A subject-specific finite element musculoskeletal framework for mechanics analysis of a total knee replacement

Machine Learning Approaches for 3D Motion Synthesis and Musculoskeletal Dynamics Estimation: A Survey

The inference of 3D motion and dynamics of the human musculoskeletal system has traditionally been solved using physics-based methods that exploit physical parameters to provide realistic simulations. Yet, such methods suffer from computational complexity and reduced stability, hindering their use in computer graphics applications that require real-time performance. With the recent explosion of data capture (mocap, video) machine learning (ML) has started to become popular as it is able to create surrogate models harnessing the huge amount of data stemming from various sources, minimizing computational time (instead of resource usage), and most importantly, approximate real-time solutions. The main purpose of this paper is to provide a review and classification of the most recent works regarding motion prediction, motion synthesis as well as musculoskeletal dynamics estimation problems using ML techniques, in order to offer sufficient insight into the state-of-the-art and draw new research directions. While the study of motion may appear distinct to musculoskeletal dynamics, these application domains provide jointly the link for more natural computer graphics character animation, since ML-based musculoskeletal dynamics estimation enables modeling of more long-term, temporally evolving, ergonomic effects, while offering automated and fast solutions. Overall, our review offers an in-depth presentation and classification of ML applications in human motion analysis, unlike previous survey articles focusing on specific aspects of motion prediction.

Prediction of medial knee contact force using multisource fusion recurrent neural network and transfer learning

Estimation of knee contact force (KCF) during gait provides essential information to evaluate knee joint function. Machine learning has been employed to estimate KCF because of the advantages of low computational cost and real-time. However, the existing machine learning models do not adequately consider gait-related data's temporal-dependent, multidimensional, and highly heterogeneous nature. This study is aimed at developing a multisource fusion recurrent neural network to predict the medial condyle KCF. First, a multisource fusion long short-term memory (MF-LSTM) model was established. Then, we developed a transfer learning strategy based on the MF-LSTM model for subject-specific medial KCF prediction. Four subjects with instrumented tibial prostheses were obtained from the literature. The results showed that the MF-LSTM model could predict medial KCF to a certain high level of accuracy (the mean of ρ = 0.970). The transfer learning model improved the prediction accuracy (the mean of ρ = 0.987). This study shows that the MF-LSTM model is a powerful and accurate computational tool for medial KCF prediction. Introducing transfer learning techniques could further improve the prediction performance for the target subject. This coupling strategy can help clinicians accurately estimate and track joint contact forces in real time.

Influence of posterior cruciate ligament tension on tibiofemoral and patellofemoral joint contact mechanics in cruciate-retaining total knee replacement: a combined musculoskeletal multibody and finite-element simulation

The influence of posterior cruciate ligament (PCL) tension on the clinical outcome of cruciate-retaining total knee replacement (CR-TKR) remains controversial. Various numerical approaches have been used to study this influence systematically, but the models used are limited by certain assumptions and simplifications. Therefore, the objective of this computational study was to develop a combined musculoskeletal multibody and finite-element simulation during a squat motion to 90° knee flexion with a CR-TKR design to overcome previous limitations regarding model inputs. In addition, different PCL tensions (tight, lax, resected) were modeled and the influence on tibiofemoral and resurfaced patellofemoral joint dynamics and contact stresses was evaluated. The effect of the PCL on knee joint dynamics and contact stresses was more pronounced at higher flexion angles. Tibiofemoral joint dynamics were influenced and a tight PCL induced increased posterior femoral translation during flexion. The maximum contact stress in the tibial insert increased from 20.6 MPa to 22.5 MPa for the resected and tightest PCL at 90° knee flexion. Patellofemoral joint dynamics were only slightly affected by PCL tension. However, the maximum contact stress in the patellar component decreased from 58.0 MPa to 53.7 MPa for the resected and tightest PCL at 90° knee flexion. The combination of musculoskeletal multibody and finite-element simulation is a sufficient method to comprehensively investigate knee joint dynamics and contact stresses in CR-TKR. The PCL tension after CR-TKR affects joint dynamics and contact stresses at the articulating implant surfaces.

Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage

Simulation studies, such as finite element (FE) modeling, provide insight into knee joint mechanics without patient involvement. Generic FE models mimic the biomechanical behavior of the tissue, but overlook variations in geometry, loading, and material properties of a population. Conversely, subject-specific models include these factors, resulting in enhanced predictive precision, but are laborious and time intensive. The present study aimed to enhance subject-specific knee joint FE modeling by incorporating a semi-automated segmentation algorithm using a 3D Swin UNETR for an initial segmentation of the femur and tibia, followed by a statistical shape model (SSM) adjustment to improve surface roughness and continuity. For comparison, a manual FE model was developed through manual segmentation (i.e., the de-facto standard approach). Both FE models were subjected to gait loading and the predicted mechanical response was compared. The semi-automated segmentation achieved a Dice similarity coefficient (DSC) of over 98% for both the femur and tibia. Hausdorff distance (mm) between the semi-automated and manual segmentation was 1.4 mm. The mechanical results (max principal stress and strain, fluid pressure, fibril strain, and contact area) showed no significant differences between the manual and semi-automated FE models, indicating the effectiveness of the proposed semi-automated segmentation in creating accurate knee joint FE models. We have made our semi-automated models publicly accessible to support and facilitate biomechanical modeling and medical image segmentation efforts ( https://data.mendeley.com/datasets/k5hdc9cz7w/1 ).

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.

Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb

Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.

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

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

Prediction on the medial knee contact force in patients with knee valgus using transfer learning approaches: Application to rehabilitation gaits

The Knee contact force (KCF) is a key factor in evaluating knee joint function of patients with knee osteoarthritis. In vivo measurement of KCF based on the instrumented implants is limited due to the ethical issues and technical complexities. Machine learning can be used to predict tibiofemoral compartment contact forces. However, anthropometric differences between individuals make the accurate predictions challenging. The purpose of this study was to develop transfer learning models to predict the medial KCF of patients with knee valgus in rehabilitation gaits. Four subjects with instrumented tibial prostheses were considered, including one with knee valgus and three with normal knee joint alignment. Two transfer learning models were proposed: a fine-tuning model and an adaptive model. In particular, a synchronization method for extracting experimental data in a complete gait cycle was developed, since different types of experimental data have different sampling frequencies. The transfer learning models were pre-trained by the experiment data of patients with normal knee joint alignment, and re-trained by the data of the patient with knee valgus. Predictions of the transfer learning models and traditional machine learning model were validated against the in vivo measurements. The proposed transfer learning models were tested within two levels: the single subject (Level 1) and multiple subjects (Level 2). The results show that the two transfer learning models could more accurately predict the medial KCF of patients with knee valgus than the traditional machine learning model. The performance of the fine-tuning model is better than that of the adaptive model. Compared with the traditional machine learning and inverse dynamics analysis, transfer learning represents a much easier and more accurate method. It can be introduced to help clinicians validate and adjust the rehabilitation gait for specific patients.

Importance of posterior tibial slope in joint kinematics with an anterior cruciate ligament-deficient knee

Aims

To fully quantify the effect of posterior tibial slope (PTS) angles on joint kinematics and contact mechanics of intact and anterior cruciate ligament-deficient (ACLD) knees during the gait cycle.

Methods

In this controlled laboratory study, we developed an original multiscale subject-specific finite element musculoskeletal framework model and integrated it with the tibiofemoral and patellofemoral joints with high-fidelity joint motion representations, to investigate the effects of 2.5° increases in PTS angles on joint dynamics and contact mechanics during the gait cycle.

Results

The ACL tensile force in the intact knee was significantly affected with increasing PTS angle. Considerable differences were observed in kinematics and initial posterior femoral translation between the intact and ACLD joints as the PTS angles increased by more than 2.5° (beyond 11.4°). Additionally, a higher contact stress was detected in the peripheral posterior horn areas of the menisci with increasing PTS angle during the gait cycle. The maximum tensile force on the horn of the medial meniscus increased from 73.9 N to 172.4 N in the ACLD joint with increasing PTS angles.

Conclusion

Knee joint instability and larger loading on the medial meniscus were found on the ACLD knee even at a 2.5° increase in PTS angle (larger than 11.4°). Our biomechanical findings support recent clinical evidence of a high risk of failure of ACL reconstruction with steeper PTS and the necessity of ACL reconstruction, which would prevent meniscus tear and thus the development or progression of osteoarthritis.

Cite this article: Bone Joint Res 2022;11(10):739–750.

Biomechanical effects of cross-pin's diameter in reconstruction of anterior cruciate ligament - A specific case study via finite element analysis

For anterior cruciate ligament reconstruction (ACL-R), one of the crucial aspects of treatment is the fixator selection that could provide initial graft fixation post-operatively. Literature on biomechanical stabilities of different sizes of fixators as femoral graft fixation is limited. Therefore, this study aims to analyse the influence of different diameters of cross-pins on the stability of graft fixations after ACL-R via finite element analysis (FEA). In the methodology, three-dimensional (3D) models of three different diameters of cross-pins were developed, of which anterior tibial loads (ATL) were applied onto the tibia. From the findings, the cross-pin with a smaller diameter (4 mm) provided optimum stability than larger diameter cross-pins, whereby it demonstrated acceptable stresses at the fixators (both cross-pin and interference screw) with a different percentage of 28%, while the stresses at the corresponding bones were favourable for osseointegration to occur. Besides, the strains of the knee joint with 4 mm diameter cross-pin were also superior in providing a good biomechanical environment for bone healing, while the recorded strain values at fixators were comparable with a larger diameter of cross-pins without being inferior in terms of deformation. To conclude, the cross-pin with 4 mm diameter depicted the best biomechanical aspects in graft fixation for ACL-R since it allows better assistance for the osseointegration process and can minimise the possibility of the breakage and migration of fixators. This study is not only useful for medical surgeons to justify their choices of pin diameter to treat patients, but also for researchers to conduct future studies.

Incremental Element Deletion-Based Finite Element Analysis of the Effects of Impact Speeds, Fall Postures, and Cortical Thicknesses on Femur Fracture

The proximal femur’s numerical simulation could give an effective method for predicting the risk of femoral fracture. However, the majority of existing numerical simulations is static, which does not correctly capture the dynamic properties of bone fractures. On the basis of femoral fracture analysis, a dynamic simulation using incremental element deletion (IED)-based finite element analysis (FEA) was developed and compared to XFEM in this study. Mechanical tests were also used to assess it. Different impact speeds, fall postures, and cortical thicknesses were also studied for their implications on fracture types and mechanical responses. The time it took for the crack to shatter was shorter when the speed was higher, and the crack line slid down significantly. The fracture load fell by 27.37% when the angle was altered from 15° to 135°, indicating that falling forward was less likely to cause proximal femoral fracture than falling backward. Furthermore, the model with scant cortical bone was susceptible to fracture. This study established a theoretical foundation and mechanism for forecasting the risk of proximal femoral fracture in the elderly.

[Enriching in vivo clinical trials with in silico models for orthopedic implants]

Clinical trials are used by the medical device industry to confirm products safety, performance, and clinical benefits. Traditional clinical studies typically follow a limited number of volunteers, which prevents capturing the full breath of patient demographics and implant use. New tools are required to overcome the limitations of traditional trials while fulfilling increasingly demanding regulatory requirements. Computer simulations have the potential to enrich traditional clinical trials with so called in silico clinical trials (ISCT) by providing data on a much broader spectrum of patients, clinical conditions and implant configurations. The historical use of simulation in the orthopedic device industry is described here to explain how it is now technically possible to model virtual populations. We also discuss the multiple benefits of such a translational research approach for the patients, healthcare systems, and manufacturers, but also the challenges to overcome. A more detailed version is available in English [1].

A Critical Review of the Design, Manufacture, and Evaluation of Bone Joint Replacements for Bone Repair

With the change of people’s living habits, bone trauma has become a common clinical disease. A large number of bone joint replacements is performed every year around the world. Bone joint replacement is a major approach for restoring the functionalities of human joints caused by bone traumas or some chronic bone diseases. However, the current bone joint replacement products still cannot meet the increasing demands and there is still room to increase the performance of the current products. The structural design of the implant is crucial because the performance of the implant relies heavily on its geometry and microarchitecture. Bionic design learning from the natural structure is widely used. With the progress of technology, machine learning can be used to optimize the structure of bone implants, which may become the focus of research in the future. In addition, the optimization of the microstructure of bone implants also has an important impact on its performance. The widely used design algorithm for the optimization of bone joint replacements is reviewed in the present study. Regarding the manufacturing of the implant, the emerging additive manufacturing technique provides more room for the design of complex microstructures. The additive manufacturing technique has enabled the production of bone joint replacements with more complex internal structures, which makes the design process more convenient. Numerical modeling plays an important role in the evaluation of the performance of an implant. For example, theoretical and numerical analysis can be carried out by establishing a musculoskeletal model to prepare for the practical use of bone implants. Besides, the in vitro and in vivo testing can provide mechanical properties of bone implants that are more in line with the implant recipient’s situation. In the present study, the progress of the design, manufacture, and evaluation of the orthopedic implant, especially the joint replacement, is critically reviewed.

A Computationally Efficient Lower Limb Finite Element Musculoskeletal Framework Directly Driven Solely by Inertial Measurement Unit Sensors

Finite element musculoskeletal (FEMS) approaches using concurrent musculoskeletal and finite element models driven by motion data such as marker-based motion trajectory can provide insight into the interactions between the knee joint secondary kinematics, contact mechanics, and muscle forces in subject-specific biomechanical investigations. However, these data-driven FEMS systems have two major disadvantages that make them challenging to apply in clinical environments: they are computationally expensive and they require expensive and inconvenient equipment for data acquisition. In this study, we developed an FEMS model of the lower limb driven solely by inertial measurement unit sensors that includes the tissue geometries of the entire knee joint and combines muscle modeling and elastic foundation theory-based contact analysis of knee into a single framework. The model requires only the angular velocities and accelerations measured by the sensors as input, and the target outputs (knee contact mechanics, secondary kinematics, and muscle forces) are predicted from the convergence results of iterative calculations of muscle force optimization and knee contact mechanics. To evaluate its accuracy, the model was compared with in vivo experimental data during gait. The maximum contact pressure (12.6 MPa) in the rigid body contact analysis occurred on the medial side of the cartilage at the maximum loading response. The proposed computationally efficient framework drastically reduced the computational time (97.5% reduction) in comparison with the conventional deformable finite element analysis. The developed framework combines measurement convenience and computational efficiency and shows promise for clinical applications.

Design of Porous Metal Block Augmentation to Treat Tibial Bone Defects in Total Knee Arthroplasty Based on Topology Optimization

Metal block augmentation, which is used for the treatment of tibial bone defects in total knee arthroplasty, with high stiffness will cause significant alteration in stress distribution, and its solid structure is not suitable for osseointegration. This study aimed to design a porous block to reduce weight, promote bone ingrowth, and improve its biomechanical performance. The metal block augmentation technique was applied to finite element models of tibial bone defects. Minimum compliance topology optimization subject to volume fraction combined with the porous architecture was adopted to redesign the block. Biomechanical changes compared with the original block were analyzed by finite element analysis. The stress distribution of the block and proximal tibia was recorded. The strain energy density of the proximal tibia was obtained. The newly designed block realized 40% weight reduction. The maximum stress in the optimized block decreased by 11.6% when compared with the solid one. The maximum stress of the proximal tibia in the optimized group increased by 18.6%. The stress of the anterior, medial, and posterior parts of the proximal medial tibia in the optimized group was significantly greater than that in the original group (all p < 0.05). The optimized block could effectively improve the biomechanical performance between the block and the bone. The presented method might provide a reference for the design of customized three-dimensional printed prostheses.

Multiscale finite element musculoskeletal model for intact knee dynamics

BACKGROUND AND OBJECTIVE

The dynamic characteristics of the intact knee joint are valuable for treating knee osteoarthritis and designing knee prostheses. However, it remains a challenge to elucidate the detailed dynamics of the knee due to its complexity of anatomical structure and complex interaction with body dynamics.

METHODS

In this study, a unique subject-specific musculoskeletal model with a concurrent high-accuracy intact finite element knee model was created and used to simultaneously evaluate the kinematics and mechanics of an intact knee joint during the gait cycle.

RESULTS

A medial pivot motion with external rotation, and a large parallel anterior translation were observed in the stance and swing phases, respectively, which is consistent with the in vivo fluoroscopy measurements. The maximum axial contact force on the knee joint, observed at 45% of the gait cycle, is approximately 2.89 times the body weight. The medial cartilage bears 65.7% of the total axial contact force. The results demonstrate that the cartilage-cartilage contact bears most of the joint load (62.5%) compared to the cartilage-meniscus-cartilage contact (37.5%). Regarding contact mechanics, the maximum contact pressure on both sides of the tibial cartilage (8.2 MPa) is almost similar to the first axial loading peak (14%) of the gait cycle. Additionally, the maximum contact pressure (6.01 MPa) was observed during the stance phase of the gait cycle on the patellofemoral joint.

CONCLUSIONS

The predicted results on the tibiofemoral and patellofemoral joints provide a theoretical basis for the treatment of knee joint diseases and knee prosthesis design. Moreover, this approach presents a comprehensive tool to evaluate the mechanics at both the body and tissue levels. Therefore, it has a high potential for application in human biomechanics.

Hamstrings Contraction Regulates the Magnitude and Timing of the Peak ACL Loading During the Drop Vertical Jump in Female Athletes

Background

Anterior cruciate ligament (ACL) injury reduction training has focused on lower body strengthening and landing stabilization. In vitro studies have shown that quadriceps forces increase ACL strain, and hamstring forces decrease ACL strain. However, the magnitude of the effect of the quadriceps and hamstrings forces on ACL loading and its timing during in vivo landings remains unclear.

Purpose

To investigate the effect and timing of knee muscle forces on ACL loading during landing.

Study Design

Descriptive laboratory study.

Methods

A total of 13 young female athletes performed drop vertical jump trials, and their movements were recorded with 3-dimensional motion capture. Lower limb joint motion and muscle forces were estimated with OpenSim and applied to a musculoskeletal finite element (FE) model to estimate ACL loading during landings. The FE simulations were performed with 5 different conditions that included/excluded kinematics, ground-reaction force (GRF), and muscle forces.

Results

Simulation of landing kinematics without GRF or muscle forces yielded an estimated median ACL strain and force of 5.1% and 282.6 N. Addition of GRF to kinematic simulations increased ACL strain and force to 6.8% and 418.4 N (P < .05). Addition of quadriceps force to kinematics + GRF simulations nonsignificantly increased ACL strain and force to 7.2% and 478.5 N. Addition of hamstrings force to kinematics + GRF simulations decreased ACL strain and force to 2.6% and 171.4 N (P < .001). Addition of all muscles to kinematics + GRF simulations decreased ACL strain and force to 3.3% and 195.1 N (P < .001). With hamstrings force, ACL loading decreased from initial contact (time of peak: 1-18 milliseconds) while ACL loading without hamstrings force peaked at 47 to 98 milliseconds after initial contact (P = .024-.001). The knee flexion angle increased from 20.9° to 73.1° within 100 milliseconds after initial contact.

Conclusion

Hamstrings activation had greater effect relative to GRF and quadriceps activation on ACL loading, which significantly decreased and regulated the magnitude and timing of ACL loading during in vivo landings.

Clinical Relevance

Clinical training should focus on strategies that influence increased hamstrings activation during landing to reduce ACL loads.

Biomechanical analysis of three different types of fixators for anterior cruciate ligament reconstruction via finite element method: a patient-specific study

Complication rates of anterior cruciate ligament reconstruction (ACL-R) were reported to be around 15% although it is a common arthroscopic procedure with good outcomes. Breakage and migration of fixators are still possible even months after surgery. A fixator with optimum stability can minimise those two complications. Factors that affect the stability of a fixator are its configuration, material, and design. Thus, this paper aims to analyse the biomechanical effects of different types of fixators (cross-pin, interference screw, and cortical button) towards the stability of the knee joint after ACL-R. In this study, finite element modelling and analyses of a knee joint attached with double semitendinosus graft and fixators were carried out. Mimics and 3-Matic softwares were used in the development of the knee joint models. Meanwhile, the graft and fixators were designed by using SolidWorks software. Once the meshes of all models were finished in 3-Matic, simulation of the configurations was done using MSC Marc Mentat software. A 100-N anterior tibial load was applied onto the tibia to simulate the anterior drawer test. Based on the findings, cross-pin was found to have optimum stability in terms of stress and strain at the femoral fixation site for better treatment of ACL-R.

Comparison of Kinematics and Contact Mechanics in Normal Knee and Total Knee Replacements: A Computational Investigation

An objective of total knee replacement (TKR) is to restore the mechanical function of a normal knee. Joint kinematics and contact mechanics performance are two of the primary indices that indicate the success of TKR devices. The aim of this study was to compare the kinematics and contact mechanics of TKR and normal knee joints. An experimentally evaluated finite-element (FE) knee model was developed and used to investigate the performance of four TKR designs (fixed cruciate-retaining (CR), mobile CR, posterior-stabilized (PS), medial pivot design (MP)) and the normal knee joint during a gait cycle. The predicted kinematic results showed that the MP design presented similar kinematics to those of the normal knee joint and did not demonstrate paradoxical motion of the femur. A considerably larger contact area and lower contact pressure were found on the normal knee joint (1315 mm², and 14.8 MPa, respectively) than on the TKRs, which was consistent with the previous in-vivo fluoroscopic investigation. The mobile CR and PS designs exhibited the smallest and greatest contact pressures of the four TKR designs, respectively. The results of the present study help to understand the kinematics and contact mechanics in the TKR during the gait cycle, and provide comprehensive information about the performance of the normal knee joint.

Development and evaluation of a new methodology for Soft Tissue Artifact compensation in the lower limb

Skin Marker (SM) based motion capture is the most widespread technique used for motion analysis. Yet, the accuracy is often hindered by Soft Tissue Artifact (STA). This is a major issue in clinical gait analysis where kinematic results are used for decision-making. It also has a considerable influence on the results of rigid body and Finite Element (FE) musculoskeletal models that rely on SM-based kinematics to estimate muscle, contact and ligament forces. Current techniques devised to compensate for STA, in particular multi-body optimization methods, often consider simplified joint models. Although joint personalization with anatomical constraints has improved kinematic estimation, these models yet don't represent a fully reliable solution to the STA problem, thus allowing us to envisage an alternative approach. In this perspective, we propose to develop a conceptual FE-based model of the lower limb for STA compensation and evaluate it for 66 healthy subjects under level walking motor task. Both hip and knee joint kinematics were analyzed, considering both rotational and translational joint motion. Results showed that STA caused underestimation of the hip joint kinematics (up to 2.2°) for all rotational DoF, and overestimation of knee joint kinematics (up to 12°) except in flexion/extension. Joint kinematics, in particular the knee joint, appeared to be sensitive to soft tissue stiffness parameters (rotational and translational mean difference up to 1.5° and 3.4 mm). Analysis of the results using alternative joint representations highlighted the versatility of the proposed modeling approach. This work paves the way for using personalized models to compensate for STA in healthy subjects and different activities.

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.

In vivo kinematical validated knee model for preclinical testing of total knee replacement

BACKGROUND AND OBJECTIVE

A computational knee model facilitates efficient component design evaluations and preclinical testing under various dynamic loadings. However, the development of a highly mimicked dynamic whole knee model with specified ligament constraints that provides high predictive accuracy with in-vivo experiments remains a challenge.

METHODS

In the present study, a musculoskeletal integrated force-driven explicit finite-element knee model with tibiofemoral and patellofemoral joints constrained with detailed soft tissue was developed. A proportional-integral-derivative controller was concurrently added to the knee model to track the boundary conditions. The actuations of the quadriceps and hamstrings were predicted via a subject-specific musculoskeletal model and matched with electromyography results.

RESULTS

Compared to in-vivo fluoroscopic results in a gait cycle, the predicted results of the kinematics of the tibiofemoral joint exhibited an agreement in terms of tendency and magnitude (anterior-posterior translation: RMSE = 1.1 mm, r² = 0.87; inferior-superior translation: RMSE = 0.83 mm, r² = 0.84; medial-lateral translation: RMSE = 0.82 mm, r² = 0.05; flexion-extension rotation: RMSE = 0.23°, r² = 1; internal-external rotation: RMSE = 1.85°, r² = 0.65; varus-valgus rotation: RMSE = 1.39°, r² = 0.08). Contact mechanics, including the contact area, pressure, and stress, were synchronously simulated on the tibiofemoral and patellofemoral joints.

CONCLUSIONS

The study provides a calibrated knee model and a kinematical validation approach that can be widely used in preclinical testing and knee prosthesis design.

Spherical center axial hinge knee prosthesis causes lower contact stress on tibial insert and bushing compared with biaxial hinge knee prosthesis

BACKGROUND

Motion axial system may affect contact stress of hinge knee prosthesis. However, it is unclear which axial system provides the better biomechanical effect. Therefore, the aim of this study was to compare the contact stress and stress distribution on the tibial insert and the bushing of hinge knee prostheses with a biaxial (BA) system and a spherical center axial (SA) system during a gait cycle.

METHODS

Three-dimensional finite-element (FE) models of the prostheses with different motion systems were included. The comparisons between experimental tests and FE analyses were performed to verify the models. Dynamic implicit FE analyses were performed to investigate the peak contact stresses and stress distributions on the tibial insert and the bushing.

RESULTS

The peak contact stresses on the tibial insert and the bushing of the BA prosthesis were higher than those of the SA prosthesis during most gait cycles. The contact time on the bushing is short in the SA prosthesis. The stress distributions on the superior surface of the tibial insert in the BA prosthesis were at the posterior side, but of the SA prosthesis were not fixed.

CONCLUSION

The SA prosthesis has a lower peak contact stress on tibial insert and bushing than the BA prosthesis; in addition, the SA prosthesis has a 'self-adjustment' mechanism which could disperse high stress on the tibial insert to decrease the risk of wear and damage. The comparison could help designers and surgeons to better understand the future design of rotating hinge knee prostheses which should be able to achieve multiaxial motion and complete weight bearing by the tibial condylar to transmit the axial force better.

Development and validation of a finite-element musculoskeletal model incorporating a deformable contact model of the hip joint during gait

Musculoskeletal models provide non-invasive and subject-specific biomechanical investigations of the musculoskeletal system. In a musculoskeletal model, muscle forces contribute to the deformation and kinematics of the joint which in turn would alter moment arms of muscles and ground reaction forces and thus affect the prediction of muscle forces and contact forces and contact mechanics of the joint. By far, deformable contact models of the hip have not been considered in musculoskeletal models, and the role of kinematics and deformation within the hip in muscle forces and hip contact mechanics is unknown. In this study, an FE musculoskeletal model including bones, joints and muscles of the lower extremity was developed. A deformable contact model of the hip joint was incorporated and coupled into the musculoskeletal model. Joint angles and ground reaction forces during gait were used as inputs. Optimization minimizing the sum of muscle stresses squared was performed directly to the FE musculoskeletal model in order to simultaneously solve muscle forces and contact forces and contact stresses of the hip joint within a single framework. The calculated hip contact forces corresponded well to the in vivo measurement data. The maximum hip contact stress was 6.5 MPa and occurred at weight-acceptance. The influence of kinematics and deformation in the hip on muscles forces and hip contact forces was minimal and not sensitive to variations in the thickness and properties of the joint cartilage during gait. This suggests that the uncoupled approach in which the hip contact forces and contact mechanics are simulated in separate frameworks would serve as an effective and efficient alternative for subject-specific modelling of the hip. This study provides guidance for the level of complexity needed for future hip models and can be used to evaluate biomechanical changes of the musculoskeletal system following interventions.

BIOMECHANICAL EFFECTS OF DIFFERENT LENGTHS OF CROSS-PINS IN ANTERIOR CRUCIATE LIGAMENT RECONSTRUCTION: A FINITE ELEMENT ANALYSIS

Complication rates of anterior cruciate ligament reconstruction (ACL-R) were reported to be around 15%. Although it is a very common arthroscopic surgery with good outcomes, breakage and migration of fixators are still possible to occur due to stability issue. One of the factors that affects the mechanical stability of fixators is its length. Therefore, the aim of this paper is to analyze the biomechanical effects of different lengths of fixators (cross-pin technique) towards the stabilities of the knee joint after ACL-R. Finite element analyses of knee joint with DST grafts and fixators were carried out. Mimics and 3-Matic were used in the development of knee joint models, while the grafts and fixators were designed by using SolidWorks software. All models were remeshed in the 3-Matic and numerical analysis was performed via MSC.Marc Mentat software. A 100 N anterior tibial load was applied onto the tibia to simulate the anterior drawer test after the surgery and proximal femur was fixed at all degrees of freedom. Based on the findings, cross-pin with 40[Formula: see text]mm in length provided the most favorable option for better treatment of ACL-R, where it could promote osseointegration and preventing fracture.

Enhanced In-Silico Polyethylene Wear Simulation of Total Knee Replacements During Daily Activities

A computational wear simulator is an efficient tool for evaluating the wear of artificial knee joints. The classical Archard's wear law-based simulator has questionable accuracy and is focused on walking. In this study, an in silico polyethylene wear simulation of total knee replacements was developed considering the various highly demanding daily activities. A good predicted accuracy (error = 8.1%) was found through comparison of the experimental results. A relatively larger averaged wear loss was found under the loading condition (1.53 mg/mc) of daily activities compared with the walking condition (1.32 mg/mc). The squatting movement (2.57 mg/mc) produces the highest overall wear rate. In addition, a relatively larger amount of wear was found on the medial side knee prosthesis than that on the lateral side. The enhanced in silico polyethylene wear simulator provides an accurate and comprehensive tool for wear prediction in preclinical wear testing.

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.

Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge

Purpose

Modern statistics and higher computational power have opened novel possibilities to complex data analysis. While gait has been the utmost described motion in quantitative human motion analysis, descriptions of more challenging movements like the squat or lunge are currently lacking in the literature. The hip and knee joints are exposed to high forces and cause high morbidity and costs. Pre-surgical kinetic data acquisition on a patient-specific anatomy is also scarce in the literature. Studying the normal inter-patient kinetic variability may lead to other comparable studies to initiate more personalized therapies within the orthopedics.

Methods

Trials are performed by 50 healthy young males who were not overweight and approximately of the same age and activity level. Spatial marker trajectories and ground reaction force registrations are imported into the Anybody Modeling System based on subject-specific geometry and the state-of-the-art TLEM 2.0 dataset. Hip and knee joint reaction forces were obtained by a simulation with an inverse dynamics approach. With these forces, a statistical model that accounts for inter-subject variability was created. For this, we applied a principal component analysis in order to enable variance decomposition. This way, noise can be rejected and we still contemplate all waveform data, instead of using deduced spatiotemporal parameters like peak flexion or stride length as done in many gait analyses. In addition, this current paper is, to the authors’ knowledge, the first to investigate the generalization of a kinetic model data toward the population.

Results

Average knee reaction forces range up to 7.16 times body weight for the forwarded leg during lunge. Conversely, during squat, the load is evenly distributed. For both motions, a reliable and compact statistical model was created. In the lunge model, the first 12 modes accounts for 95.26% of inter-individual population variance. For the maximal-depth squat, this was 95.69% for the first 14 modes. Model accuracies will increase when including more principal components.

Conclusion

Our model design was proved to be compact, accurate, and reliable. For models aimed at populations covering descriptive studies, the sample size must be at least 50.

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

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

A critical review on the three-dimensional finite element modelling of the compression therapy for chronic venous insufficiency

Compression therapy is an adjuvant physical intervention providing the benefits of calibrated compression and controlled stretch and consequently is increasingly applied for the treatment of chronic venous insufficiency. However, the mechanism of the compression therapy for chronic venous insufficiency is still unclear. To elaborate the mechanism of compression therapy, in recent years, the computational modelling technique, especially the finite element modelling method, has been widely used. However, there are still many unclear issues regarding the finite element modelling of compression therapy, for example, the selection of appropriate material models, the validation of the finite element predictions, the post-processing of the results. To shed light on these unclear issues, this study provides a state-of-the-art review on the application of finite element modelling technique in the compression therapy for chronic venous insufficiency. The aims of the present study are as follows: (1) to provide guidance on the application of the finite element technique in healthcare and relevant fields, (2) to enhance the understanding of the mechanism of compression therapy and (3) to foster the collaborations among different disciplines. To achieve these aims, the following parts are reviewed: (1) the background on chronic venous insufficiency and the computational modelling approach, (2) the acquisition of medical images and the procedure for generating the finite element model, (3) the definition of material models in the finite element model, (4) the methods for validating the finite element predictions, (5) the post-processing of the finite element results and (6) future challenges in the finite element modelling of compression therapy.