Automated personalization of biomechanical knee model

PURPOSE

Patient-specific biomechanical models of the knee joint can effectively aid in understanding the reasons for pathologies and improve diagnostic methods and treatment procedures. For deeper research of knee diseases, the development of biomechanical models with appropriate configurations is essential. In this study, we mainly focus on the development of a personalized biomechanical model for the investigation of knee joint pathologies related to patellar motion using automated methods.

METHODS

This study presents a biomechanical model created for patellar motion pathologies research and some techniques for automating the generation of the biomechanical model. To generate geometric models of bones, the U-Net neural network was adapted for 3D input datasets. The method uses the same neural network for segmentation of femur, tibia, patella and fibula. The total size of the train/validation (75/25%) dataset is 18,183 3D volumes of size [Formula: see text] voxels. The configuration of the biomechanical knee model proposed in the paper includes six degrees of freedom for the tibiofemoral and patellofemoral joints, lateral and medial contact surfaces for femur and tibia, and ligaments, representing, among other things, the medial and lateral stabilizers of the knee cap. The development of the personalized biomechanical model was carried out using the OpenSim software system. The automated model generation was implemented using OpenSim Python scripting commands.

RESULTS

The neural network for bones segmentation achieves mean DICE 0.9838. A biomechanical model for realistic simulation of patellar movement within the trochlear groove was proposed. Generation of personalized biomechanical models was automated.

CONCLUSIONS

In this paper, we have implemented a neural network for the segmentation of 3D CT scans of the knee joint to produce a biomechanical model for the study of knee cap motion pathologies. Most stages of the generation process have been automated and can be used to generate patient-specific models.

Validation of a Robotic Testbench for Evaluating Biomechanical Effects of Implant Rotation in Total Knee Arthroplasty on a Cadaveric Specimen

In this study, we developed and validated a robotic testbench to investigate the biomechanical compatibility of three total knee arthroplasty (TKA) configurations under different loading conditions, including varus-valgus and internal-external loading across defined flexion angles. The testbench captured force-torque data, position, and quaternion information of the knee joint. A cadaver study was conducted, encompassing a native knee joint assessment and successive TKA testing, featuring femoral component rotations at -5°, 0°, and +5° relative to the transepicondylar axis of the femur. The native knee showed enhanced stability in varus-valgus loading, with the +5° external rotation TKA displaying the smallest deviation, indicating biomechanical compatibility. The robotic testbench consistently demonstrated high precision across all loading conditions. The findings demonstrated that the TKA configuration with a +5° external rotation displayed the minimal mean deviation under internal-external loading, indicating superior joint stability. These results contribute meaningful understanding regarding the influence of different TKA configurations on knee joint biomechanics, potentially influencing surgical planning and implant positioning. We are making the collected dataset available for further biomechanical model development and plan to explore the 6 Degrees of Freedom (DOF) robotic platform for additional biomechanical analysis. This study highlights the versatility and usefulness of the robotic testbench as an instrumental tool for expanding our understanding of knee joint biomechanics.

Cosimulation of the index finger extensor apparatus with finite element and musculoskeletal models

Musculoskeletal modeling has been effective for simulating dexterity and exploring the consequences of disability. While previous approaches have examined motor function using multibody dynamics, existing musculoskeletal models of the hand and fingers have difficulty simulating soft tissue such as the extensor mechanism of the fingers, which remains underexplored. To investigate the extensor mechanism and its impact on finger motor function, we developed a finite element model of the index finger extensor mechanism and a cosimulation method that combines the finite element model with a multibody dynamic model. The finite element model and cosimulation were validated through comparison with experimentally derived tissue strains and fingertip endpoint forces respectively. Tissue strains predicted by the finite element model were consistent with the experimentally observed strains of the 9 postures tested in cadaver specimens. Fingertip endpoint forces predicted using the cosimulation were well aligned in both force (difference within 0.60 N) and direction (difference within 30°with experimental results. Sensitivity of the extensor mechanism to changes in modulus and adhesion configuration were evaluated for ± 50% of experimental moduli, presence of the radial and ulnar adhesions, and joint capsule. Simulated strains and endpoint forces were found to be minimally sensitive to alterations in moduli and adhesions. These results are promising and demonstrate the ability of the cosimulation to predict global behavior of the extensor mechanism, while enabling measurement of stresses and strains within the structure itself. This model could be used in the future to predict the outcomes for different surgical repairs of the extensor mechanism.

Effect of Tibial Component Misalignment on the Lower Limb Joint Kinematics During Squat

The component orientation of the total knee replacement is critical to surgical outcomes. There have been many studies focused on knee movement for different component rotations. However, the effect of component misalignment on a dynamic movement, especially which requires high knee flexion, is not widely studied. The aim of this study is to investigate the effect of tibial component misalignment on a squat motion by predictive simulation. Squat motions with different replacement component alignments were predicted by formulating an optimal control problem. The result indicates that component misalignment on coronal and horizontal planes reduces peak joint flexion angles and the external rotation on the horizontal plane has the most negative impact. Misalignment in external rotation resulted in the greatest reduction of peak joint flexion angles. The simulation was validated by comparison with experimental data, which showed a high level of correlation with the predicted motion.Clinical relevance- The predictive simulation presented in this study can predict the dynamic post-surgery movement of TKR. It has the potential to help surgeons and clinicians at the preoperative planning stage.

Towards a validated musculoskeletal knee model to estimate tibiofemoral kinematics and ligament strains: comparison of different anterolateral augmentation procedures combined with isolated ACL reconstructions

BACKGROUND

Isolated ACL reconstructions (ACLR) demonstrate limitations in restoring native knee kinematics. This study investigates the knee mechanics of ACLR plus various anterolateral augmentations using a patient-specific musculoskeletal knee model.

MATERIALS AND METHODS

A patient-specific knee model was developed in OpenSim using contact surfaces and ligament details derived from MRI and CT data. The contact geometry and ligament parameters were varied until the predicted knee angles for intact and ACL-sectioned models were validated against cadaveric test data for that same specimen. Musculoskeletal models of the ACLR combined with various anterolateral augmentations were then simulated. Knee angles were compared between these reconstruction models to determine which technique best matched the intact kinematics. Also, ligament strains calculated by the validated knee model were compared to those of the OpenSim model driven by experimental data. The accuracy of the results was assessed by calculating the normalised RMS error (NRMSE); an NRMSE < 30% was considered acceptable.

RESULTS

All rotations and translations predicted by the knee model were acceptable when compared to the cadaveric data (NRMSE < 30%), except for the anterior/posterior translation (NRMSE > 60%). Similar errors were observed between ACL strain results (NRMSE > 60%). Other ligament comparisons were acceptable. All ACLR plus anterolateral augmentation models restored kinematics toward the intact state, with ACLR plus anterolateral ligament reconstruction (ACLR + ALLR) achieving the best match and the greatest strain reduction in ACL, PCL, MCL, and DMCL.

CONCLUSION

The intact and ACL-sectioned models were validated against cadaveric experimental results for all rotations. It is acknowledged that the validation criteria are very lenient; further refinement is required for improved validation. The results indicate that anterolateral augmentation moves the kinematics closer to the intact knee state; combined ACLR and ALLR provide the best outcome for this specimen.

A digital twin framework for robust control of robotic-biological systems

Medical device regulatory standards are increasingly incorporating computational modelling and simulation to accommodate advanced manufacturing and device personalization. We present a method for robust testing of engineered soft tissue products involving a digital twin paradigm in combination with robotic systems. We developed and validated a digital twin framework for calibrating and controlling robotic-biological systems. A forward dynamics model of the robotic manipulator was developed, calibrated, and validated. After calibration, the accuracy of the digital twin in reproducing the experimental data improved in the time domain for all fourteen tested configurations and improved in frequency domain for nine configurations. We then demonstrated displacement control of a spring in lieu of a soft tissue element in a biological specimen. The simulated experiment matched the physical experiment with 0.09 mm (0.001%) root-mean-square error for a 2.9 mm (5.1%) length change. Finally, we demonstrated kinematic control of a digital twin of the knee through 70-degree passive flexion kinematics. The root-mean-square error was 2.00°, 0.57°, and 1.75° degrees for flexion, adduction, and internal rotations, respectively. The system well controlled novel mechanical elements and generated accurate kinematics in silico for a complex knee model. This calibration method could be applied to other situations where the specimen is poorly represented in the model environment (e.g., human or animal tissues), and the control system could be extended to track internal parameters such as tissue strain (e.g., control knee ligament strain). Further development of this framework can facilitate medical device testing and innovative biomechanics research.

The risk of tibial eminence avulsion fracture with bi-unicondylar knee arthroplasty : a finite element analysis

AIMS

The aim of this study was to determine the risk of tibial eminence avulsion intraoperatively for bi-unicondylar knee arthroplasty (Bi-UKA), with consideration of the effect of implant positioning, overstuffing, and sex, compared to the risk for isolated medial unicondylar knee arthroplasty (UKA-M) and bicruciate-retaining total knee arthroplasty (BCR-TKA).

METHODS

Two experimentally validated finite element models of tibia were implanted with UKA-M, Bi-UKA, and BCR-TKA. Intraoperative loads were applied through the condyles, anterior cruciate ligament (ACL), medial collateral ligament (MCL), and lateral collateral ligament (LCL), and the risk of fracture (ROF) was evaluated in the spine as the ratio of the 95^th percentile maximum principal elastic strains over the tensile yield strain of proximal tibial bone.

RESULTS

Peak tensile strains occurred on the anterior portion of the medial sagittal cut in all simulations. Lateral translation of the medial implant in Bi-UKA had the largest increase in ROF of any of the implant positions (43%). Overstuffing the joint by 2 mm had a much larger effect, resulting in a six-fold increase in ROF. Bi-UKA had ~10% increased ROF compared to UKA-M for both the male and female models, although the smaller, less dense female model had a 1.4 times greater ROF compared to the male model. Removal of anterior bone akin to BCR-TKA doubled ROF compared to Bi-UKA.

CONCLUSION

Tibial eminence avulsion fracture has a similar risk associated with Bi-UKA to UKA-M. The risk is higher for smaller and less dense tibiae. To minimize risk, it is most important to avoid overstuffing the joint, followed by correctly positioning the medial implant, taking care not to narrow the bone island anteriorly.Cite this article: Bone Joint Res 2022;11(8):575-584.

The effect of modelling parameters in the development and validation of knee joint models on ligament mechanics: A systematic review

BACKGROUND

The ligaments in the knee are prone to injury especially during dynamic activities. The resulting instability can have a profound impact on a patient's daily activities and functional capacity. Musculoskeletal knee modelling provides a non-invasive tool for investigating ligament force-strain behaviour in various dynamic scenarios, as well as potentially complementing existing pre-planning tools to optimise surgical reconstructions. However, despite the development and validation of many musculoskeletal knee models, the effect of modelling parameters on ligament mechanics has not yet been systematically reviewed.

OBJECTIVES

This systematic review aimed to investigate the results of the most recent studies using musculoskeletal modelling techniques to create models of the native knee joint, focusing on ligament mechanics and modelling parameters in various simulated movements.

DATA SOURCES

PubMed, ScienceDirect, Google Scholar, and IEEE Xplore.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Databases were searched for articles containing any numerical ligament strain or force data on the intact, ACL-deficient, PCL-deficient, or lateral extra-articular reconstructed (LER) knee joints. The studies had to derive these results from musculoskeletal modelling methods. The dates of the publications were between 1 January 1995 and 30 November 2021.

METHOD

A customised data extraction form was created to extract each selected study's critical musculoskeletal model development parameters. Specific parameters of the musculoskeletal knee model development used in each eligible study were independently extracted, including the (1) musculoskeletal model definition (i.e., software used for modelling, knee type, source of geometry, the inclusion of cartilage and menisci, and articulating joints and joint boundary conditions (i.e., number of degrees of freedom (DoF), subjects, type of activity, collected data and type of simulation)), (2) specifically ligaments modelling techniques (i.e., ligament bundles, attachment points, pathway, wrapping surfaces and ligament material properties such as stiffness and reference length), (3) sensitivity analysis, (4) validation approaches, (5) predicted ligament mechanics (i.e., force, length or strain) and (6) clinical applications if available. The eligible papers were then discussed quantitatively and qualitatively with respect to the above parameters.

RESULTS AND DISCUSSION

From the 1004 articles retrieved by the initial electronic search, only 25 met all inclusion criteria. The results obtained by aggregating data reported in the eligible studies indicate that considerable variability in the predicted ligament mechanics is caused by differences in geometry, boundary conditions and ligament modelling parameters.

CONCLUSION

This systematic review revealed that there is currently a lack of consensus on knee ligament mechanics. Despite this lack of consensus, some papers highlight the potential of developing translational tools using musculoskeletal modelling. Greater consistency in model design, incorporation of sensitivity assessment of the model outcomes and more rigorous validation methods should lead to better agreement in predictions for ligament mechanics between studies. The resulting confidence in the musculoskeletal model outputs may lead to the development of clinical tools that could be used for patient-specific treatments.

Estimation of forces on anterior cruciate ligament in dynamic activities

In this work, a nonlinear strain rate dependent plugin developed for the OpenSim® platform was used to estimate the instantaneous strain rate (ISR) and the forces on the ACL's anteromedial (aACL) and posterolateral (pACL) bundles during walking and sudden change of direction of running termed as 'plant-and-cut' (PC). The authors obtained the kinematics data for walking via optical motion capture. PC movements, along with running kinematics, were obtained from the literature. A nonlinear plugin developed for ligaments was interfaced with OpenSim® platform to simulate walking and PC motions with a flexed knee and an extended knee. PC phase is sandwiched between an approach phase and take-off phase and was studied at various event velocities (1.8, 3, and 4.2 m s^-1), and angles of PC (23°, 34°, and 45°) as encountered in adult ball games. In both cases of PC-with-extended knee and PC-with-flexed-knee, the maximum forces on both the ACL bundles were observed after the take-off phase. A maximum force of ~ 35 N kg^-1 of body weight (BW) was observed on aACL after the take-off phase for an event velocity of 4.2 m s^-1. In the posterolateral bundle (pACL), the maximum forces (~ 40 N kg^-1 of BW) were observed towards the end of the mid-swing phase (after the take-off phase) for the various combinations of the parameters studied. The forces observed in the simulation of PC-with-flexed-knee and PC-with-extended-knee has resulted in magnitude higher than sustainable by the adults. This study is novel in attempting to incorporate differing rates-of-strain that have been shown to alter soft tissue properties into the OpenSim® musculoskeletal model. The proposed model can be used by researchers to predict the forces during various kinematic activities for other soft tissues.

Influence of passive elements on prediction of intradiscal pressure and muscle activation in lumbar musculoskeletal models

BACKGROUND AND OBJECTIVE

The objective of this study was to investigate the effect of incorporating various passive elements, which could represent combined or individual effects of intervertebral disc, facet articulation and ligaments, on the prediction of lumbar muscle activation and L4-L5 intradiscal pressure.

METHODS

The passive elements representing the intervertebral disc, facet articulations, and ligaments were added to the existed lumbar musculoskeletal model with nonlinear rotational stiffness or force-strain relationships. The model was fed with kinematics of trunk flexion, extension, axial rotation and lateral bending to calculate muscle activation and L4-L5 intradiscal pressure.

RESULTS

In the trunk axial rotation, the intradiscal pressure values predicted by the models with elements representing facet articulation were much higher than that predicated by models removing these elements. In the trunk flexion, the models with passive elements showed lower muscle activation of extensors than model with no passive elements. At the end of trunk flexion, extension, axial rotation and lateral bending, the intradiscal pressure values predicted by model with intact passive elements were 120.6%, 92.5%, 334.8% and 74.9% of the values predicted by model with no passive elements, respectively.

CONCLUSIONS

Caution must be taken while modeling facet articulation as elements with rotational stiffness, as they may lead to overestimation of intradiscal pressure in trunk axial rotation. The inclusion of ligaments as spring-like elements may improve the simulation of flexion-relaxation phenomenon in trunk flexion. Future models considering detailed properties of passive elements are needed to allow more access to understanding the mechanics of the lumbar spine.

Development and validation of a kinematically-driven discrete element model of the patellofemoral joint

Quantifying the complex loads at the patellofemoral joint (PFJ) is vital to understanding the development of PFJ pain and osteoarthritis. Discrete element analysis (DEA) is a computationally efficient method to estimate cartilage contact stresses with potential application at the PFJ to better understand PFJ mechanics. The current study validated a DEA modeling framework driven by PFJ kinematics to predict experimentally-measured PFJ contact stress distributions. Two cadaveric knee specimens underwent quadriceps muscle [215 N] and joint compression [350 N] forces at ten discrete knee positions representing PFJ positions during early gait while measured PFJ kinematics were used to drive specimen-specific DEA models. DEA-computed contact stress and area were compared to experimentally-measured data. There was good agreement between computed and measured mean and peak stress across the specimens and positions (r = 0.63-0.85). DEA-computed mean stress was within an average of 12% (range: 1-47%) of the experimentally-measured mean stress while DEA-computed peak stress was within an average of 22% (range: 1-40%). Stress magnitudes were within the ranges measured (0.17-1.26 MPa computationally vs 0.12-1.13 MPa experimentally). DEA-computed areas overestimated measured areas (average error = 60%; range: 4-117%) with magnitudes ranging from 139 to 307 mm² computationally vs 74-194 mm² experimentally. DEA estimates of the ratio of lateral to medial patellofemoral stress distribution predicted the experimental data well (mean error = 15%) with minimal measurement bias. These results indicate that kinematically-driven DEA models can provide good estimates of relative changes in PFJ contact stress.

Simulating contact using the elastic foundation algorithm in OpenSim

Modeling joint contact in OpenSim is not well understood. This study systematically investigated the variables associated with the elastic foundation contact model within OpenSim by performing a series of controlled benchtop experiment and concomitant simulations. Four metal-on-plastic interactions were modeled, including a model of a total knee replacement (TKR). Load-displacement curves were recorded during cyclic loading between 100 and 750 N. Geometries were imported and into OpenSim and contact mechanics were modeled with the on-board elastic foundation algorithm. A hybrid optimization algorithm determined that stiffness and dissipation coefficients for TKR implants were 1.52 × 10¹⁰ N/m and 57.7 Ns/m, respectively. Estimations of contact forces were 10.2% of blinded experimental data (average root mean square error: 76.82 ± 11.47 N). In the second portion of this study, freely available eTibia TKR renderings were used to test the ubiquity of the tuning parameters. They were also used to perform a sensitivity analysis of material stiffness and mesh density with regard to penetration depth and computational time. When a stiffness of 1 × 10¹⁰ was applied to an eTibia model with 5000 faces, a 100 kg load caused 0.259 mm of penetration. Under the same conditions, the tuned model experienced 0.300 mm of penetration. Material stiffnesses between 1 × 10¹³ and 1 × 10¹⁵ N/m increased computation time by factors of 12-23. This study provides much needed clarity regarding the use of the OpenSim EF algorithm. It also demonstrates the utility of OpenSim to model deformable materials and complex geometries, and this approach can be adapted to make reasonable estimations for both natural and surgically modified joints.

The impact of thigh and shank marker quantity on lower extremity kinematics using a constrained model

Background

Musculoskeletal models are commonly used to quantify joint motions and loads during human motion. Constraining joint kinematics simplifies these models but the implications of the placement and quantity of markers used during data acquisition remains unclear. The purpose of this study was to establish the effects of marker placement and quantity on lower extremity kinematics calculated using a constrained-kinematic model. We hypothesized that a constrained-kinematic model would produce lower-extremity kinematics errors that correlated with the number of tracking markers removed from the thigh and shank.

Methods

Healthy-young adults (N = 10) walked on a treadmill at slow, moderate, and fast speeds while skin-mounted markers were tracked using motion capture. Lower extremity kinematics were calculated for 256 combinations of leg and shank markers to establish the implications of marker placement and quantity on joint kinematics. Marker combinations that yielded differences greater than 5 degrees were tested with paired t-tests and the relationship between number of markers and kinematic errors were modeled with polynomials to determine goodness of fit (R²).

Results

Sagittal joint and hip coronal kinematics errors were smaller than documented errors caused by soft-tissue artifact, which tends to be approximately 5 degrees, when excluding thigh and shank markers. Joint angle and center kinematic errors negatively correlated with the number of markers included in the analyses (R² > 0.97) and typically showed the greatest error reductions when two markers were included on the thigh or shank segments. Further, we demonstrated that a simplified marker set that included markers on the pelvis, lateral knee condyle, lateral malleolus, and shoes produced kinematics that strongly agreed with the traditional marker set that included 3 tracking markers for each segment.

Conclusion

Constrained-kinematic models are resilient to marker placement and quantity, which has implications on study design and post-processing workflows.

An extended OpenSim knee model for analysis of strains of connective tissues

Background

OpenSim musculoskeletal models provide an accurate simulation environment that eases limitations of in vivo and in vitro studies. In this work, a biomechanical knee model was formulated with femoral articular cartilages and menisci along with 25 connective tissue bundles representing ligaments and capsules. The strain patterns of the connective tissues in the presence of femoral articular cartilage and menisci in the OpenSim knee model was probed in a first of its kind study.

Methods

The effect of knee flexion (0°–120°), knee rotation (− 40° to 30°) and knee adduction (− 15° to 15°) on the anterior cruciate, posterior cruciate, medial collateral, lateral collateral ligaments and other connective tissues were studied by passive simulation. Further, a new parameter for assessment of strain namely, the differential inter-bundle strain of the connective tissues were analyzed to provide new insights for injury kinematics.

Results

ACL, PCL, LCL and PL was observed to follow a parabolic strain pattern during flexion while MCL represented linear strain patterns. All connective tissues showed non-symmetric parabolic strain variation during rotation. During adduction, the strain variation was linear for the knee bundles except for FL, PFL and TL.

Conclusions

Strains higher than 0.1 were observed in most of the bundles during lateral rotation followed by abduction, medial rotation and adduction. In the case of flexion, highest strains were observed in aACL and aPCL. A combination of strains at a flexion of 0° with medial rotation of 30° or a flexion of 80° with rotation of 30° are evaluated as rupture-prone kinematics.

Electronic supplementary material

The online version of this article (10.1186/s12938-018-0474-8) contains supplementary material, which is available to authorized users.

Commentary on the integration of model sharing and reproducibility analysis to scholarly publishing workflow in computational biomechanics

OBJECTIVE

The overall goal of this paper is to demonstrate that dissemination of models and analyses for assessing the reproducibility of simulation results can be incorporated in the scientific review process in biomechanics.

METHODS

As part of a special issue on model sharing and reproducibility in the IEEE Transactions on Biomedical Engineering, two manuscripts on computational biomechanics were submitted: Rajagopal et al., IEEE Trans. Biomed. Eng., 2016 and Schmitz and Piovesan, IEEE Trans. Biomed. Eng., 2016. Models used in these studies were shared with the scientific reviewers and the public. In addition to the standard review of the manuscripts, the reviewers downloaded the models and performed simulations that reproduced results reported in the studies.

RESULTS

There was general agreement between simulation results of the authors and those of the reviewers. Discrepancies were resolved during the necessary revisions. The manuscripts and instructions for download and simulation were updated in response to the reviewers' feedback; changes that may otherwise have been missed if explicit model sharing and simulation reproducibility analysis was not conducted in the review process. Increased burden on the authors and the reviewers, to facilitate model sharing and to repeat simulations, were noted.

CONCLUSION

When the authors of computational biomechanics studies provide access to models and data, the scientific reviewers can download and thoroughly explore the model, perform simulations, and evaluate simulation reproducibility beyond the traditional manuscript-only review process.

SIGNIFICANCE

Model sharing and reproducibility analysis in scholarly publishing will result in a more rigorous review process, which will enhance the quality of modeling and simulation studies and inform future users of computational models.