Simplified Mechanical Tests Can Simulate Physiological Mechanics of a Fixation Construct for Periprosthetic Femoral Fractures.

Plate fractures after fixation of a Vancouver Type B1 periprosthetic femoral fracture (PFF) are difficult to treat and could lead to severe disability. However, due to the lack of direct measurement of in vivo performance of the PFF fixation construct, it is unknown whether current standard mechanical tests or previous experimental and computational studies have appropriately reproduced the in vivo mechanics of the plate. To provide a basis for the evaluation and development of appropriate mechanical tests for assessment of plate fracture risk, this study applied loads of common activities of daily living (ADLs) to implanted femur finite element (FE) models with PFF fixation constructs with an existing or a healed PFF. Based on FE simulated plate mechanics, the standard four-point-bend test adequately matched the stress state and the resultant bending moment in the plate as compared with femur models with an existing PFF. In addition, the newly developed constrained three-point-bend tests were able to reproduce plate stresses in models with a healed PFF. Furthermore, a combined bending and compression cadaveric test was appropriate for risk assessment including both plate fracture and screw loosening after the complete healing of PFF. The result of this study provides the means for combined experimental and computational preclinical evaluation of PFF fixation constructs.

The Use of Synthetic IMU Signals in the Training of Deep Learning Models Significantly Improves the Accuracy of Joint Kinematic Predictions.

Gait analysis based on inertial sensors has become an effective method of quantifying movement mechanics, such as joint kinematics and kinetics. Machine learning techniques are used to reliably predict joint mechanics directly from streams of IMU signals for various activities. These data-driven models require comprehensive and representative training datasets to be generalizable across the movement variability seen in the population at large. Bottlenecks in model development frequently occur due to the lack of sufficient training data and the significant time and resources necessary to acquire these datasets. Reliable methods to generate synthetic biomechanical training data could streamline model development and potentially improve model performance. In this study, we developed a methodology to generate synthetic kinematics and the associated predicted IMU signals using open source musculoskeletal modeling software. These synthetic data were used to train neural networks to predict three degree-of-freedom joint rotations at the hip and knee during gait either in lieu of or along with previously measured experimental gait data. The accuracy of the models' kinematic predictions was assessed using experimentally measured IMU signals and gait kinematics. Models trained using the synthetic data out-performed models using only the experimental data in five of the six rotational degrees of freedom at the hip and knee. On average, root mean square errors in joint angle predictions were improved by 38% at the hip (synthetic data RMSE: 2.3°, measured data RMSE: 4.5°) and 11% at the knee (synthetic data RMSE: 2.9°, measured data RMSE: 3.3°), when models trained solely on synthetic data were compared to measured data. When models were trained on both measured and synthetic data, root mean square errors were reduced by 54% at the hip (measured + synthetic data RMSE: 1.9°) and 45% at the knee (measured + synthetic data RMSE: 1.7°), compared to measured data alone. These findings enable future model development for different activities of clinical significance without the burden of generating large quantities of gait lab data for model training, streamlining model development, and ultimately improving model performance.

Deep Learning in Gait Parameter Prediction for OA and TKA Patients Wearing IMU Sensors.

Quantitative assessments of patient movement quality in osteoarthritis (OA), specifically spatiotemporal gait parameters (STGPs), can provide in-depth insight into gait patterns, activity types, and changes in mobility after total knee arthroplasty (TKA). A study was conducted to benchmark the ability of multiple deep neural network (DNN) architectures to predict 12 STGPs from inertial measurement unit (IMU) data and to identify an optimal sensor combination, which has yet to be studied for OA and TKA subjects. DNNs were trained using movement data from 29 subjects, walking at slow, normal, and fast paces and evaluated with cross-fold validation over the subjects. Optimal sensor locations were determined by comparing prediction accuracy with 15 IMU configurations (pelvis, thigh, shank, and feet). Percent error across the 12 STGPs ranged from 2.1% (stride time) to 73.7% (toe-out angle) and overall was more accurate in temporal parameters than spatial parameters. The most and least accurate sensor combinations were feet-thighs and singular pelvis, respectively. DNNs showed promising results in predicting STGPs for OA and TKA subjects based on signals from IMU sensors and overcomes the dependency on sensor locations that can hinder the design of patient monitoring systems for clinical application.

Prediction of In Vivo Knee Joint Loads Using a Global Probabilistic Analysis.

Musculoskeletal models are powerful tools that allow biomechanical investigations and predictions of muscle forces not accessible with experiments. A core challenge modelers must confront is validation. Measurements of muscle activity and joint loading are used for qualitative and indirect validation of muscle force predictions. Subject-specific models have reached high levels of complexity and can predict contact loads with surprising accuracy. However, every deterministic musculoskeletal model contains an intrinsic uncertainty due to the high number of parameters not identifiable in vivo. The objective of this work is to test the impact of intrinsic uncertainty in a scaled-generic model on estimates of muscle and joint loads. Uncertainties in marker placement, limb coronal alignment, body segment parameters, Hill-type muscle parameters, and muscle geometry were modeled with a global probabilistic approach (multiple uncertainties included in a single analysis). 5-95% confidence bounds and input/output sensitivities of predicted knee compressive loads and varus/valgus contact moments were estimated for a gait activity of three subjects with telemetric knee implants from the "Grand Challenge Competition." Compressive load predicted for the three subjects showed confidence bounds of 333 ± 248 N, 408 ± 333 N, and 379 ± 244 N when all the sources of uncertainty were included. The measured loads lay inside the predicted 5-95% confidence bounds for 77%, 83%, and 76% of the stance phase. Muscle maximum isometric force, muscle geometry, and marker placement uncertainty most impacted the joint load results. This study demonstrated that identification of these parameters is crucial when subject-specific models are developed.

The Neuromuscular Response to Spinal Manipulation in the Presence of Pain.

OBJECTIVE: The purpose of this study was to evaluate differences in muscle activity in participants with and without low back pain during a side-lying lumbar diversified spinal manipulation. METHODS: Surface and indwelling electromyography at eight muscle locations were recorded during lumbar side-lying manipulations in 20 asymptomatic participants and 20 participants with low back pain. The number of muscle responses and muscle activity onset delays in relation to the manipulation impulse were compared in the 2 pain groups using mixed linear regressions. Effect sizes for all comparisons were calculated using Cohen's d. RESULTS: Muscle responses occurred in 61.6% ± 23.6% of the EMG locations in the asymptomatic group and 52.8% ± 26.3% of the symptomatic group. The difference was not statistically significant but there was a small effect of pain (d = 0.350). Muscle activity onset delays were longer for the symptomatic group at every EMG location except the right side indwelling L5 electrode, and a small effect of pain was present at the left L2, quadratus lumborum and trapezius surface electrodes (d = 0.311, 0.278, and 0.265) respectively. The indwelling electrodes demonstrated greater muscle responses (P ≤ .01) and shorter muscle activity onset delays (P < .01) than the surface electrodes. CONCLUSIONS: The results revealed trends that indicate participants with low back pain have less muscle responses, and when muscle responses are present they occur with longer onset delays following the onset of a manipulation impulse.

Methods of Muscle Activation Onset Timing Recorded During Spinal Manipulation.

OBJECTIVE: The purpose of this study was to determine electromyographic threshold parameters that most reliably characterize the muscular response to spinal manipulation and compare 2 methods that detect muscle activity onset delay: the double-threshold method and cross-correlation method. METHODS: Surface and indwelling electromyography were recorded during lumbar side-lying manipulations in 17 asymptomatic participants. Muscle activity onset delays in relation to the thrusting force were compared across methods and muscles using a generalized linear model. RESULTS: The threshold combinations that resulted in the lowest Detection Failures were the "8 SD-0 milliseconds" threshold (Detection Failures = 8) and the "8 SD-10 milliseconds" threshold (Detection Failures = 9). The average muscle activity onset delay for the double-threshold method across all participants was 149 ± 152 milliseconds for the multifidus and 252 ± 204 milliseconds for the erector spinae. The average onset delay for the cross-correlation method was 26 ± 101 for the multifidus and 67 ± 116 for the erector spinae. There were no statistical interactions, and a main effect of method demonstrated that the delays were higher when using the double-threshold method compared with cross-correlation. CONCLUSIONS: The threshold parameters that best characterized activity onset delays were an 8-SD amplitude and a 10-millisecond duration threshold. The double-threshold method correlated well with visual supervision of muscle activity. The cross-correlation method provides several advantages in signal processing; however, supervision was required for some results, negating this advantage. These results help standardize methods when recording neuromuscular responses of spinal manipulation and improve comparisons within and across investigations.

Specimen-specific finite element representations of implanted hip capsules.

The hip capsule is a ligamentous structure that contributes to hip stability. This article developed specimen-specific finite element models that replicated internal-external (I-E) laxity for ten implanted hip capsules. Capsule properties were calibrated to minimize root mean square error (RMSE) between model and experimental torques. RMSE across specimens was 1.02 ± 0.21 Nm for I-E laxity and 0.78 ± 0.33 Nm and 1.10 ± 0.48 Nm during anterior and posterior dislocation, respectively. RMSE for the same models with average capsule properties was 2.39 ± 0.68 Nm. Specimen-specific models demonstrated the importance of capsule tensioning in hip stability and have relevance for surgical planning and evaluation of implant designs.

Treatment and Response Factors in Muscle Activation during Spinal Manipulation.

The forces applied during a spinal manipulation produce a neuromuscular response in the paraspinal muscles. A systematic evaluation of the factors involved in producing this muscle activity provides a clinical insight. The purpose of this study is to quantify the effect of treatment factors (manipulation sequence and manipulation site) and response factors (muscle layer, muscle location, and muscle side) on the neuromuscular response to spinal manipulation. The surface and indwelling electromyographies of 8 muscle sites were recorded during lumbar side-lying manipulations in 20 asymptomatic participants. The effects of the factors on the number of muscle responses and the muscle activity onset delays were compared using mixed-model linear regressions, effect sizes, and equivalence testing. The treatment factors did not reveal statistical differences between the manipulation sequences (first or second) or manipulation sites (L3 or SI) in the number of muscle responses (p = 0.11, p = 0.28, respectively), or in muscle activity onset delays (p = 0.35 p = 0.35, respectively). There were significantly shorter muscle activity onset delays in the multifidi compared to the superficial muscles (p = 0.02). A small effect size of side (d = 0.44) was observed with significantly greater number of responses (p = 0.02) and shorter muscle activity onset delays (p < 0.001) in the muscles on the left side compared to the right. The location, layer, and side of the neuromuscular responses revealed trends of decreasing muscle response rates and increasing muscle activity onset delays as the distance from the manipulation site increased. These results build on the body of work suggesting that the specificity of manipulation site may not play a role in the neuromuscular response to spinal manipulation-at least within the lumbar spine. In addition, these results demonstrate that multiple manipulations performed in similar areas (L3 and S1) do not change the response significantly, as well as contribute to the clinical understanding that the muscle response rate is higher and with a shorter delay, the closer it is to the manipulation.

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.

Knee pivot location in asymptomatic older adults.

Representative data of asymptomatic, native-knee kinematics is important when studying changes in knee function across the lifespan. High-speed stereo radiography (HSSR) provides a reliable measure of knee kinematics to <1 mm of translation and 1° of rotation, but studies often have limited statistical power to make comparisons between groups or measure the contribution of individual variability. The purpose of this study is to examine in vivo condylar kinematics to quantify the transverse center-of-rotation, or pivot, location across the flexion range and challenge the medial-pivot paradigm in asymptomatic knee kinematics. We quantified the pivot location during supine leg press, knee extension, standing lunge, and gait for 53 middle-aged and older adults (27 men; 26 women: 50.8 ± 7.0 yrs, 1.75 ± 0.1 m, 79.1 ± 15.4 kg). A central- to medial-pivot location was identified for all activities with increased knee flexion associated with posterior translation of the center-of-rotation. The association between knee angle and anterior-posterior center-of-rotation location was not as strong as the relation between medial-lateral and anterior-posterior location, excluding gait. The Pearson's correlation for gait was stronger between knee angle and anterior-posterior center-of-rotation location (P < 0.001) than medial-lateral and anterior-posterior location (P = 0.0122). Individual variability accounted for a measurable proportion in variance explained of center-of-rotation location. Unique to gait, the lateral translation of center-of-rotation location resulted in the anterior translation of center-of-rotation at <10° knee flexion. Furthermore, no association between vertical ground-reaction force and center-of-rotation was identified.

Modeling of active skeletal muscles: a 3D continuum approach incorporating multiple muscle interactions.

Skeletal muscles have a highly organized hierarchical structure, whose main function is to generate forces for movement and stability. To understand the complex heterogeneous behaviors of muscles, computational modeling has advanced as a non-invasive approach to evaluate relevant mechanical quantities. Aiming to improve musculoskeletal predictions, this paper presents a framework for modeling 3D deformable muscles that includes continuum constitutive representation, parametric determination, model validation, fiber distribution estimation, and integration of multiple muscles into a system level for joint motion simulation. The passive and active muscle properties were modeled based on the strain energy approach with Hill-type hyperelastic constitutive laws. A parametric study was conducted to validate the model using experimental datasets of passive and active rabbit leg muscles. The active muscle model with calibrated material parameters was then implemented to simulate knee bending during a squat with multiple quadriceps muscles. A computational fluid dynamics (CFD) fiber simulation approach was utilized to estimate the fiber arrangements for each muscle, and a cohesive contact approach was applied to simulate the interactions among muscles. The single muscle simulation results showed that both passive and active muscle elongation responses matched the range of the testing data. The dynamic simulation of knee flexion and extension showed the predictive capability of the model for estimating the active quadriceps responses, which indicates that the presented modeling pipeline is effective and stable for simulating multiple muscle configurations. This work provided an effective framework of a 3D continuum muscle model for complex muscle behavior simulation, which will facilitate additional computational and experimental studies of skeletal muscle mechanics. This study will offer valuable insight into the future development of multiscale neuromuscular models and applications of these models to a wide variety of relevant areas such as biomechanics and clinical research.

Optimized prediction of contact force application during side-lying lumbar manipulation.

OBJECTIVES: The purposes of this study included the following: (1) to predict L3 contact force during side-lying lumbar manipulation by combining direct and indirect measurements into a single mathematical framework and (2) to assess the accuracy and confidence of predicting L3 contact force using common least squares (CLS) and weighted least squares (WLS) methods. METHODS: Five participants with no history of lumbar pain underwent 10 high-velocity, low-amplitude lumbar spinal manipulations at L3 in a side-lying position. Data from 5 low-force criterion standard trials where the L3 contact force was directly measured were used to generate participant-specific force prediction algorithms. These algorithms were used to predict L3 contact force in 5 experimental trials performed at therapeutic levels. The accuracy and effectiveness of CLS and WLS methods were compared. RESULTS: Differences between the CLS-predicted forces and the criterion standard-measured forces were 621.0 ± 193.5 N. Differences between the WLS-predicted forces and the criterion standard-measured forces were -3.6 ± 9.1 N. The 95% limits of agreement ranged from 234.0 to 1008.0 N for the CLS and -21.9 to 14.7 N for the WLS. During both the criterion standard and experimental trials, the CLS overestimated contact forces with larger variance than the WLS. CONCLUSION: This novel method to predict spinal contact force combines direct and indirect measurements into a single framework and preserves clinically relevant practitioner-participant contacts. As advanced instrumentation becomes available, this framework will enable advancements in training and high-quality research on mechanisms of spinal manipulative therapy.

Effect of intraoperative treatment options on hip joint stability following total hip arthroplasty.

Dislocation remains the leading indication for revision of total hip arthroplasty (THA). The objective of this study was to use a computational model to compare the overall resistance to both anterior and posterior dislocation for the available THA constructs commonly considered by surgeons attempting to produce a stable joint. Patient-specific musculoskeletal models of THA patients performing activities consistent with anterior and posterior dislocation were developed to calculate joint contact forces and joint positions used for simulations of dislocation in a finite element model of the implanted hip that included an experimentally calibrated hip capsule representation. Dislocations were then performed with consideration of offset using +5 and +9 offset, iteratively with three lipped liner variations in jump distance (10°, 15°, and 20° lips), a size 40 head, and a dual-mobility construct. Dislocation resistance was quantified as the moment required to dislocate the hip and the integral of the moment-flexion angle (dislocation energy). Increasing head diameter increased resistive moment on average for anterior and posterior dislocation by 22% relative to a neutral configuration. A lipped liner resulted in increases in the resistive moment to posterior dislocation of 9%, 19%, and 47% for 10°, 15°, and 20° lips, a sensitivity of approximately 2.8 Nm/mm of additional jump distance. A dual-mobility acetabular design resulted in an average 38% increase in resistive moment and 92% increase in dislocation energy for anterior and posterior dislocation. A quantitative understanding of tradeoffs in the dislocation risk inherent to THA construct options is valuable in supporting surgical decision making.

Impact of bone health on the mechanics of plate fixation for Vancouver B1 periprosthetic femoral fractures.

BACKGROUND: Condyle-spanning plate-screw constructs have shown potential to lower the risks of femoral refractures after the healing of a primary Vancouver type B1 periprosthetic femoral fracture. Limited information exists to show how osteoporosis (a risk factor for periprosthetic femoral fractures) may affect the plate fixation during activities of daily living. METHODS: Using total hip arthroplasty and plate-implanted finite element models of three osteoporotic femurs, this study simulated physiological loads of three activities of daily living, as well as osteoporosis associated muscle weakening, and compared the calculated stress/strain, load transfer and local stiffness with experimentally validated models of three healthy femurs. Two plating systems and two construct lengths (a diaphyseal construct and a condyle-spanning construct) were modeled. FINDINGS: Osteoporotic femurs showed higher bone strain (21.9%) and higher peak plate stress (144.3%) as compared with healthy femurs. Compared with shorter diaphyseal constructs, condyle-spanning constructs of two plating systems reduced bone strains in both healthy and osteoporotic femurs (both applying 'the normal' and 'the weakened muscle forces') around the most distal diaphyseal screw and in the distal metaphysis, both locations where secondary fractures are typically reported. The lowered resultant compressive force and the increased local compressive stiffness in the distal diaphysis and metaphysis may be associated with strain reductions via condyle-spanning constructs. INTERPRETATION: Strain reductions in condyle-spanning constructs agreed with the clinically reported lowered risks of femoral refractures in the distal diaphysis and metaphysis. Multiple condylar screws may mitigate the concentrated strains in the lateral condyle, especially in osteoporotic femurs.

Impact of periprosthetic femoral fracture fixation plating constructs on local stiffness, load transfer, and bone strains.

Secondary femoral fractures after the successful plate-screw fixation of a primary Vancouver type B1 periprosthetic femoral fracture (PFF) have been associated with the altered state of stress/strain in the femur as the result of plating. The laterally implanted condyle-spanning plate-screw constructs have shown promises clinically in avoiding secondary bone and implant failures as compared with shorter diaphyseal plates. Though the condyle-spanning plating has been hypothesized to avoid stress concentration in the femoral diaphysis through increasing the working length of the plate, biomechanical evidence is lacking on how plate length may impact the stress/strain state of the implanted femur. Through developing and experimentally validating finite element (FE) models of 3 cadaveric femurs, this study investigated the impact of plating on bone strains, load transfer and local stiffness, which were compared between FE models of 2 different plating systems that each had a diaphyseal configuration and a condyle-spanning configuration. Under simulated gait-loading, the condyle-spanning constructs of both plating systems were shown to lower the bone strains around the distal fixation screws (up to 24.8% reduction in maximum principal strain and 26.6% reduction in minimum principal strain) and in the distal metaphyseal shaft of the femur (up to 15.9% and 25.7% reductions in maximum and minimum principal strains, respectively), where secondary bone fractures have been typically reported. In the distal diaphyseal and metaphyseal shaft of femur, FE models of the condyle-spanning constructs were shown to increase the local compressive stiffness (up to 152.9% increases under simulated gait-loading) and decrease the transfer of compressive load (37.1% decreases under simulated gait-loading), which may be indicative of the lowered risks of bone damage.

Machine learning for rapid estimation of lower extremity muscle and joint loading during activities of daily living.

Joint contact and muscle forces estimated with musculoskeletal modeling techniques offer useful metrics describing movement quality that benefit multiple research and clinical applications. The expensive processing of laboratory data associated with generating these outputs presents challenges to researchers and clinicians, including significant time and expertise requirements that limit the number of subjects typically evaluated. The objective of the current study was to develop and compare machine learning techniques for rapid, data-driven estimation of musculoskeletal metrics from derived gait lab data. OpenSim estimates of patient joint and muscle forces during activities of daily living were simulated using laboratory data from 70 total knee replacement patients and used to develop 4 different machine learning algorithms. Trained machine learning models predicted both trend and magnitude of estimated joint contact (mean correlation coefficients ranging from 0.93 to 0.94 during gait) and muscle forces (mean correlation coefficients ranging from 0.83 to 0.91 during gait) based on anthropometrics, ground reaction forces, and joint angle data. Patient mechanics were accurately predicted by recurrent neural networks, even after removing dependence on key subsets of predictor features. The ability to quickly estimate patient mechanics from derived measurements of movement has the potential to broaden the impact of musculoskeletal modeling by enabling faster assessment in both clinical and research settings.

Automatic tracking of healthy joint kinematics from stereo-radiography sequences.

Kinematic tracking of healthy joints in radiography sequences is frequently performed by maximizing similarities between computed perspective projections of 3D computer models and corresponding objects' appearances in radiographic images. Significant human effort associated with manual tracking presents a major bottleneck in biomechanics research methods and limits the scale of target applications. The current work introduces a method for fully-automatic tracking of tibiofemoral and patellofemoral kinematics in stereo-radiography sequences for subjects performing dynamic activities. The proposed method involves the application of convolutional neural networks for annotating radiographs and a multi-stage optimization pipeline for estimating bone pose based on information provided by neural net predictions. Predicted kinematics are evaluated by comparing against manually-tracked trends across 20 distinct trials. Median absolute differences below 1.5 millimeters or degrees for 6 tibiofemoral and 3 patellofemoral degrees of freedom demonstrate the utility of our approach, which improves upon previous semi-automatic methods by enabling end-to-end automation. Implementation of a fully-automatic pipeline for kinematic tracking will benefit evaluation of human movement by enabling large-scale studies of healthy knee kinematics.

Development of axial compression and combined axial compression and torque loading configurations to reproduce strain in the implanted femur during activities of daily living.

Femoral strain is indicative of the potential for bone remodeling (strain energy density, SED) and periprosthetic femoral fracture (magnitude of principal strains) after total hip arthroplasty (THA). Previous modeling studies have evaluated femoral strains in THA-implanted femurs under gait loads including both physiological hip contact force and femoral muscle forces. However, experimental replication of the complex muscle forces during activities of daily living (ADLs) is difficult for in vitro assessment of femoral implant or fixation hardware. Alternatively, cadaveric tests using simplified loading configurations have been developed to assess post-THA bone mechanics, although no current studies have demonstrated simplified loading configurations used in mechanical tests may simulate the physiological femoral strains under ADL loads. Using an optimization approach integrated with finite element analysis, this study developed axial compression and combined axial compression and torque testing configurations for three common ADLs (gait, stair-descent and sit-to-stand) via matching the SED profile of the femur in THA-implanted models of three specimens. The optimized simplified-loading models showed good agreement in predicting bone remodeling stimuli (post-THA change in SED per unit mass) and fatigue regions as compared with the ADL-loading models, as well as other modeling and clinical studies. The optimized simplified test configurations can provide a physiological-loading based pre-clinical platform for the evaluation of implant/fixation devices of the femur.

Impact of alignment and kinematic variation on resistive moment and dislocation propensity for THA with lipped and neutral liners.

Instability and dislocation remain leading indications for revision of total hip arthroplasty (THA). Many studies have addressed the links between implant design and dislocation; however, an understanding of the impact of alignment and kinematic variability on constraint of modern THA constructs to provide joint stability is needed. The objective of this study is to provide objective data to be considered in the treatment algorithm to protect against joint instability. Joint contact and muscle forces were evaluated using musculoskeletal models of THA patients performing activities consistent with posterior and anterior dislocation. Position and joint loads were transferred to a finite element simulation with an experimentally calibrated hip capsule representation, where they were kinematically extrapolated until impingement and eventual dislocation. Cup anteversion and inclination were varied according to clinical measurements, and variation in imposed kinematics was included. The resistive moment provided by the contact force and joint capsule, and overall dislocation rate (dislocations/total simulations) were determined with neutral and lipped acetabular liners. Use of a lipped liner did increase the resistive moment in posterior dislocation, by an average of 5.2 Nm, and the flexion angle at dislocation by 1.4° compared to a neutral liner. There was a reduction in similar magnitude in resistance to anterior dislocation. Increased cup anteversion and inclination, hip abduction and internal rotation all reduced the occurrence of posterior dislocation but increased anterior dislocation. A quantitative understanding of tradeoffs in the dislocation risk inherent to THA construct options is valuable in supporting surgical decision making.

Development and calibration of a probabilistic finite element hip capsule representation.

The objective of this study was to develop a probabilistic representation of the hip capsule, which is calibrated to experimental capsular torque-rotation behavior and captures the observed variability for use in population-based studies. A finite element model of the hip capsule was developed with structures composed of a fiber-reinforced membrane, represented by 2D quadrilateral elements embedded with tension-only non-linear spring. An average capsule representation was developed by calibrating ligament properties (linear stiffness, reference strain) so that torque-rotation behavior matched mean cadaveric data. A probabilistic capsule was produced by determining the ligament property variability which represented ±2 SD measured in the experiment. Differences between experimental and model kinematics across all positions had RMS error of 4.7°. Output bounds from the optimized probabilistic capsule representation were consistent with ±2 SD of experimental data; the overall RMS error was 5.1°. This model can be employed in population-based finite element studies of THA to assess mechanics in realistic scenarios considering implant design, as well as surgical and patient factors.