Redistribution of knee stress using laterally wedged insole intervention: Finite element analysis of knee-ankle-foot complex

The effect of gait modification on the response of medial meniscus extrusion during gait in patients with knee osteoarthritis

BACKGROUND

An increase in medial meniscus extrusion during weight-bearing conditions is associated with the progression of medial knee osteoarthritis (OA). Toe-out gait modification has been known to reduce the knee adduction moment (KAM); however, its effect on reducing the increase in medial meniscus extrusion in patients with knee OA remains unclear.

RESEARCH QUESTION

To (1) evaluate the effect of toe-out gait on the increase in medial meniscus extrusion and the KAM in patients with medial knee OA and (2) investigate the synergetic effect of lateral wedge insoles in combination with toe-out gait in determining the most effective intervention for reducing medial meniscus extrusion during gait.

METHODS

Twenty-five patients with medial knee OA were enrolled in this study. Participants walked under four conditions: normal gait, toe-out gait, normal gait with lateral wedge insoles, and toe-out gait with lateral wedge insoles. Medial meniscus extrusion and KAM peaks during gait were measured using ultrasound and a three-dimensional motion analysis system in each condition. These parameters were compared among the four conditions using repeated measures analysis of variance.

RESULTS

The increase in medial meniscus extrusion and the second KAM peak were significantly lower in all interventions compared with those observed during normal gait. However, there was no significant difference among the interventions.

SIGNIFICANCE

This study suggested that toe-out gait reduces the increase in medial meniscus extrusion and is associated with the reduction of the second KAM peak. However, no synergistic effect of lateral wedge insoles and toe-out gait was observed.

Longitudinal Relationship Between Tibiofemoral Contact Stress at Baseline and Worsening of Knee Pain Over 84 Months in the Multicenter Osteoarthritis Study

OBJECTIVE

The aim of the study was to determine whether tibiofemoral contact stress predicts risk for worsening knee pain over 84 ms in adults aged 50-79 yrs with or at elevated risk for knee osteoarthritis.

DESIGN

Baseline tibiofemoral contact stress was estimated using discrete element analysis. Other baseline measures included weight, height, hip-knee-ankle alignment, Kellgren-Lawrence grade, and Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. Logistic regression models assessed the association between baseline contact stress and 84-mo worsening of Western Ontario and McMaster Universities Osteoarthritis Index pain subscale.

RESULTS

Data from the dominant knee (72.6% Kellgren-Lawrence grade 0/1 and 27.4% Kellgren-Lawrence grade ≥ 2) of 208 participants (64.4% female, mean ± SD body mass index = 29.6 ± 5.1 kg/m 2 ) were analyzed. Baseline mean and peak contact stress were 3.3 ± 0.9 and 9.4 ± 4.3 MPa, respectively. Forty-seven knees met the criterion for worsening pain. The highest tertiles in comparison with the lowest tertiles of mean (odds ratio [95% confidence interval] = 2.47 [1.03-5.95], P = 0.04) and peak (2.49 [1.03-5.98], P = 0.04) contact stress were associated with worsening pain at 84 mos, after adjustment for age, sex, race, clinic site, and baseline pain. Post hoc sensitivity analyses including adjustment for body mass index and hip-knee-ankle alignment attenuated the effect.

CONCLUSIONS

These findings suggest that elevated tibiofemoral contact stress can predict the development of worsening of knee pain.

A Review of Finite Element Models of Ligaments in the Foot and Considerations for Practical Application

PURPOSE

Finite element (FE) modeling has been used as a research tool for investigating underlying ligaments biomechanics and orthopedic applications. However, FE models of the ligament in the foot have been developed with various configurations, mainly due to their complex 3D geometry, material properties, and boundary conditions. Therefore, the purpose of this review was to summarize the current state of finite element modeling approaches that have been used in the ?eld of ligament biomechanics, to discuss their applicability to foot ligament modeling in a practical setting, and also to acknowledge current limitations and challenges.

METHODS

A comprehensive literature search was performed. Each article was analyzed in terms of the methods used for: (a) ligament geometry, (b) material property, (c) boundary and loading condition related to its application, and (d) model verification and validation.

RESULTS

Of the reviewed studies, 80% of the studies used simplified representations of ligament geometry, the non-linear mechanical behavior of ligaments was taken into account in only 19.2% of the studies, 33% of included studies did not include any kind of validation of the FE model.

CONCLUSION

Further refinement in the functional modeling of ligaments, the micro-structure level characteristics, nonlinearity, and time-dependent response, may be warranted to ensure the predictive ability of the models.

Magnetic Resonance Imaging-based biomechanical simulation of cartilage: A systematic review

MRI-based mathematical and computational modeling studies can contribute to a better understanding of the mechanisms governing cartilage's mechanical performance and cartilage disease. In addition, distinct modeling of cartilage is needed to optimize artificial cartilage production. These studies have opened up the prospect of further deepening our understanding of cartilage function. Furthermore, these studies reveal the initiation of an engineering-level approach to how cartilage disease affects material properties and cartilage function. Aimed at researchers in the field of MRI-based cartilage simulation, research articles pertinent to MRI-based cartilage modeling were identified, reviewed, and summarized systematically. Various MRI applications for cartilage modeling are highlighted, and the limitations of different constitutive models used are addressed. In addition, the clinical application of simulations and studied diseases are discussed. The paper's quality, based on the developed questionnaire, was assessed, and out of 79 reviewed papers, 34 papers were determined as high-quality. Due to the lack of the best constitutive models for various clinical conditions, researchers may consider the effect of constitutive material models on the cartilage disease simulation. In the future, research groups may incorporate various aspects of machine learning into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification, such as gait analysis.

Finite Element Analysis of a Novel Approach for Knee and Ankle Protection during Landing

There is a high risk of serious injury to the lower extremities during a human drop landing. Prophylactic knee and ankle braces are commonly used to reduce injury by restraining the motion of joints. However, braces that restrain joint range of motion (ROM) may have detrimental effects on the user’s kinematical performance and joint function. The present study aimed to propose a novel set of double-joint braces and to evaluate its protective performance in terms of the ankle and knee. Accordingly, the finite element method was performed to investigate the biomechanical responses of the ankle and knee in braced and unbraced conditions. The results showed that the semi-rigid support at the ankle joint can share the high impact force that would otherwise be inflicted on one’s lower extremity, thereby reducing the peak stress on the inferior articular surface of the tibia, menisci, and articular cartilages, as well as the horizontal force on the talus. Moreover, with knee bending, the elongated spring component at the knee joint can convert the impact kinetic energy into elastic potential energy of the spring; meanwhile, the retractive force generated by the spring also provides a more balanced interaction between the menisci and articular cartilages. This biomechanical analysis can accordingly provide inspiration for new approaches to place human lower extremities at lower risk during landings.

Random Forest enhancement using improved Artificial Fish Swarm for the medial knee contact force prediction

Knee contact force (KCF) is an important factor to evaluate the knee joint function for the patients with knee joint impairment. However, the KCF measurement based on the instrumented prosthetic implants or inverse dynamics analysis is limited due to the invasive, expensive price and time consumption. In this work, we propose a KCF prediction method by integrating the Artificial Fish Swarm and the Random Forest algorithm. First, we train a Random Forest to learn the nonlinear relation between gait parameters (input) and contact pressures (output) based on a dataset of three patients instrumented with knee replacement. Then, we use the improved artificial fish group algorithm to optimize the main parameters of the Random Forest based KCF prediction model. The extensive experiments verify that our method can predict the medial knee contact force both before and after the intervention of gait patterns, and the performance outperforms the classical multi-body dynamics analysis and artificial neural network model.

The optimal degree of lateral wedge insoles for reducing knee joint load: a systematic review and meta-analysis

Background

Lateral wedge insoles are traditionally used to reduce the adduction moment that crosses the knee during walking in people with medial knee osteoarthritis. However, the best degree to reduce knee joint load is not yet well established.

Methods

Electronic databases were searched from their inception until May 2017. Included studies reported on the immediate biomechanical effects of different degrees of lateral wedge insoles during walking in people with knee osteoarthritis. The main measures of interest relating to the biomechanics were the first and second peak of external knee adduction moment and knee adduction angular impulse. For the comparison of the biomechanical effects of different degrees of insoles, the studies were divided in three subgroups: insoles with a degree higher than 0° and equal to or lower than 5°; insoles higher than 5° and equal to or lower than 9°; and insoles higher than 9°. Eligible studies were pooled using random-effects meta-analysis.

Results

Fifteen studies with a total of 415 participants met all eligibility criteria and were included in the final review and meta-analysis. The overall effect suggests that lateral wedge insoles resulted in a statistically significant reduction in the first peak (standardized mean difference [SMD] -0.25; 95% confidence interval [CI] -0.36, - 0.13; P < 0.001), second peak (SMD -0.26 [95% CI -0.48, - 0.04]; P = 0.02) and knee adduction angular impulse (SMD -0.17 [95% CI -0.31, - 0.03]; P = 0.02). The test of subgroups found no statistically significant differences.

Conclusion

Systematic review and meta-analysis suggests that lateral wedge insoles cause an overall slight reduction in the biomechanical parameters. Higher degrees do not show higher reductions than lower degrees. Prior analysis of biomechanical parameters may be a valid option for selecting the optimal angle of wedge that best fits in knee osteoarthritis patients with the lowest possible degree.

Finite element analysis of knee and ankle joint during gait based on motion analysis

Contact pressures in the articular cartilage during gait affect injuries and the degenerative arthritis of knee and ankle joints. However, only contact forces at the knee and ankle joints during gait can be estimated by using a rigid body dynamic model. The contact pressure distribution can be obtained quantitatively for a static posture by using finite element (FE) analysis in most cases. The purpose of this study is to develop a new method to obtain the contact pressure distribution at the knee and ankle joints during gait by integrating FE analysis with rigid body dynamic analysis. In this method, a reference FE model of the lower extremity is constructed first and is then transformed to each stance phase of the gait obtained from dynamic analysis by using homogeneous transformation. The muscle forces and ground reaction force (GRF) during gait obtained from the dynamic analysis were used as loading conditions for FE analysis. Finally, the contact pressure distribution at the tibia plateau cartilage and talus cartilage were estimated at the 1st peak, mid-stance, and the 2nd peak at the same time. The present method can provide the contact pressure distribution at the knee and ankle joints over the entire gait.

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.

Comparative Biomechanical Analysis of Stress-Strain State of the Elbow Joint After Displaced Radial Head Fractures

Radial head fractures are becoming a major public health problem and are an increasingly important target for both clinical and mechanical researchers. In this work, comparative biomechanical analyses of the stress–strain state of a healthy elbow joint and elbow joints with radial head compression from 2 to 5 mm due to injury are performed. Three-dimensional models of the elbow joint with cartilage surfaces and ligaments were constructed based on the results of computed tomography. This study is focused on an elbow joint range of motion ranging from 0° to 120° flexion. Analysis of the stress–strain state of cartilage and ligaments under the influence of functional loads is conducted using a finite element method (FEM) and the ABAQUS software package. The results show that with increasing compression of the radial head, contact stress increases at the olecranon, which can lead to cartilage damage. Analysis of displacement shows that compression of the radial head during full extension of the elbow joint leads to an increased humeral shift from 1.14° ± 0.22 in the healthy joint to 10.3° ± 2.13 during 5-mm compression of the radial head. Mathematical modeling performed in this study proved that reducing the height of the radial head and the contact area between the radial head and the humeral head led to increased medial collateral ligament stresses of up to 36 ± 3.8 MPa. This work confirmed that the head of the radius is the main stabilizing structure of the elbow joint and that the medial collateral ligament is the second structure responsible for valgus stability of the elbow joint.

Wedged Insoles and Gait in Patients with Knee Osteoarthritis: A Biomechanical Review

The study of gait biomechanics in individuals with knee osteoarthritis has become widespread, especially in regards to the knee adduction moment-a variable commonly believed to be associated with knee osteoarthritis progression. Unfortunately, this variable is often studied clinically without considering how it is derived, or what it means in a mechanical context. The use of footwear for knee osteoarthritis management has received much attention as well. However, in many cases, footwear is studied without regard for the mechanical effects they actually induce on the patient. Therefore, this review aims to summarize the current state of knowledge in regards to knee osteoarthritis gait and footwear biomechanics, by taking a step back to review the foundations of these two research areas. First, an overview of the calculation of the knee adduction moment is provided, along with mechanical considerations. Then, this is used to discuss current evidence for wedged insoles and highlight knowledge gaps. The intent was to place this mechanical information in a clinically-oriented framework for approachability by scientists, engineers and clinicians alike. Based on this discussion, areas for future investigation are proposed.

Surrogate modeling of deformable joint contact using artificial neural networks

Deformable joint contact models can be used to estimate loading conditions for cartilage-cartilage, implant-implant, human-orthotic, and foot-ground interactions. However, contact evaluations are often so expensive computationally that they can be prohibitive for simulations or optimizations requiring thousands or even millions of contact evaluations. To overcome this limitation, we developed a novel surrogate contact modeling method based on artificial neural networks (ANNs). The method uses special sampling techniques to gather input-output data points from an original (slow) contact model in multiple domains of input space, where each domain represents a different physical situation likely to be encountered. For each contact force and torque output by the original contact model, a multi-layer feed-forward ANN is defined, trained, and incorporated into a surrogate contact model. As an evaluation problem, we created an ANN-based surrogate contact model of an artificial tibiofemoral joint using over 75,000 evaluations of a fine-grid elastic foundation (EF) contact model. The surrogate contact model computed contact forces and torques about 1000 times faster than a less accurate coarse grid EF contact model. Furthermore, the surrogate contact model was seven times more accurate than the coarse grid EF contact model within the input domain of a walking motion. For larger input domains, the surrogate contact model showed the expected trend of increasing error with increasing domain size. In addition, the surrogate contact model was able to identify out-of-contact situations with high accuracy. Computational contact models created using our proposed ANN approach may remove an important computational bottleneck from musculoskeletal simulations or optimizations incorporating deformable joint contact models.

Material models and properties in the finite element analysis of knee ligaments: a literature review

Knee ligaments are elastic bands of soft tissue with a complex microstructure and biomechanics, which are critical to determine the kinematics as well as the stress bearing behavior of the knee joint. Their correct implementation in terms of material models and properties is therefore necessary in the development of finite element models of the knee, which has been performed for decades for the investigation of both its basic biomechanics and the development of replacement implants and repair strategies for degenerative and traumatic pathologies. Indeed, a wide range of element types and material models has been used to represent knee ligaments, ranging from elastic unidimensional elements to complex hyperelastic three-dimensional structures with anatomically realistic shapes. This paper systematically reviews literature studies, which described finite element models of the knee, and summarizes the approaches, which have been used to model the ligaments highlighting their strengths and weaknesses.

Application of neural networks for the prediction of cartilage stress in a musculoskeletal system

Traditional finite element (FE) analysis is computationally demanding. The computational time becomes prohibitively long when multiple loading and boundary conditions need to be considered such as in musculoskeletal movement simulations involving multiple joints and muscles. Presented in this study is an innovative approach that takes advantage of the computational efficiency of both the dynamic multibody (MB) method and neural network (NN) analysis. A NN model that captures the behavior of musculoskeletal tissue subjected to known loading situations is built, trained, and validated based on both MB and FE simulation data. It is found that nonlinear, dynamic NNs yield better predictions over their linear, static counterparts. The developed NN model is then capable of predicting stress values at regions of interest within the musculoskeletal system in only a fraction of the time required by FE simulation.