Estimating patient-specific soft-tissue properties in a TKA knee

Influence of the Initial Guess on the Estimation of Knee Ligament Parameters via Optimization Procedures

Optimization procedures provide ligament parameters by minimizing the difference between experimental measurements and computational simulations. Literature values are used as initial guesses of ligament parameters for these optimization procedures. However, it remains unknown how these values affect the estimation of ligament parameters. This study evaluates the effects of the initial guess on estimations of ligament parameters. A synthetic data set was generated using a subject-specific knee computational model, reference ligament parameters and simulated laxity tests. Subsequently, ligament parameters were estimated using an optimization routine and four different initial guesses. The distance of these initial guesses from their true values ranged from 0 to 3.5 kN and from 0 to 3.6% for the stiffness and reference strains, respectively. The optimized ligament parameters had an average absolute mean error ranging from 0.15 (0.09) kN and 0.08 (0.04)% to 3.67 (2.46) kN and 1.25 (0.76)%, while the kinematic error remained below 1 mm and 1.2° for all conditions. Our results showed that the estimations of the ligament parameters worsened as the initial guesses moved farther away from their true values. Moreover, the optimization procedure resulted in suboptimal ligament parameters that provided similar behavior to the true laxity behavior, which is an alarming finding that should be further investigated.

Methodology to identify subject-specific dynamic laxity tests to stretch individual parts of knee ligaments

The mechanical properties of ligaments are important for multiple applications and are often estimated from laxity tests. However, the typical laxity tests are not optimized for this application and, a potential exists to develop better laxity tests in this respect. Therefore, the purpose of this study was to develop a methodology to identify optimal, dynamic laxity tests that isolate the stretch of the individual ligaments from each other. To this end, we applied an existing rigid body-based knee model and a dataset of ∼100.000 random samples of applied forces (0-150 N), moments (0-10 Nm) and knee flexion angles (0-90°) through Monte Carlo Simulations. For each modelled ligament bundle, we identified ten load cases; one producing the highest force and nine equally spaced between the maximal and zero force, where the maximal force in all other ligament bundles were minimized. We compared these novel laxity tests to standard internal/external and varus/valgus laxity tests using an isolation metric. We found that no laxity test could stretch the anterior part of the posterior cruciate and medial cruciate ligaments (PCL and MCL), whereas for all other ligaments, except the posterior PCL, the new laxity tests isolated the ligament stretch 28 % to 450 % better than standard tests. From our study, we conclude that it is possible to define better laxity tests than currently exist and these may be highly relevant for determination of mechanical properties of ligaments in vivo. Future studies should generalize our results and translate them to modern laxity measurements technologies.

Calibration of Holzapfel-Gasser-Ogden collateral ligament properties in a hybrid post-arthroplasty knee joint model for laxity testing

Knee collateral ligaments play a vital role in providing frontal-plane stability in post-total knee arthroplasty (TKA) knees. Finite element models can utilize computationally efficient one-dimensional springs or more physiologically accurate three-dimensional continuum elements like the Holzapfel-Gasser-Ogden (HGO) formulation. However, there is limited literature defining subject-specific mechanical properties, particularly for the HGO model. In this study, we propose a co-simulation framework to obtain subject-specific material parameters for an HGO-based finite element ligament model integrated into a rigid-body model of the post-TKA knee. Our approach achieves comparable accuracy to spring formulations while significantly reducing coefficient calibration time and demonstrating improved correlation with reference knee kinematics and ligament strains throughout the tested loading range.

Modeling of the native knee with kinematic data derived from experiments using the VIVO™ joint simulator: a feasibility study

BACKGROUND

Despite advances in total knee arthroplasty, many patients are still unsatisfied with the functional outcome. Multibody simulations enable a more efficient exploration of independent variables compared to experimental studies. However, to what extent numerical models can fully reproduce knee joint kinematics is still unclear. Hence, models must be validated with different test scenarios before being applied to biomechanical questions.

METHODS

In our feasibility study, we analyzed a human knee specimen on a six degree of freedom joint simulator, applying a passive flexion and different laxity tests with sequential states of ligament resection while recording the joint kinematics. Simultaneously, we generated a subject-specific multibody model of the native tibiofemoral joint considering ligaments and contact between articulating cartilage surfaces.

RESULTS

Our experimental data on the sequential states of ligament resection aligned well with the literature. The model-based knee joint kinematics during passive flexion showed good agreement with the experiment, with root-mean-square errors of less than 1.61 mm for translations and 2.1° for knee joint rotations. During laxity tests, the experiment measured up to 8 mm of anteroposterior laxity, while the numerical model allowed less than 3 mm.

CONCLUSION

Although the multibody model showed good agreement to the experimental kinematics during passive flexion, the validation showed that ligament parameters used in this feasibility study are too stiff to replicate experimental laxity tests correctly. Hence, more precise subject-specific ligament parameters have to be identified in the future through model optimization.

The effect of trapeziometacarpal joint passive stiffness on mechanical loadings of cartilages

Hypermobility of the trapeziometacarpal joint is commonly considered to be a potential risk factor for osteoarthritis. Nevertheless, the results remain controversial due to a lack of quantitative validation. The objective of this study was to evaluate the effect of joint laxity on the mechanical loadings of cartilage. A patient-specific finite element model of trapeziometacarpal joint passive stiffness was developed. The joint passive stiffness was modeled by creating linear springs all around the joint. The linear spring stiffness was determined by using an optimization process to fit force-displacement data measured during laxity tests performed on eight healthy volunteers. The estimated passive stiffness parameters were then included in a full thumb finite element simulation of a pinch grip task driven by muscle forces to evaluate the effect on trapeziometacarpal loading. The correlation between stiffness and the loading of cartilage in terms of joint contact pressure and maximum shear strain was analyzed. A significant negative correlation was found between the trapeziometacarpal joint passive stiffness and the contact pressure on trapezium cartilage during the simulated pinch grip task. These results therefore suggest that the hypermobility of the trapeziometacarpal joint could affect the contact pressure on trapezium cartilage and support the existence of an increased risk associated with hypermobility.

Instantaneous Generation of Subject-Specific Finite Element Models of the Hip Capsule

Subject-specific hip capsule models could offer insights into impingement and dislocation risk when coupled with computer-aided surgery, but model calibration is time-consuming using traditional techniques. This study developed a framework for instantaneously generating subject-specific finite element (FE) capsule representations from regression models trained with a probabilistic approach. A validated FE model of the implanted hip capsule was evaluated probabilistically to generate a training dataset relating capsule geometry and material properties to hip laxity. Multivariate regression models were trained using 90% of trials to predict capsule properties based on hip laxity and attachment site information. The regression models were validated using the remaining 10% of the training set by comparing differences in hip laxity between the original trials and the regression-derived capsules. Root mean square errors (RMSEs) in laxity predictions ranged from 1.8° to 2.3°, depending on the type of laxity used in the training set. The RMSE, when predicting the laxity measured from five cadaveric specimens with total hip arthroplasty, was 4.5°. Model generation time was reduced from days to milliseconds. The results demonstrated the potential of regression-based training to instantaneously generate subject-specific FE models and have implications for integrating subject-specific capsule models into surgical planning software.

Design and evaluation of a 3D printed mechanical balancer for soft tissue balancing in total knee replacement

PURPOSE

Soft tissue balancing is an important step in a total knee procedure, carried out manually, or using an indicator. The purpose of this study was to evaluate our design of 3D printed Balancer, and demonstrate how it could be used at surgery.

PROCEDURES

When inserted between the femur and tibia, the Balancer displayed the forces acting across the lateral and medial compartments, indicated by pointers at the end of the handle. A loading rig was used to measure the pointer deflections for different forces applied at different locations on the condyle surfaces. Repeatability and reproducibilty were evaluated. The Balancer was tested in six fresh knee specimens using a surgical simulation rig.

MAIN FINDINGS

Pointer deflections of up to 12 millimeters occurred for less than 1 mm displacements at the condyle surfaces. Reproducibility tests showed a standard deviation of 14% at lower loads, reducing to only 4% at higher loads. Mean pointer deflections were within 8% for forces applied at ±10 mm AP, and +5/-3 mm in an ML direction, relative to the neutral contact point. In specimens, most lateral to medial force differences could be corrected by a 2° change in frontal plane angle of the tibial resection. Effects of ligament releases were also demonstrated.

PRINCIPAL CONCLUSIONS

The 3D printed Balancer was easy to use, and provided the surgeon with lateral and medial force data over a full range of flexion, enabling possible corrective procedures to be specified.

Polynomial chaos expansion based sensitivity analysis of predicted knee reactions-assessing the influence of the primary ligaments in distraction based models

Computational knee models have shown that predicted condylar reactions are sensitive to the utilized ligament mechanical parameters. These models, however, are computationally expensive with multiple sources of uncertainty. Traditional uncertainty analysis using Monte-Carlo (MC) inspired methods are costly to perform. The purpose of this study was to use two example calibrated knee models to compare quasi-MC versus polynomial chaos expansion (PCE) sensitivity analyses of predicted condylar reactions that included uncertainty in the mechanical parameters of the ligaments. PCE was practically identical versus quasi-MC with 95% and 98% reductions in model evaluations for analyses with 10 and 6 uncertain variables, respectively.

Development of Multibundle Virtual Ligaments to Simulate Knee Mechanics After Total Knee Arthroplasty

Preclinical evaluation of total knee arthroplasty (TKA) components is essential to understanding their mechanical behavior and developing strategies for improving joint stability. While preclinical testing of TKA components has been useful in quantifying their effectiveness, such testing can be criticized for lacking clinical relevance, as the important contributions of surrounding soft tissues are either neglected or greatly simplified. The purpose of our study was to develop and determine if subject-specific virtual ligaments reproduce a similar behavior as native ligaments surrounding TKA joints. Six TKA knees were mounted to a motion simulator. Each was subjected to tests of anterior-posterior (AP), internal-external (IE), and varus-valgus (VV) laxity. The forces transmitted through major ligaments were measured using a sequential resection technique. By tuning the measured ligament forces and elongations to a generic nonlinear elastic ligament model, virtual ligaments were designed and used to simulate the soft tissue envelope around isolated TKA components. The average root-mean-square error (RMSE) between the laxity results of TKA joints with native versus virtual ligaments was 3.5 ± 1.8 mm during AP translation, 7.5 ± 4.2 deg during IE rotations, and 2.0 ± 1.2 deg during VV rotations. Interclass correlation coefficients (ICCs) indicated a good level of reliability for AP and IE laxity (0.85 and 0.84). To conclude, the advancement of virtual ligament envelopes as a more realistic representation of soft tissue constraint around TKA joints is a valuable approach for obtaining clinically relevant kinematics when testing TKA components on joint motion simulators.

Bayesian Calibration of Computational Knee Models to Estimate Subject-Specific Ligament Properties, Tibiofemoral Kinematics, and Anterior Cruciate Ligament Force With Uncertainty Quantification

High-grade knee laxity is associated with early anterior cruciate ligament (ACL) graft failure, poor function, and compromised clinical outcome. Yet, the specific ligaments and ligament properties driving knee laxity remain poorly understood. We described a Bayesian calibration methodology for predicting unknown ligament properties in a computational knee model. Then, we applied the method to estimate unknown ligament properties with uncertainty bounds using tibiofemoral kinematics and ACL force measurements from two cadaver knees that spanned a range of laxities; these knees were tested using a robotic manipulator. The unknown ligament properties were from the Bayesian set of plausible ligament properties, as specified by their posterior distribution. Finally, we developed a calibrated predictor of tibiofemoral kinematics and ACL force with their own uncertainty bounds. The calibrated predictor was developed by first collecting the posterior draws of the kinematics and ACL force that are induced by the posterior draws of the ligament properties and model parameters. Bayesian calibration identified unique ligament slack lengths for the two knee models and produced ACL force and kinematic predictions that were closer to the corresponding in vitro measurement than those from a standard optimization technique. This Bayesian framework quantifies uncertainty in both ligament properties and model outputs; an important step towards developing subject-specific computational models to improve treatment for ACL injury.

Assessment of reporting practices and reproducibility potential of a cohort of published studies in computational knee biomechanics

Reproducible research serves as a pillar of the scientific method and is a foundation for scientific advancement. However, estimates for irreproducibility of preclinical science range from 75% to 90%. The importance of reproducible science has not been assessed in the context of mechanics-based modeling of human joints such as the knee, despite this being an area that has seen dramatic growth. Framed in the context of five experienced teams currently documenting knee modeling procedures, the aim of this study was to evaluate reporting and the perceived potential for reproducibility across studies the teams viewed as important contributions to the literature. A cohort of studies was selected by polling, which resulted in an assessment of nine studies as opposed to a broader analysis across the literature. Using a published checklist for reporting of modeling features, the cohort was evaluated for both "reporting" and their potential to be "reproduced," which was delineated into six major modeling categories and three subcategories. Logistic regression analysis revealed that for individual modeling categories, the proportion of "reported" occurrences ranged from 0.31, 95% confidence interval (CI) [0.23, 0.41] to 0.77, 95% CI: [0.68, 0.86]. The proportion of whether a category was perceived as "reproducible" ranged from 0.22, 95% CI: [0.15, 0.31] to 0.44, 95% CI: [0.35, 0.55]. The relatively low ratios highlight an opportunity to improve reporting and reproducibility of knee modeling studies. Ongoing efforts, including our findings, contribute to a dialogue that facilitates adoption of practices that provide both credibility and translation possibilities.

Rotational Soft-Tissue Balance Is Highly Correlated with Rotational Kinematics in Total Knee Arthroplasty

Recovery of normal knee kinematics is critical for improving functional outcomes and patient satisfaction after total knee arthroplasty (TKA). The kinematics pattern after TKA varies from case to case, and it remains unclear how to reproduce normal knee kinematics. The present study aimed to evaluate rotational knee kinematics and soft-tissue balance using a navigation system and to assess the influence of intraoperative soft-tissue balance on the rotational knee kinematics. We evaluated 81 osteoarthritic knees treated with TKA using a posterior stabilized (50 knees) or cruciate retaining (31 knees) prosthesis. Rotational kinematics were assessed at 0, 30, 45, 60, and 90 degrees flexion angles by using a computer-assisted navigation system. Correlation between femorotibial rotational position and measured soft tissue balance was assessed by using Spearman's rank correlation coefficient. Rotational soft-tissue balance (the median angle of rotational stress) was significantly correlated with rotational kinematics (rotational axis of the femur relative to the tibia throughout the range of motion) at all measured angles after TKA. The correlation coefficients between the median angle of rotational stress and rotational kinematics were 0.97, 0.80, 0.74, 0.71, and 0.70 at 0, 30, 45, 60, and 90 degrees of flexion, respectively (p-values <0.0001 in all measured angles). The correlation coefficient increased as the knee approached full extension. Our findings suggest that soft-tissue balance is a key factor for rotational kinematics, following both cruciate-retaining and posterior-stabilized TKA.

Can TKA outcomes be predicted with computational simulation? Generation of a patient specific planning tool

BACKGROUND

Computer simulations of knee movement allow Total Knee Arthroplasty (TKA) dynamic outcomes to be studied. This study aims to build a model predicting patient reported outcome from a simulation of post-operative TKA joint dynamics.

METHODS

Landmark localisation was performed on 239 segmented pre-operative computerized tomography (CT) scans to capture patient specific soft tissue attachments. The pre-operative bones and 3D implant files were registered to post-operative CT scans following TKA. Each post-operative knee was simulated undergoing a deep knee bend with assumed ligament balancing of the extension space. The kinematic results from this simulation were used in a Multivariate Adaptive Regression Spline algorithm, predicting attainment of a Patient Acceptable Symptom State (PASS) score in captured 12 month post-operative Knee Injury and Osteoarthritis Outcome Scores (KOOS). An independent series of 250 patients was evaluated by the predictive model to assess how the predictive model behaved in a pre-operative planning context.

RESULTS

The generated predictive algorithm, called the Dynamic Knee Score (DKS) contained features, in order of significance, related to tibio-femoral force, patello-femoral motion and tibio-femoral motion. Area Under the Curve for predicting attainment of the PASS KOOS Score was 0.64. The predictive model produced a bimodal spread of predictions, reflecting a tendency to either strongly prefer one alignment plan over another or be ambivalent.

CONCLUSION

A predictive algorithm relating patient reported outcome to the outputs of a computational simulation of a deep knee bend has been derived (the DKS). Simulation outcomes related to tibio-femoral balance had the highest correlation with patient reported outcome.

WraptMor: Confirmation of an Approach to Estimate Ligament Fiber Length and Reactions With Knee-Specific Morphology

Knee ligament length can be used to infer ligament recruitment during functional activities and subject-specific morphology affects the interplay between ligament recruitment and joint motion. This study presents an approach that estimated ligament fiber insertion-to-insertion lengths with wrapping around subject-specific osseous morphology (WraptMor). This represents an advancement over previous work that utilized surrogate geometry to approximate ligament interaction with bone surfaces. Additionally, the reactions each ligament imparted onto bones were calculated by assigning a force-length relationship (kinetic WraptMor model), which assumed that the insertion-to-insertion lengths were independent of the assigned properties. Confirmation of the approach included comparing WraptMor predicted insertion-to-insertion length and reactions with an equivalent displacement-controlled explicit finite element model. Both models evaluated 10 ligament bundles at 16 different joint positions, which were repeated for five different ligament prestrain values for a total of 80 simulations per bundle. The WraptMor and kinetic WraptMor models yielded length and reaction predictions that were similar to the equivalent finite element model. With a few exceptions, predicted ligament lengths and reactions agreed to within 0.1 mm and 2.0 N, respectively, across all tested joint positions and prestrain values. The primary source of discrepancy between the models appeared to be caused by artifacts in the finite element model. The result is a relatively efficient approach to estimate ligament lengths and reactions that include wrapping around knee-specific bone surfaces.

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

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

Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy

Recent explorations of knee biomechanics have benefited from computational modeling, specifically leveraging advancements in finite element analysis and rigid body dynamics of joint and tissue mechanics. A large number of models have emerged with different levels of fidelity in anatomical and mechanical representation. Adapted modeling and simulation processes vary widely, based on justifiable choices in relation to anticipated use of the model. However, there are situations where modelers' decisions seem to be subjective, arbitrary, and difficult to rationalize. Regardless of the basis, these decisions form the "art" of modeling, which impact the conclusions of simulation-based studies on knee function. These decisions may also hinder the reproducibility of models and simulations, impeding their broader use in areas such as clinical decision making and personalized medicine. This document summarizes an ongoing project that aims to capture the modeling and simulation workflow in its entirety-operation procedures, deviations, models, by-products of modeling, simulation results, and comparative evaluations of case studies and applications. The ultimate goal of the project is to delineate the art of a cohort of knee modeling teams through a publicly accessible, transparent approach and begin to unravel the complex array of factors that may lead to a lack of reproducibility. This manuscript outlines our approach along with progress made so far. Potential implications on reproducibility, on science, engineering, and training of modeling and simulation, on modeling standards, and on regulatory affairs are also noted.

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.

Effects of femoral component placement on the balancing of a total knee at surgery

Misalignment and soft-tissue imbalance in total knee arthroplasty (TKA) can cause discomfort, pain, inadequate motion and instability that may require revision surgery. Balancing can be defined as equal collateral ligament tensions or equal medial and lateral compartmental forces during the flexion range. Our goal was to study the effects on balancing of linear femoral component misplacements (proximal, distal, anterior, posterior); and different component rotations in mechanical alignment compared to kinematic alignment throughout the flexion path. A test rig was constructed such that the position of a standard femoral component could be adjusted to simulate the linear and rotational positions. With the knee in neutral reference values of the collateral tensions were adjusted to give anatomic contact force patterns, measured with an instrumented tibial trial. The deviations in the forces for each femoral component position were then determined. Compartmental forces were significantly influenced by 2 mm linear errors in the femoral component placement. However, the errors were least for a distal error, equivalent to undercutting the distal femur. The largest errors mainly increase the lateral condyle force, occurred for proximal and posterior component errors. There were only small contact force differences between kinematic and mechanical alignment. Based on these results, surgeons should avoid overcutting the distal femur and undercutting the posterior femur. However, the 2-3 degrees varus slope of the joint line as in kinematic alignment did not have much effect on balancing, so mechanical or kinematic alignment were equivalent.

Medially-stabilized total knee arthroplasty does not alter knee laxity and balance in cadaveric knees

Instability after total knee arthroplasty (TKA) can lead to suboptimal outcomes and revision surgery. Medially-stabilized implants aim to more closely replicate normal knee motion than other implants following TKA, but no study has investigated knee laxity (motion under applied loads) and balance (i.e., difference in varus/valgus motion under load) following medially-stabilized TKA. The primary purposes of this study were to investigate how medially-stabilized implants change knee laxity in non-arthritic, cadaveric knees, and if it produces a balanced knee after TKA. Force-displacement data were collected on 18 non-arthritic cadaveric knees before and after arthroplasty using medially-stabilized implants. Varus-valgus and anterior-posterior laxity and varus-valgus balance were compared between native and medially-stabilized knees at 0°, 20°, 60°, and 90° under three different loading conditions. Varus-valgus and anterior-posterior laxities were not different between native and medially-stabilized knees under most testing conditions (p ≥ 0.068), but differences of approximately 2° less varus-valgus laxity at 20° of flexion and 4 mm more anterior-posterior laxity at 90° were present from native laxities (p < 0.017) Medially-stabilized implant balance had ≤1.5° varus bias at all flexion angles. Future studies should confirm if the consistent laxity afforded by the medially-stabilized implant is associated with better and more predictable postoperative outcomes. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:335-349, 2019.

Personalised 3D knee compliance from clinically viable knee laxity measurements: A proof of concept ex vivo experiment

Personalised information of knee mechanics is increasingly used for guiding knee reconstruction surgery. We explored use of uniaxial knee laxity tests mimicking Lachman and Pivot-shift tests for quantifying 3D knee compliance in healthy and injured knees. Two healthy knee specimens (males, 60 and 88 years of age) were tested. Six-degree-of-freedom tibiofemoral displacements were applied to each specimen at 5 intermediate angles between 0° and 90° knee flexion. The force response was recorded. Six-degree-of-freedom and uniaxial tests were repeated after sequential resection of the anterior cruciate, posterior cruciate and lateral collateral ligament. 3D knee compliance (C_6DOF) was calculated using the six-degrees-of-freedom measurements for both the healthy and ligament-deficient knees and validated using a leave-one-out cross-validation. 3D knee compliance (C_CT) was also calculated using uniaxial measurements for Lachman and Pivot-shift tests both conjointly and separately. C_6DOF and C_CT matrices were compared component-by-component and using principal axes decomposition. Bland-Altman plots, median and 40-60th percentile range were used as measurements of bias and dispersion. The error on tibiofemoral displacements predicted using C_6DOF was < 9.6% for every loading direction and after release of each ligament. Overall, there was good agreement between C_6DOF and C_CT components for both the component-by-component and principal component comparison. The dispersion of principal components (compliance coefficients, positions and pitches) based on both uniaxial tests was lower than that based on single uniaxial tests. Uniaxial tests may provide personalised information of 3D knee compliance.

Patient-Specific Simulated Dynamics After Total Knee Arthroplasty Correlate With Patient-Reported Outcomes

BACKGROUND

Component alignment variation following total knee arthroplasty (TKA) does not fully explain the instance of long-term postoperative pain. Joint dynamics following TKA vary with component alignment and patient-specific musculoskeletal anatomy. Computational simulations allow joint dynamics outcomes to be studied across populations. This study aims to determine if simulated postoperative TKA joint dynamics correlate with patient-reported outcomes.

METHODS

Landmarking and 3D registration of implants was performed on 96 segmented postoperative computed tomography scans of TKAs. A cadaver rig-validated platform for generating patient-specific simulation of deep knee bend kinematics was run for each patient. Resultant dynamic outcomes were correlated with a 12-month postoperative Knee Injury and Osteoarthritis Outcome Score (KOOS). A Classification and Regression Tree (CART) was used for determining nonlinear relationships.

RESULTS

Nonlinear relationships between the KOOS pain score and rollback and dynamic coronal alignment were found to be significant. Combining a dynamic coronal angular change from extension to full flexion between 0° and 4° varus (long leg axis) and measured rollback of no more than 6 mm without rollforward formed a "kinematic safe zone" of outcomes in which the postoperative KOOS score is 10.5 points higher (P = .013).

CONCLUSION

The study showed statistically significant correlations between kinematic factors in a simulation of postoperative TKA and postoperative KOOS scores. The presence of a dynamic safe zone in the data suggests a potential optimal target for any given individual patient's joint dynamics and the opportunity to preoperatively determine a patient-specific alignment target to achieve those joint dynamics.

Applying a Hybrid Experimental-Computational Technique to Study Elbow Joint Ligamentous Stabilizers

Much of our understanding of the role of elbow ligaments to overall joint biomechanics has been developed through in vitro cadaver studies using joint motion simulators. The principle of superposition can be used to indirectly compute the force contributions of ligaments during prescribed motions. Previous studies have analyzed the contribution of different soft tissue structures to the stability of human elbow joints, but have limitations in evaluating the loads sustained by those tissues. This paper introduces a unique, hybrid experimental-computational technique for measuring and simulating the biomechanical contributions of ligaments to elbow joint kinematics and stability. in vitro testing of cadaveric joints is enhanced by the incorporation of fully parametric virtual ligaments, which are used in place of the native joint stabilizers to characterize the contribution of elbow ligaments during simple flexion–extension (FE) motions using the principle of superposition. Our results support previously reported findings that the anterior medial collateral ligament (AMCL) and the radial collateral ligament (RCL) are the primary soft tissue stabilizers for the elbow joint. Tuned virtual ligaments employed in this study were able to restore the kinematics and laxity of elbows to within 2 deg of native joint behavior. The hybrid framework presented in this study demonstrates promising capabilities in measuring the biomechanical contribution of ligamentous structures to joint stability.

Neural Network Optimization of Ligament Stiffnesses for the Enhanced Predictive Ability of a Patient-Specific, Computational Foot/Ankle Model

Computational models of diarthrodial joints serve to inform the biomechanical function of these structures, and as such, must be supplied appropriate inputs for performance that is representative of actual joint function. Inputs for these models are sourced from both imaging modalities as well as literature. The latter is often the source of mechanical properties for soft tissues, like ligament stiffnesses; however, such data are not always available for all the soft tissues nor is it known for patient-specific work. In the current research, a method to improve the ligament stiffness definition for a computational foot/ankle model was sought with the greater goal of improving the predictive ability of the computational model. Specifically, the stiffness values were optimized using artificial neural networks (ANNs); both feedforward and radial basis function networks (RBFNs) were considered. Optimal networks of each type were determined and subsequently used to predict stiffnesses for the foot/ankle model. Ultimately, the predicted stiffnesses were considered reasonable and resulted in enhanced performance of the computational model, suggesting that artificial neural networks can be used to optimize stiffness inputs.

Computational model-based probabilistic analysis of in vivo material properties for ligament stiffness using the laxity test and computed tomography

The objective of this paper was to evaluate in vivo material properties in order to address technical aspects of computational modeling of ligaments in the tibiofemoral joint using a probabilistic method. The laxity test was applied to the anterior-posterior drawer under 30° and 90° of flexion with a series of stress radiographs, a Telos device, and computed tomography. Ligament stiffness was investigated using sensitivity analysis based on the Monte-Carlo method with a subject-specific finite element model generated from in vivo computed tomography and magnetic resonance imaging data, subjected to laxity test conditions. The material properties of ligament stiffness and initial ligament strain in a subject-specific finite element model were optimized to minimize the differences between the movements of the tibia and femur in the finite element model and the computed tomography images in the laxity test. The posterior cruciate ligament was the most significant factor in flexion and posterior drawer, while the anterior cruciate ligament primarily was the most significant factor for the anterior drawer. The optimized material properties model predictions in simulation and the laxity test were more accurate than predictions based on the initial material properties in subject-specific computed tomography measurement. Thus, this study establishes a standard for future designs in allograft, xenograft, and artificial ligaments for anterior cruciate ligament and posterior cruciate ligament injuries.

Traditional Chinese medicines in the management of cardiovascular diseases: a comprehensive systematic review

AIMS

The aim was to perform a systematic review of the efficacy of traditional Chinese medicines (TCM) in cardiovascular disease.

METHODS

Electronic databases were searched up to 11 November 2015 for all randomized-controlled trials evaluating the effect of TCM in hypertension, ischaemic stroke, heart failure, coronary heart disease and type 2 diabetes mellitus. Pooled odds ratios (ORs) were calculated using a fixed-effects model.

RESULTS

Four hypertension studies were eligible for statistical analysis and included 133 patients receiving TCM and 130 control patients. There were significant reductions in systolic blood pressure in patients receiving TCM, comparable to results achieved with pharmaceutical medicines. An OR of 3.781 (95% confidence interval 2.392, 5.977; P = 0.000) was observed for the anti-hypertensive effect of TCM. Significant heterogeneity was present (P = 0.011), with a tendency towards publication bias that did not reach significance (P = 0.05275). Outcome measures for other cardiovascular diseases were inconsistent.

CONCLUSIONS

Certain TCM compounds appear to have significant anti-hypertensive effects, and although some are associated in some studies with improved outcomes in coronary heart disease, heart failure and type 2 diabetes mellitus, the data are inconsistent and will require large-scale randomized-controlled trials to allow full evaluation of any potential therapeutic benefit in these areas.