Evaluating knee replacement mechanics during ADL with PID-controlled dynamic finite element analysis.

Validated computational knee simulations are valuable tools for design phase development of knee replacement devices. Recently, a dynamic finite element (FE) model of the Kansas knee simulator was kinematically validated during gait and deep flexion cycles. In order to operate the computational simulator in the same manner as the experiment, a proportional-integral-derivative (PID) controller was interfaced with the FE model to control the quadriceps actuator excursion and produce a target flexion profile regardless of implant geometry or alignment conditions. The controller was also expanded to operate multiple actuators simultaneously in order to produce in vivo loading conditions at the joint during dynamic activities. Subsequently, the fidelity of the computational model was improved through additional muscle representation and inclusion of relative hip-ankle anterior-posterior (A-P) motion. The PID-controlled model was able to successfully recreate in vivo loading conditions (flexion angle, compressive joint load, medial-lateral load distribution or varus-valgus torque, internal-external torque, A-P force) for deep knee bend, chair rise, stance-phase gait and step-down activities.

Identifying alignment parameters affecting implanted patellofemoral mechanics.

Complications of the patellofemoral (PF) joint remain a common cause for revision of total knee replacements. PF complications, such as patellar maltracking, subluxation, and implant failure, have been linked to femoral and patellar component alignment. In this study, a dynamic finite element model of an implanted PF joint was applied in conjunction with a probabilistic simulation to establish relationships between alignment parameters and PF kinematics, contact mechanics, and internal stresses. Both traditional sensitivity analysis and a coupled probabilistic and principal component analysis approach were applied to characterize relationships between implant alignment and resulting joint mechanics. Critical alignment parameters, and combinations of parameters, affecting PF mechanics were identified for three patellar designs (dome, modified dome, and anatomic). Femoral internal-external (I-E) alignment was identified as a critical alignment factor for all component designs, influencing medial-lateral contact force and anterior-posterior translation. The anatomic design was sensitive to patellar flexion-extension (F-E) alignment, while the dome, as expected, was less influenced by rotational alignment, and more by translational position. The modified dome was sensitive to a combination of superior-inferior, F-E, and I-E alignments. Understanding the relationships and design-specific dependencies between alignment parameters can aid preoperative planning, and help focus instrumentation design on those alignment parameters of primary concern.

Control-matched computational evaluation of tendo-femoral contact in patients with posterior-stabilized total knee arthroplasty.

Painful patellar crepitus is a potential complication in up to 14% of patients following posterior-stabilized (PS) total knee arthroplasty (TKA). A recent clinical study identified influential patient and surgical variables by comparing a group of crepitus patients with controls matched for age, sex, and body mass index. The purpose of our study was to evaluate effects of variables identified as significant in the clinical study, including patellar ligament length, femoral component flexion, patellar button size, and position of the joint line, on contact between the quadriceps tendon and the PS femoral component. A previously verified finite element model was utilized to estimate tendo-femoral contact during deep flexion activity. Using discrete perturbations, the computational model confirmed the clinical findings in that an increased patellar ligament length, flexed femoral component, lowered joint line, and larger patellar component all reduced potentially deleterious contact near the intercondylar notch. With the selected level of anatomic and component alignment perturbations, the most influential factor affecting tendo-femoral contact was patellar ligament length. Three crepitus patients with matched controls were subsequently modeled, and contact with the anterior border of the notch was present in each crepitus patient, but none of the controls. Alternative surgical alignments for these patients were evaluated to improve the potential long-term outcomes. By characterizing conditions that may lead to painful crepitus, the modeling approach supports clinicians by identifying pre-surgical indicators and important alignment parameters to control intraoperatively.

Dynamic finite element knee simulation for evaluation of knee replacement mechanics.

In vitro pre-clinical testing of total knee replacement (TKR) devices is a necessary step in the evaluation of new implant designs. Whole joint knee simulators, like the Kansas knee simulator (KKS), provide a controlled and repeatable loading environment for comparative evaluation of component designs or surgical alignment under dynamic conditions. Experimental testing, however, is time and cost prohibitive for design-phase evaluation of tens or hundreds of design variations. Experimentally-verified computational models provide an efficient platform for analysis of multiple components, sizes, and alignment conditions. The purpose of the current study was to develop and verify a computational model of a dynamic, whole joint knee simulator. Experimental internal-external and valgus-varus laxity tests, followed by dynamic deep knee bend and gait simulations in the KKS were performed on three cadaveric specimens. Specimen-specific finite element (FE) models of posterior-stabilized TKR were created from magnetic resonance images and CAD geometry. The laxity data was used to optimize mechanical properties of tibiofemoral soft-tissue structures on a specimen-specific basis. Each specimen was subsequently analyzed in a computational model of the experimental KKS, simulating both dynamic activities. The computational model represented all joints and actuators in the experimental setup, including a proportional-integral-derivative (PID) controller to drive quadriceps actuation. The computational model was verified against six degree-of-freedom patellofemoral (PF) and tibiofemoral (TF) kinematics and actuator loading during both deep knee bend and gait activities, with good agreement in trends and magnitudes between model predictions and experimental kinematics; differences were less than 1.8 mm and 2.2° for PF and TF translations and rotations. The whole joint FE simulator described in this study can be applied to investigate a wide range of clinical and research questions.

Development of a statistical shape model of the patellofemoral joint for investigating relationships between shape and function.

Patellofemoral (PF)-related pathologies, including joint laxity, patellar maltracking, cartilage degradation and anterior knee pain, affect nearly 25% of the population. Researchers have investigated the influence of articular geometry on kinematics and contact mechanics in order to gain insight into the etiology of these conditions. The purpose of the current study was to create a three-dimensional statistical shape model of the PF joint and to characterize relationships between PF shape and function (kinematics and contact mechanics). A statistical shape model of the patellar and femoral articular surfaces and their relative alignment was developed from magnetic resonance images. Using 15 shape parameters, the model characterized 97% of the variation in the training set. The first three shape modes primarily described variation in size, patella alta-baja and depth of the sulcus groove. A previously verified finite element model was used to predict kinematics and contact mechanics for each subject. Combining the shape and joint mechanics data, a statistical shape-function model was developed that established quantitative relations of how changes in the shape of the PF joint influence mechanics. The predictive capability of the shape-function model was evaluated by comparing statistical model and finite element predictions, resulting in kinematic root mean square errors of less than 3° and 2.5 mm. The key results of the study are dually in the implementation of a novel approach linking statistical shape and finite element models and the relationships elucidated between PF articular geometry and mechanics.

Combined probabilistic and principal component analysis approach for multivariate sensitivity evaluation and application to implanted patellofemoral mechanics.

Many aspects of biomechanics are variable in nature, including patient geometry, joint mechanics, implant alignment and clinical outcomes. Probabilistic methods have been applied in computational models to predict distributions of performance given uncertain or variable parameters. Sensitivity analysis is commonly used in conjunction with probabilistic methods to identify the parameters that most significantly affect the performance outcome; however, it does not consider coupled relationships for multiple output measures. Principal component analysis (PCA) has been applied to characterize common modes of variation in shape and kinematics. In this study, a novel, combined probabilistic and PCA approach was developed to characterize relationships between multiple input parameters and output measures. To demonstrate the benefits of the approach, it was applied to implanted patellofemoral (PF) mechanics to characterize relationships between femoral and patellar component alignment and loading and the resulting joint mechanics. Prior studies assessing PF sensitivity have performed individual perturbation of alignment parameters. However, the probabilistic and PCA approach enabled a more holistic evaluation of sensitivity, including identification of combinations of alignment parameters that most significantly contributed to kinematic and contact mechanics outcomes throughout the flexion cycle, and the predictive capability to estimate joint mechanics based on alignment conditions without requiring additional analysis. The approach showed comparable results for Monte Carlo sampling with 500 trials and the more efficient Latin Hypercube sampling with 50 trials. The probabilistic and PCA approach has broad applicability to biomechanical analysis and can provide insight into the interdependencies between implant design, alignment and the resulting mechanics.

Comparison of patellar bone strain in the natural and implanted knee during simulated deep flexion.

Instances of anterior knee pain and patellar fracture are significant complications following total knee replacement (TKR). Bone strain measured in the patella can provide an indication of patellar fracture risk and may also be related to anterior knee pain. The objective of this study was to develop subject-specific finite element models of the patellofemoral (PF) joint including density-mapped material properties to gain insight into the patellar bone strain distribution in the natural and implanted knee. In eight subjects, the volume of bone experiencing strains >0.5% in the implanted condition was ∼200% larger, on average, than the natural condition. An inverse relationship with a correlation of -0.74 was established between postoperative bone volume and strain in the implanted specimens, suggesting that patellar geometry may be a useful indicator of postoperative strain. Comparing strains between regions (superior, inferior, medial, and lateral), it was found that although highly strained bone was evenly distributed between medial and lateral regions in the natural case, the implanted specimens demonstrated significantly larger volumes of highly strained bone medially as a result of substantially lower modulus bone in the medial compartment. Understanding distributions of PF strain may aid in preoperative identification of those patients at risk for patellar fracture or anterior knee pain, guidance regarding altered component placement for at-risk patients, and design of components considering the implications of PF load transfer and patellar strain distribution.

Computationally efficient finite element evaluation of natural patellofemoral mechanics.

Finite element methods have been applied to evaluate in vivo joint behavior, new devices, and surgical techniques but have typically been applied to a small or single subject cohort. Anatomic variability necessitates the use of many subject-specific models or probabilistic methods in order to adequately evaluate a device or procedure for a population. However, a fully deformable finite element model can be computationally expensive, prohibiting large multisubject or probabilistic analyses. The aim of this study was to develop a group of subject-specific models of the patellofemoral joint and evaluate trade-offs in analysis time and accuracy with fully deformable and rigid body articular cartilage representations. Finite element models of eight subjects were used to tune a pressure-overclosure relationship during a simulated deep flexion cycle. Patellofemoral kinematics and contact mechanics were evaluated and compared between a fully deformable and a rigid body analysis. Additional eight subjects were used to determine the validity of the rigid body pressure-overclosure relationship as a subject-independent parameter. There was good agreement in predicted kinematics and contact mechanics between deformable and rigid analyses for both the tuned and test groups. Root mean square differences in kinematics were less than 0.5 deg and 0.2 mm for both groups throughout flexion. Differences in contact area and peak and average contact pressures averaged 5.4%, 9.6%, and 3.8%, respectively, for the tuned group and 6.9%, 13.1%, and 6.4%, respectively, for the test group, with no significant differences between the two groups. There was a 95% reduction in computational time with the rigid body analysis as compared with the deformable analysis. The tuned pressure-overclosure relationship derived from the patellofemoral analysis was also applied to tibiofemoral (TF) articular cartilage in a group of eight subjects. Differences in contact area and peak and average contact pressures averaged 8.3%, 11.2%, and 5.7% between rigid and deformable analyses in the tibiofemoral joint. As statistical, probabilistic, and optimization techniques can require hundreds to thousands of analyses, a viable platform is crucial to component evaluation or clinical applications. The computationally efficient rigid body platform described in this study may be integrated with statistical and probabilistic methods and has potential clinical application in understanding in vivo joint mechanics on a subject-specific or population basis.

Development of subject-specific and statistical shape models of the knee using an efficient segmentation and mesh-morphing approach.

Subject-specific finite element models developed from imaging data provide functional representation of anatomical structures and have been used to evaluate healthy and pathologic knee mechanics. The creation of subject-specific models is a time-consuming process when considering manual segmentation and hexahedral (hex) meshing of the articular surfaces to ensure accurate contact assessment. Previous studies have emphasized automated mesh mapping to bone geometry from computed tomography (CT) scans, but have not considered cartilage and soft tissue structures. Statistical shape modeling has been proposed as an alternative approach to develop a population of subject models, but still requires manual segmentation and registration of a training set. Accordingly, the aim of the current study was to develop an efficient, integrated mesh-morphing-based segmentation approach to create hex meshes of subject-specific geometries from scan data, to apply the approach to natural femoral, tibial, and patellar cartilage from magnetic resonance (MR) images, and to demonstrate the creation of a statistical shape model of the knee characterizing the modes of variation using principal component analysis. The platform was demonstrated on MR scans from 10 knees and enabled hex mesh generation of the knee articular structures in approximately 1.5h per subject. In a subset of geometries, average root mean square geometric differences were 0.54 mm for all structures and in quasi-static analyses over a range of flexion angles, differences in predicted peak contact pressures were less than 5.3% between the semi-automated and manually generated models. The integrated segmentation, mesh-morphing approach was employed in the efficient development of subject-specific models and a statistical shape model, where populations of subject-specific models have application to implant design evaluation or surgical planning.

Verification of predicted specimen-specific natural and implanted patellofemoral kinematics during simulated deep knee bend.

Verified computational models represent an efficient method for studying the relationship between articular geometry, soft-tissue constraint, and patellofemoral (PF) mechanics. The current study was performed to evaluate an explicit finite element (FE) modeling approach for predicting PF kinematics in the natural and implanted knee. Experimental three-dimensional kinematic data were collected on four healthy cadaver specimens in their natural state and after total knee replacement in the Kansas knee simulator during a simulated deep knee bend activity. Specimen-specific FE models were created from medical images and CAD implant geometry, and included soft-tissue structures representing medial-lateral PF ligaments and the quadriceps tendon. Measured quadriceps loads and prescribed tibiofemoral kinematics were used to predict dynamic kinematics of an isolated PF joint between 10 degrees and 110 degrees femoral flexion. Model sensitivity analyses were performed to determine the effect of rigid or deformable patellar representations and perturbed PF ligament mechanical properties (pre-tension and stiffness) on model predictions and computational efficiency. Predicted PF kinematics from the deformable analyses showed average root mean square (RMS) differences for the natural and implanted states of less than 3.1 degrees and 1.7 mm for all rotations and translations. Kinematic predictions with rigid bodies increased average RMS values slightly to 3.7 degrees and 1.9 mm with a five-fold decrease in computational time. Two-fold increases and decreases in PF ligament initial strain and linear stiffness were found to most adversely affect kinematic predictions for flexion, internal-external tilt and inferior-superior translation in both natural and implanted states. The verified models could be used to further investigate the effects of component alignment or soft-tissue variability on natural and implant PF mechanics.

Efficient probabilistic representation of tibiofemoral soft tissue constraint.

Verified and efficient representations of knee ligamentous constraints are essential to forward-dynamic models for prediction of knee mechanics. The objectives of this study were to develop an efficient probabilistic representation of knee ligamentous constraint using the advanced mean value (AMV) probabilistic approach, and to compare the AMV representation with the gold standard Monte Carlo (MC) approach. Specifically, the effects of inherent uncertainty in ligament stiffness, reference strain and attachment site locations on joint constraint were assessed. An explicit finite element model of the knee was evaluated under a series of anterior-posterior (AP) and internal-external (IE) loading at full extension and 90 degrees flexion. Distributions of AP and IE laxity were predicted using experimentally-based levels of ligament parameter variability. Importance factors identified the critical properties affecting the predicted bounds, and agreed with reported ligament recruitment. The AMV method agreed closely with MC results with a four-fold reduction in computation time.

Effects of rotator cuff tears on muscle moment arms: a computational study.

Rotator cuff tears cause morphologic changes to cuff tendons and muscles, which can alter muscle architecture and moment arm. The effects of these alterations on shoulder mechanical performance in terms of muscle force and joint strength are not well understood. The purpose of this study was to develop a three-dimensional explicit finite element model for investigating morphological changes to rotator cuff tendons following cuff tear. The subsequent objectives were to validate the model by comparing model-predicted moment arms to empirical data, and to use the model to investigate the hypothesis that rotator cuff muscle moment arms are reduced when tendons are divided along the force-bearing direction of the tendon. The model was constructed by extracting tendon, cartilage, and bone geometry from the male Visible Human data set. Infraspinatus and teres minor muscle and tendon paths were identified relative to the humerus and scapula. Kinetic and kinematic boundary conditions in the model replicated experimental protocols, which rotated the humerus from 45 degrees internal to 45 degrees external rotation with constant loads on the tendons. External rotation moment arms were calculated for two conditions of the cuff tendons: intact normal and divided tendon. Predicted moment arms were within the 1-99% confidence intervals of experimental data for nearly all joint angles and tendon sub-regions. In agreement with the experimental findings, when compared to the intact condition, predicted moment arms were reduced for the divided tendon condition. The results of this study provide evidence that one potential mechanism for the reduction in strength observed with cuff tear is reduction of muscle moment arms. The model provides a platform for future studies addressing mechanisms responsible for reduced muscle force and joint strength including changes to muscle length-tension operating range due to altered muscle and tendon excursions, and the effects of cuff tear size and location on moment arms and muscle forces.

Incorporating uncertainty in mechanical properties for finite element-based evaluation of bone mechanics.

Finite element (FE) models of bone, developed from computed tomography (CT) scan data, are used to evaluate stresses and strains, load transfer and fixation of implants, and potential for fracture. The experimentally derived relationships used to transform CT scan data in Hounsfield unit to modulus and strength contain substantial scatter. The scatter in these relationships has potential to impact the results and conclusions of bone studies. The objectives of this study were to develop a computationally efficient probabilistic FE-based platform capable of incorporating uncertainty in bone property relationships, and to apply the model to a representative analysis; variability in stresses and fracture risk was predicted in five proximal femurs under stance loading conditions. Based on published variability in strength and modulus relationships derived in the proximal femur, the probabilistic analysis predicted the distributions of stress and risk. For the five femurs analyzed, the 1 and 99 percentile bounds varied by an average of 17.3 MPa for stress and by 0.28 for risk. In each femur, the predicted variability in risk was greater than 50% of the mean risk calculated, with obvious implications for clinical assessment. Results using the advanced mean value (AMV) method required only seven analysis trials (1h) and differed by less than 2% when compared to a 1000-trial Monte-Carlo simulation (400 h). The probabilistic modeling platform developed has broad applicability to bone studies and can be similarly implemented to investigate other loading conditions, structures, sources of uncertainty, or output measures of interest.

Filter frequency selection for manual wheelchair biomechanics.

Wheelchair locomotion is an important form of mobility for many individuals with spinal cord injury. However, manual wheelchair propulsion can lead to upper-limb pain and can be very inefficient. This has led investigators to apply biomechanics to the study of wheelchair use. The objectives of this study were (1) to determine the frequency content of the motion of both hands during two speeds of wheelchair propulsion, (2) to obtain the filter frequencies necessary to remove noise from wheelchair motion data, and (3) to provide signal-to-noise ratio data for wheelchair kinematics. The participants in this study were a random sample of manual wheelchair users with paraplegia caused by spinal cord injury. Subjects propelled their personal wheelchairs on a computer-controlled dynamometer at speeds of 0.9 m/s and 1.8 m/s. Motion data were collected at 60 Hz with the use of a commercial infrared marker-based system. The main outcome measures were arm motions and noise frequency spectra, filter cutoff frequencies, and signal-to-noise ratio. Our results indicate that there is no useful signal power above 6 Hz during manual wheelchair propulsion at the speeds that we analyzed. In many cases, there was no useful signal power above 4 Hz. This would indicate that the frequency content of manual wheelchair propulsion is similar to that of human gait. The mean signal-to-noise ratio varied from a high of 91 dB to a low of 21.8 dB. The signal-to-noise ratio was greatest in the x direction (along the line of progression) and lowest in the z direction (medial-lateral). Manual wheelchair propulsion kinematic data should be low-pass filtered at approximately 6 Hz for speeds at or below 1.8 m/s. The data presented in the archival literature appear to have been filtered at an appropriate frequency.