Uncertainty in Muscle–Tendon Parameters can Greatly Influence the Accuracy of Knee Contact Force Estimates of Musculoskeletal Models

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

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

Comparison of biomechanical analysis results using different musculoskeletal models for children with cerebral palsy

Introduction: Musculoskeletal model-based simulations have gained popularity as a tool for analyzing human movement biomechanics. However, when examining the same gait, different models with varying anatomical data and assumptions may produce inconsistent biomechanical results. This inconsistency is particularly relevant for children with cerebral palsy, who often exhibit multiple pathological gait patterns that can impact model outputs. Methods: The aim of this study was to investigate the effect of selecting musculoskeletal models on the biomechanical analysis results in children with cerebral palsy. Gait data were collected from multiple participants at slow, medium, and fast velocities. Joint kinematics, joint dynamics, and muscle activation were calculated using six popular musculoskeletal models within a biomechanical simulation environment. Results: The degree of inconsistency, measured as the root-mean-square deviation, in kinematic and kinetic results produced by the different models ranged from 4% to 40% joint motion range and 0%-28% joint moment range, respectively. The correlation between the results of the different models (both kinematic and kinetic) was good (R> 0.85, P < 0.01), with a stronger correlation observed in the kinetic results. Four of the six models showed a positive correlation between the simulated muscle activation of rectus femoris and the surface EMG, while all models exhibited a positive correlation between the activation of medial gastrocnemius and the surface EMG (P < 0.01). Discussion: These results provide insights into the consistency of model results, factors influencing consistency, characteristics of each model's outputs, mechanisms underlying these characteristics, and feasible applications for each model. By elucidating the impact of model selection on biomechanical analysis outcomes, this study advances the field's understanding of musculoskeletal modeling and its implications for clinical gait analysis model decision-making in children with cerebral palsy.

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

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