. Minor discrepancies in the results were observed between the models. AnyBody-driven FE models showed slightly higher stresses in the medial tibial cartilage, while OpenSim-driven FE models estimated more anterior and lateral center of pressure. Recognizing these differences in the MS-FE models is important to ensure reliable analysis of cartilage mechanics and failure and simulation of rehabilitation.

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.

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.

Validation and evaluation of subject-specific finite element models of the pediatric knee

Finite element (FE) models have been widely used to investigate knee joint biomechanics. Most of these models have been developed to study adult knees, neglecting pediatric populations. In this study, an atlas-based approach was employed to develop subject-specific FE models of the knee for eight typically developing pediatric individuals. Initially, validation simulations were performed at four passive tibiofemoral joint (TFJ) flexion angles, and the resulting TFJ and patellofemoral joint (PFJ) kinematics were compared to corresponding patient-matched measurements derived from magnetic resonance imaging (MRI). A neuromusculoskeletal-(NMSK)-FE pipeline was then used to simulate knee biomechanics during stance phase of walking gait for each participant to evaluate model simulation of a common motor task. Validation simulations demonstrated minimal error and strong correlations between FE-predicted and MRI-measured TFJ and PFJ kinematics (ensemble average of root mean square errors < 5 mm for translations and < 4.1° for rotations). The FE-predicted kinematics were strongly correlated with published reports (ensemble average of Pearson's correlation coefficients (ρ) > 0.9 for translations and ρ > 0.8 for rotations), except for TFJ mediolateral translation and abduction/adduction rotation. For walking gait, NMSK-FE model-predicted knee kinematics, contact areas, and contact pressures were consistent with experimental reports from literature. The strong agreement between model predictions and experimental reports underscores the capability of sequentially linked NMSK-FE models to accurately predict pediatric knee kinematics, as well as complex contact pressure distributions across the TFJ articulations. These models hold promise as effective tools for parametric analyses, population-based clinical studies, and enhancing our understanding of various pediatric knee injury mechanisms. They also support intervention design and prediction of surgical outcomes in pediatric populations.

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.

Finite element analysis of a healthy knee joint at deep squatting for the study of tibiofemoral and patellofemoral contact

Background

In non-western countries, deep squatting is a daily activity, and prolonged deep squatting is common among occupational squatters. Household tasks, taking a bath, socializing, using toilets, and performing religious acts are among the activities frequently carried out while squatting by the Asian population. High knee loading is responsible for a knee injury and osteoarthritis. Finite element analysis is an effective tool to determine stresses on the knee joint.

Methods

Magnetic Resonance Imaging (MRI) and Computed Tomographic (CT) images were acquired of one adult without knee injuries. The CT images were acquired at the fully extended knee and one more set of images was acquired with the knee at a deeply flexed knee position. The MRI was acquired with the fully extended knee. 3-Dimensional models of bones were created using CT and soft tissue using MRI with the help of 3D Slicer software. Kinematics and finite element analysis of the knee was performed for standing and deep squatting posture using Ansys Workbench 2022.

Results

High peak stresses were observed at deep squatting compared to standing along with the reduction in the contact area. Peak von Mises stresses on femoral cartilage, tibial cartilage, patellar cartilage, and meniscus were increased from 3.3 MPa to 19.9 MPa, 2.9 MPa to 12.4 MPa, 1.5 MPa to 16.7 MPa and 15.8 MPa to 32.8 MPa respectively during deep squatting. Posterior translation of 7.01 mm, and 12.58 mm was observed for medial and lateral femoral condyle respectively from full extension to 153° knee flexion.

Conclusions

Increased stresses in the knee joint at deep squat posture may cause cartilage damage. A sustained deep squat posture should be avoided for healthy knee joints. More posterior translations of the medial femoral condyle at higher knee flexion angle warrant further investigation.

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.

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.

Influence of material heterogeneity on the mechanical response of articulated cartilages in a knee joint

Structurally, the articular cartilages are heterogeneous owing to nonuniform distribution and orientation of its constituents. The oversimplification of this soft tissue as a homogeneous material is generally considered in the simulation domain to estimate contact pressure along with other physical responses. Hence, there is a need for investigating knee cartilages for their actual response to external stimuli. In this article, impact of material and geometrical heterogeneity of the cartilage is resolved using well known material models. The findings are compared with conventional homogeneous models. The results indicate vital differences in contact pressure distribution and tissue deformation. Further, this study paves way for standardizing material models to extract maximum information possible for investigating knee mechanics with variable geometry and case specific parameters.

Workflow assessing the effect of Achilles tendon rupture on gait function and metatarsal stress: Combined musculoskeletal modeling and finite element analysis

Achilles tendon rupture (ATR) incidence has increased among badminton players in recent years. The foot internal stress was hard to obtain through experimental testing. The purpose of the current research is to develop a methodology that could improve the finite element model derived foot internal stress prediction for ATR clinical and rehabilitation applications. A subject-specific musculoskeletal model was combined with a 3D finite element model to predict the metatarsal stress. The 80% point during the push-off phase of walking was selected for the comparing between injured and uninjured sides. The surgical repaired Achilles tendon (AT) after 12 months was elongated by 5.5% than the uninjured tendon. At 80% point of stance phase, the ankle plantarflexion angle and AT force decreased by 39.6% and 21.9% on the injured side, respectively. The foot inversion degree increased by 22.9% and was accompanied by the redistribution of metatarsals von Mises stress. The stresses on the fourth and fifth metatarsals were increased by 59.5% and 85.9% on the injured side. The workflow is available to assess musculoskeletal disorders and obtain foot internal stress after ATR. The decreased ankle plantar flexor force may be affected by triceps surae muscle atrophy and weakened force transmission ability of elongated AT. The increased von Mises stress on fourth and fifth metatarsals accompanied by higher foot inversion may increase the ankle lateral sprain injury risk.

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.

A Methodology to Evaluate the Effects of Kinematic Measurement Uncertainties on Knee Ligament Properties Estimated From Laxity Measurements

Ligaments are important joint stabilizers but assessing their mechanical properties remain challenging. We developed a methodology to investigate the effects of kinematic measurement uncertainty during laxity tests on optimization-based estimation of ligament properties. We applied this methodology to a subject-specific knee model with known ligament properties as inputs and compared the estimated to the known knee ligament properties under the influence of noise. Four different sets of laxity tests were simulated with an increasing number of load cases, capturing anterior/posterior, varus/valgus, and internal/external rotation loads at 0 deg and 30 deg of knee flexion. 20 samples of uniform random noise ([-0.5,0.5] mm and degrees) were added to each set and fed into an optimization routine that subsequently estimated the ligament properties based on the noise targets. We found a large range of estimated ligament properties (stiffness ranges of 5.97 kN, 7.64 kN, 8.72 kN, and 3.86 kN; reference strain ranges of 3.11%, 2.53%, 1.88%, and 1.58% for anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), medical collateral ligament (MCL), and lateral collateral ligament (LCL), respectively) for three sets of laxity tests, including up to 22 load cases. A set of laxity tests with 60 load cases kept the stiffness and reference strain ranges below 470 N per unit strain and 0.85%, respectively. These results illustrate that kinematic measurement noise have a large impact on estimated ligament properties and we recommend that future studies assess and report both the estimated ligament properties and the associated uncertainties due to kinematic measurement noise.

A Simulation Case Study of Knee Joint Compressive Stress during the Stance Phase in Severe Knee Osteoarthritis Using Finite Element Method

Background and Objectives: Medial knee osteoarthritis is known to increase the mechanical load on the medial compartment of the knee joint during walking; however, it is not visually understood how much the mechanical load increases nor where in the medial compartment of the knee joint that load is focused. Therefore, we conducted a simulation study to determine the location and amount of the mechanical load in the medial compartment of the knee joint during the stance phase. Materials and Methods: Subject was a patient with right medial knee osteoarthritis. Computed tomography imaging and gait analysis were performed on subject. The CT image of the right knee was calculated using finite element analysis software. Since this software can set the flexion angle arbitrarily while maintaining the nonuniform material properties of the bone region, the model is constructed by matching the knee joint extension image obtained by CT to the loading response phase of gait analysis. The data of muscle exertion tension and vertical ground reaction force were inserted into the knee joint model created from the computed tomography-based finite element method, and the knee joint compressive stress was calculated. Results: With regard to compressive stress, the tibia showed high stress at 4.10 to 5.36 N/mm². The femur showed high stress at 4.00 to 6.48 N/mm². The joint compressive stress on the medial compartment of the knee joint was found to concentrate on the edge of the medial tibial condyle in the medial knee osteoarthritis subject. Conclusions: The measurement method of knee joint compressive stress by computed tomography-based finite element method can visually be a reliable method of measuring joint compressive stress in the medial knee osteoarthritis. This reflects the clinical findings because concentration of stress on the medial knee joint was observed at the medial osteophyte.

Real-Time Prediction of Joint Forces by Motion Capture and Machine Learning

Conventional biomechanical modelling approaches involve the solution of large systems of equations that encode the complex mathematical representation of human motion and skeletal structure. To improve stability and computational speed, being a common bottleneck in current approaches, we apply machine learning to train surrogate models and to predict in near real-time, previously calculated medial and lateral knee contact forces (KCFs) of 54 young and elderly participants during treadmill walking in a speed range of 3 to 7 km/h. Predictions are obtained by fusing optical motion capture and musculoskeletal modeling-derived kinematic and force variables, into regression models using artificial neural networks (ANNs) and support vector regression (SVR). Training schemes included either data from all subjects (LeaveTrialsOut) or only from a portion of them (LeaveSubjectsOut), in combination with inclusion of ground reaction forces (GRFs) in the dataset or not. Results identify ANNs as the best-performing predictor of KCFs, both in terms of Pearson R (0.89-0.98 for LeaveTrialsOut and 0.45-0.85 for LeaveSubjectsOut) and percentage normalized root mean square error (0.67-2.35 for LeaveTrialsOut and 1.6-5.39 for LeaveSubjectsOut). When GRFs were omitted from the dataset, no substantial decrease in prediction power of both models was observed. Our findings showcase the strength of ANNs to predict simultaneously multi-component KCF during walking at different speeds-even in the absence of GRFs-particularly applicable in real-time applications that make use of knee loading conditions to guide and treat patients.

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.

Estimation of joint contact pressure in the index finger using a hybrid finite element musculoskeletal approach

The knowledge of local stress distribution in hand joints is crucial to understand injuries and osteoarthritis occurrence. However, determining cartilage contact stresses remains a challenge, requiring numerical models including both accurate anatomical components and realistic tendon force actuation. Contact forces in finger joints have frequently been calculated but little data is available on joint contact pressures. This study aimed to develop and assess a hybrid biomechanical model of the index finger to estimate in-vivo joint contact pressure during a static maximal strength pinch grip task. A finite element model including bones, cartilage, tendons, and ligaments was developed, with tendon force transmission based on a tendon-pulley system. This model was driven by realistic tendon forces estimated from a musculoskeletal model and motion capture data for six subjects. The hybrid model outputs agreed well with the experimental measurement of fingertip forces and literature data on the physiological distribution of tendon forces through the index finger. Mean contact pressures were 6.9 ± 2.7 MPa, 6.2 ± 1.0 MPa and 7.2 ± 1.3 MPa for distal, proximal interphalangeal and metacarpophalangeal joints, respectively. Two subjects had higher mean contact pressure in the distal joint than in the other two joints, suggesting a mechanical cause for the prevalence of osteoarthritis in the index distal joint. The inter-subject variability in joint contact pressure could be explained by different neuromuscular strategies employed for the task. This first application of an effective hybrid model to the index finger is promising for estimating hand joint stresses under daily grip tasks and simulating surgical procedures.

Constitutive modeling of menisci tissue: a critical review of analytical and numerical approaches

Menisci are fibrocartilaginous disks consisting of soft tissue with a complex biomechanical structure. They are critical determinants of the kinematics as well as the stability of the knee joint. Several studies have been carried out to formulate tissue mechanical behavior, leading to the development of a wide spectrum of constitutive laws. In addition to developing analytical tools, extensive numerical studies have been conducted on menisci modeling. This study reviews the developments of the most widely used continuum models of the meniscus mechanical properties in conjunction with emerging analytical and numerical models used to study the meniscus. The review presents relevant approaches and assumptions used to develop the models and includes discussions regarding strengths, weaknesses, and discrepancies involved in the presented models. The study presents a comprehensive coverage of relevant publications included in Compendex, EMBASE, MEDLINE, PubMed, ScienceDirect, Springer, and Scopus databases. This review aims at opening novel avenues for improving menisci modeling within the framework of constitutive modeling through highlighting the needs for further research directed toward determining key factors in gaining insight into the biomechanics of menisci which is crucial for the elaborate design of meniscal replacements.

Impact of alignment and kinematic variation on resistive moment and dislocation propensity for THA with lipped and neutral liners

Instability and dislocation remain leading indications for revision of total hip arthroplasty (THA). Many studies have addressed the links between implant design and dislocation; however, an understanding of the impact of alignment and kinematic variability on constraint of modern THA constructs to provide joint stability is needed. The objective of this study is to provide objective data to be considered in the treatment algorithm to protect against joint instability. Joint contact and muscle forces were evaluated using musculoskeletal models of THA patients performing activities consistent with posterior and anterior dislocation. Position and joint loads were transferred to a finite element simulation with an experimentally calibrated hip capsule representation, where they were kinematically extrapolated until impingement and eventual dislocation. Cup anteversion and inclination were varied according to clinical measurements, and variation in imposed kinematics was included. The resistive moment provided by the contact force and joint capsule, and overall dislocation rate (dislocations/total simulations) were determined with neutral and lipped acetabular liners. Use of a lipped liner did increase the resistive moment in posterior dislocation, by an average of 5.2 Nm, and the flexion angle at dislocation by 1.4° compared to a neutral liner. There was a reduction in similar magnitude in resistance to anterior dislocation. Increased cup anteversion and inclination, hip abduction and internal rotation all reduced the occurrence of posterior dislocation but increased anterior dislocation. A quantitative understanding of tradeoffs in the dislocation risk inherent to THA construct options is valuable in supporting surgical decision making.

Prediction of patellofemoral joint kinematics and contact through co-simulation of rigid body dynamics and nonlinear finite element analysis

Joint-level rigid body dynamics simulations, when coupled with tissue-level finite element analyses, can simultaneously provide movement and tissue deformation metrics to understand mechanical interactions within the joint on a multi-scale level. In this study, a co-simulation workflow of a joint-level rigid body model that predicts the relative motion as a function of the non-linear cartilage response predicted by a non-linear implicit finite element solver is presented. Predictions are compared to in-vitro measurements (The Open Knee(s) project) in terms of the mean error and level-of-agreement: pressure_error = 0.46 MPa (level-of-agreement, -0.23 - 1.1 MPa); area_error = -89 mm² (level-of-agreement, -280 - 98 mm²) and contact force_error = 93 N (level-of-agreement, 7.8 - 180 N). The automated co-simulation control algorithm enables multiscale coupling between joint and tissue-level models with real-time two-way communication as opposed to the traditional feed-forward approach of multi-scale models.

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

Abnormal mechanical loading is essential in the onset and progression of knee osteoarthritis. Combined musculoskeletal (MS) and finite element (FE) modeling is a typical method to estimate load distribution and tissue responses in the knee joint. However, earlier combined models mostly utilize static-optimization based MS models and muscle force driven FE models typically use elastic materials for soft tissues or analyze specific time points of gait. Therefore, here we develop an electromyography-assisted muscle force driven FE model with fibril-reinforced poro(visco)elastic cartilages and menisci to analyze knee joint loading during the stance phase of gait. Moreover, since ligament pre-strains are one of the important uncertainties in joint modeling, we conducted a sensitivity analysis on the pre-strains of anterior and posterior cruciate ligaments (ACL and PCL) as well as medial and lateral collateral ligaments (MCL and LCL). The model produced kinematics and kinetics consistent with previous experimental data. Joint contact forces and contact areas were highly sensitive to ACL and PCL pre-strains, while those changed less cartilage stresses, fibril strains, and fluid pressures. The presented workflow could be used in a wide range of applications related to the aetiology of cartilage degeneration, optimization of rehabilitation exercises, and simulation of knee surgeries.

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

Abnormal mechanical loading is essential in the onset and progression of knee osteoarthritis. Combined musculoskeletal (MS) and finite element (FE) modeling is a typical method to estimate load distribution and tissue responses in the knee joint. However, earlier combined models mostly utilize static-optimization based MS models and muscle force driven FE models typically use elastic materials for soft tissues or analyze specific time points of gait. Therefore, here we develop an electromyography-assisted muscle force driven FE model with fibril-reinforced poro(visco)elastic cartilages and menisci to analyze knee joint loading during the stance phase of gait. Moreover, since ligament pre-strains are one of the important uncertainties in joint modeling, we conducted a sensitivity analysis on the pre-strains of anterior and posterior cruciate ligaments (ACL and PCL) as well as medial and lateral collateral ligaments (MCL and LCL). The model produced kinematics and kinetics consistent with previous experimental data. Joint contact forces and contact areas were highly sensitive to ACL and PCL pre-strains, while those changed less cartilage stresses, fibril strains, and fluid pressures. The presented workflow could be used in a wide range of applications related to the aetiology of cartilage degeneration, optimization of rehabilitation exercises, and simulation of knee surgeries.

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

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

Accuracy and kinematics consistency of marker-based scaling approaches on a lower limb model: a comparative study with imagery data

Medical images are not typically included in protocol of motion laboratories. Thus, accurate scaling of musculoskeletal models from optoelectronic data are important for any biomechanical analysis. The aim of the current study was to identify a scaling method based on optoelectronic data, inspired from literature, which could offer the best trade-off between accurate geometrical parameters (segment lengths, orientation of joint axes, marker coordinates) and consistent inverse kinematics outputs (kinematic error, joint angles). The methods were applied on 26 subjects and assessed with medical imagery building EOS-based models, considered as a reference. The main contribution of this paper is to show that the marker-based scaling followed by an optimisation of orientation joint axes and markers local coordinates, gives the most consistent scaling and joint angles with EOS-based models. Thus, when a non-invasive mean with an optoelectronic system is considered, a marker-based scaling is preliminary needed to get accurate segment lengths and to optimise joint axes and marker local coordinates to reduce kinematic errors.AbbrevationsAJCAnkle joint centreCKEcumulative kinematic errorDoFdegree of freedomEBEOS-basedHBheight-basedHJChip joint centreKJCknee joint centreMBmarker-basedMSMmusculoskeletal modelsSPMstatistical parametric mappingSTAsoft tissue artifactEB_a.m∗EOS-based with optimised joint axes, and all model markers coordinatesMB_a.m∗marker-based with optimised joint axes, and all model markers coordinatesMB_l.a.mmarker-based with optimised segment lengths, joint axes, and selected model markers coordinatesASISanterior superior illiac spinePSISposterior superior illiac spine.

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.

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.

Neuro-musculoskeletal flexible multibody simulation yields a framework for efficient bone failure risk assessment

Fragility fractures are a major socioeconomic problem. A non-invasive, computationally-efficient method for the identification of fracture risk scenarios under the representation of neuro-musculoskeletal dynamics does not exist. We introduce a computational workflow that integrates modally-reduced, quantitative CT-based finite-element models into neuro-musculoskeletal flexible multibody simulation (NfMBS) for early bone fracture risk assessment. Our workflow quantifies the bone strength via the osteogenic stresses and strains that arise due to the physiological-like loading of the bone under the representation of patient-specific neuro-musculoskeletal dynamics. This allows for non-invasive, computationally-efficient dynamic analysis over the enormous parameter space of fracture risk scenarios, while requiring only sparse clinical data. Experimental validation on a fresh human femur specimen together with femur strength computations that were consistent with literature findings provide confidence in the workflow: The simulation of an entire squat took only 38 s CPU-time. Owing to the loss (16% cortical, 33% trabecular) of bone mineral density (BMD), the strain measure that is associated with bone fracture increased by 31.4%; and yielded an elevated risk of a femoral hip fracture. Our novel workflow could offer clinicians with decision-making guidance by enabling the first combined in-silico analysis tool using NfMBS and BMD measurements for optimized bone fracture risk assessment.

Gait retraining using real-time feedback in patients with medial knee osteoarthritis: Feasibility and effects of a six-week gait training program

BACKGROUND

The knee adduction moment (KAM) is often elevated in medial knee osteoarthritis (KOA). The aim of this study was to evaluate effects on KAM and patient-reported outcomes of a six-week gait training program.

METHODS

Twenty-one patients (61 ± 6 years) with KOA participated in a six-week biofeedback training program to encourage increased toe-in (all patients) and increased step-width (five patients). Patients received real-time visual feedback while walking on an instrumented treadmill. We analysed the effect of the gait modification(s) on peak KAM in week six and three and six months post-training. We also evaluated the effect on pain and functional ability.

RESULTS

Of 21 patients starting the program, 16 completed it with high attendance (15 and 16 respectively) at the three and six month follow-ups. First peak KAM was significantly reduced by up to 14.0% in week six with non-significant reductions of 8.2% and 5.5% at the follow-ups. Functional ability (assessed using the WOMAC questionnaire) improved significantly after the training (eight point reduction, p = 0.04 in week six and nine point reduction, p = 0.04 at six-month follow-up). There was also a trend towards reduction in WOMAC pain (p = 0.06) at follow-up.

CONCLUSIONS

Biofeedback training to encourage gait modifications is feasible and leads to short-term benefits. However, at follow-up, reductions in KAM were less pronounced in some participants suggesting that to influence progression of KOA in the longer term, a permanent regime to reinforce the effects of the training program is needed. Trial number: ISRCTN14687588.

Relationship between knee joint contact forces and external knee joint moments in patients with medial knee osteoarthritis: effects of gait modifications

OBJECTIVE

To evaluate 1) the relationship between the knee contact force (KCF) and knee adduction and flexion moments (KAM and KFM) during normal gait in people with medial knee osteoarthritis (KOA), 2) the effects on the KCF of walking with a modified gait pattern and 3) the relationship between changes in the KCF and changes in the knee moments.

METHOD

We modeled the gait biomechanics of thirty-five patients with medial KOA using the AnyBody Modeling System during normal gait and two modified gait patterns. We calculated the internal KCF and evaluated the external joint moments (KAM and KFM) against it using linear regression analyses.

RESULTS

First peak medial KCF was associated with first peak KAM (R² = 0.60) and with KAM and KFM (R² = 0.73). Walking with both modified gait patterns reduced KAM (P = 0.002) and the medial to total KCF ratio (P < 0.001) at the first peak. Changes in KAM during modified gait were moderately associated with changes in the medial KCF at the first peak (R² = 0.54 and 0.53).

CONCLUSIONS

At the first peak, KAM is a reasonable substitute for the medial contact force, but not at the second peak. First peak KFM is also a significant contributor to the medial KCF. At the first peak, walking with a modified gait reduced the ratio of the medial to total KCF but not the medial KCF itself. To determine the effects of gait modifications on cartilage loading and disease progression, longitudinal studies and individualized modeling, accounting for motion control, would be required.