Despite the success of total knee arthroplasty (TKA) restoration of normal function is often not achieved. Soft-tissue balance is a major factor leading to poor outcomes including malalignment, instability, excessive wear, and subluxation. Mechanical ligament balancers only measure the joint space in full extension and at 90° flexion. This study uses a novel electronic ligament balancer to measure the ligament balance in normal knees and in knees after TKA to determine the impact on passive and active kinematics. Fresh-frozen cadaver legs (N = 6) were obtained. A standard cruciate-retaining TKA was performed using measured resection approach and computer navigation (Stryker Navigation, Kalamazoo, MI). Ligament balance was measured using a novel electronic balancer (Fig 1, XO1, XpandOrtho, Inc, La Jolla, CA, USA). The XO1 balancer generates controlled femorotibial distraction of up to 120N. The balancer only requires a tibial cut and can be used before or after femoral cuts, or after trial implants have been mounted. The balancer monitors the distraction gap and the medial and lateral gaps in real time, and graphically displays gap measurements over the entire range of knee flexion. Gap measurements can be monitored during soft-tissue releases without removing the balancer. Knee kinematics were measured during active knee extension (Oxford knee rig) and during passive knee extension under varus and valgus external moment of 10Nm in a passive test rig. Sequence of testing and measurement:
Ligament balance was recorded with the XO1 balancer after the tibial cut, after measured resection of the femur, and after soft-tissue release and/or bone resection to balance flexion-extension and mediolateral gaps. Passive and active kinematics were measured in the normal knee before TKA, after measured resection TKA, and after soft-tissue release and/or bone resection to balance flexion-extension and mediolateral gaps.Background
Methods
Wear and fatigue damage to polyethylene components remain major factors leading to complications after total knee and unicompartmental arthroplasty. A number of wear simulations have been reported using mechanical test equipment as well as computer models. Computational models of knee wear have generally not replicated experimental wear under diverse conditions. This is partly because of the complexity of quantifying the effect of cross-shear at the articular interface and partly because the results of pin-on-disk experiments cannot be extrapolated to total knee arthroplasty wear. Our premise is that diverse experimental knee wear simulation studies are needed to generate validated computational models. We combined five experimental wear simulation studies to develop and validate a finite-element model that accurately predicted polyethylene wear in high and low crosslinked polyethylene, mobile and fixed bearing, and unicompartmental (UKA) and tricompartmental knee arthroplasty (TKA). Low crosslinked polyethylene (PE). A finite element analysis (FEA) of two different experimental wear simulations involving TKA components of low crosslinked polyethylene inserts, with two different loading patterns and knee kinematics conducted in an AMTI knee wear simulator: a low intensity and a high intensity. Wear coefficients incorporating contact pressure, sliding distance, and cross-shear were generated by inverse FEA using the experimentally measured volume of wear loss as the target outcome measure. The FE models and wear coefficients were validated by predicting wear in a mobile bearing UKA design. Highly crosslinked polyethylene (XLPE). Two FEA models were constructed involving TKA and UKA XLPE inserts with different loading patterns and knee kinematics conducted in an AMTI knee wear simulator. Wear coefficients were generated by inverse FEA.Background
Methods
Despite the success of total knee arthroplasty (TKA) restoration of normal function is often not achieved. Soft tissue balance is a major factor for poor outcomes including malalignment, instability, excessive wear, and subluxation. Computer navigation and robotic-assisted systems have increased the accuracy of prosthetic component placement. On the other hand, soft tissue balancing remains an art, relying on a qualitative feel for the balance of the knee, and is developed over years of practice Several instruments are available to assist surgeons in estimating soft tissue balance. However, mechanical devices only measure the joint space in full extension and at 90° flexion. Further, because of lack of comprehensive characterization of the ligament balance of healthy knees, surgeons do not have quantitative guidelines relating the stability of an implanted to that of the normal knee. This study measures the ligament balance of normal knees and tests the accuracy of two mechanical distraction instruments and an electronic distraction instrument. Cadaver specimens were mounted on a custom knee rig and on the AMTI VIVO which replicated passive kinematics. A six-axis load cell and an infrared tracking system was used to document the kinematics and the forces acting on the knee. Dynamic knee laxity was measured under 10Nm of varus/valgus moment, 10Nm of axial rotational moment, and 200N of AP shear. Measurements were repeated after transecting the anterior cruciate ligament, after TKA, and after transecting the posterior cruciate ligament. The accuracy and reproducibility of two mechanical and one electronic distraction device was measured.Background
Methods
Kinematic studies are used to evaluate function and efficacy of various implant designs. Given the large variation between subjects, matched pairs are ideal when comparing competing designs. It is logical to deduce that both limbs in a subject will behave identically during a given motion [1], barring unilateral underlying pathology, thus allowing for the most direct comparison of two designs. It is our goal to determine if this is a valid assumption by assessing whether or not there are significant differences present in the kinematics of left and right knees from the same subject. Gait studies have compared pre-and postoperative implantation kinematics for various pathologies like ACL rupture [2] and osteoarthritis [3, 4]. We designed a study to assess squatting in cadaver specimens. Sixteen matched pairs of fresh-frozen cadavers, (Eleven males, five females; aged 71 years [± 10 yrs]) were tested. Each knee, intact, was tested by mounting it on a dynamic, quadriceps-driven, closed-kinetic-chain Oxford knee rig (OKR), which simulated a deep knee bend from full extension to 120° flexion. We chose femoral rollback, tibiofemoral external rotation, tibial adduction, patellofemoral tilt and shift as our outcomes, which were recorded using an active infrared tracking system.Introduction:
Methods:
Telemetric knee implants have provided invaluable insight into the forces occurring in the knee during various activities. However, due to the high amount of cost involved only a few of them have been developed. Mathematical modeling of the knee provides an alternative that can be easily applied to study high number of patients. However, in order to ensure accuracy these models need to be validated with in vivo force data. Previously, mathematical models have been developed and validated to study only specific activities. Therefore, the objective of this study was compare the knee force predictions from the same model with that obtained using telemetry for multiple activities. Kinematics of a telemetric patient was collected using fluoroscopy and 2D to 3D image registration for gait, deep knee bend (DKB), chair rise, step up and step down activities. Along with telemetric forces obtained from the implant, synchronized ground reaction forces (GRF) were also collected from a force plate. The relevant kinematics and the GRF were input into an inverse dynamic model of the human leg starting from the foot and ending at the pelvis (Figure 1). All major ligaments and muscles affecting the knee joint were included in the model. The pelvis and the foot were incorporated into the system so as to provide realistic boundary conditions at the hip and the ankle and also to provide reference geometry for the attachment sites of relevant muscles. The muscle redundancy problem was solved using the pseudo-inverse technique which has been shown to automatically optimize muscle forces based on the Crowninshield-Brand cost function. The same model, without any additional changes, was applied for all activities and the predicted knee force results were compared with the data obtained from telemetry. Comparison of the model predictions for the tibiofemoral contact forces with the telemetric implant data revealed a high degree of correlation both in the nature of variation of forces and the magnitudes of the forces obtained. Interestingly, the model predicted forces with a high level of accuracy for activities in which the flexion of the knee do not vary monotonically (increases and decreases or vice-versa) with the activity cycle (gait, step up and step down). During these activities, the difference between the model predictions with the telemetric data was less than 5% (Figure 2). For activities where flexion varies monotonically (either increases or decreases) with activity (DKB and chair rise) the difference between the forces was less than 10% (Figure 3). The results from this study show that inverse dynamic computational models of the knee can be robust enough to predict forces occurring at the knee with a high amount of accuracy for multiple activities. While this study was conducted only on one patient with a telemetric implant, the required inputs to the model are generic enough so that it is applicable for any TKA patient with the mobility to conduct the desired activity. This allows kinetic data to be provided for the improvement of implant design and surgical techniques accessibly and relatively inexpensively.
Despite over 95% long-term survivorship of TKA, 14–39% of patients express dissatisfaction due to anterior knee pain, mid-flexion instability, reduction in range of flexion, and incomplete return of function. Changing demographics with higher expectations are leading to renewed interest in patient-specific designs with the goal of restoring of normal kinematics. Improved imaging and image-processing technology coupled with rapid prototyping allow manufacturing of patient-specific cutting guides with individualized femoral and tibial components with articulating surfaces that maximize bony coverage and more closely approximate the natural anatomy. We hypothesized that restoring the articular surface and maintaining medial and lateral condylar offset of the implanted knee to that of the joint before implantation would restore normal knee kinematics. To test this hypothesis we recorded kinematics of patient-specific prostheses implanted using patient-specific cutting guides. Preoperative CT scans were obtained from nine matched pairs of human cadaveric knees. One of each pair was randomly assigned to one of two groups: one group implanted with a standard off-the-shelf posterior cruciate-retaining design using standard cutting guides based on intramedullary alignment; the contralateral knee implanted with patient-specific implants using patient-specific cutting guides, both manufactured from the preoperative CT scans. Each knee was tested preoperatively as an intact, normal knee, by mounting the knee on a dynamic, quadriceps-driven, closed-kinetic-chain Oxford knee rig (OKR), simulating a deep knee bend from 0° to 120° flexion. Following implantation with either the standard or patient-specific implant, knees were mounted on the OKR and retested. Femoral rollback, tibiofemoral rotation, tibial adduction, patellofemoral tilt and shift were recorded using an active infrared tracking system.Introduction:
Methods:
Wear and polyethylene damage have been implicated in up to 22% of revision surgeries after unicompartmental knee replacement. Two major design rationales to reduce this rate involve either geometry and/or material strategies. Geometric options involve highly congruent mobile bearings with large contact areas; or moderately conforming fixed bearings to prevent bearing dislocation and reduce back-side wear, while material changes involve use of highly crosslinked polyethylene. This study was designed to determine if a highly crosslinked fixed-bearing design would increase wear resistance. Gravimetric wear rates were measured for two unicompartmental implant designs: Oxford unicompartmental (Biomet) and Triathlon X3 PKR (Stryker) on a knee wear simulator (AMTI) using the ISO-recommended standard. The Oxford design had a highly conforming mobile bearing of compression molded Polyethylene (Arcom). The Triathlon PKR had a moderately conforming fixed bearing of sequentially crosslinked Polyethylene (X3). A finite element model of the AMTI wear simulation was constructed to replicate experimental conditions and to compute wear. This approach was validated using experimental results from previous studies. The wear coefficient obtained previously for radiation-sterilized low crosslinked polyethylene was used to predict wear in Oxford components. The wear coefficient obtained for highly crosslinked polyethylene was used to predict wear in Triathlon X3 PKR components. To study the effect design and polyethylene crosslinking, wear rates were computed for each design using both wear coefficients.INTRODUCTION
METHODS
Knee contact force during activities after total knee arthroplasty (TKA) is very important, since it directly affects component wear and implant loosening. While several computational models have predicted knee contact force, the reports vary widely based on the type of modeling approach and the assumptions made in the model. The knee is a complex joint, with three compartments of which stability is governed primarily by soft tissues. Multiple muscles control knee motion with antagonistic co-contraction and redundant actions, which adds to the difficulty of accurate dynamic modeling. For accurate clinically relevant predictions a subject-specific approach is necessary to account for inter-patient variability. Data were collected from 3 patients who received custom TKA tibial prostheses instrumented with force transducers and a telemetry system. Knee contact forces were measured during squatting, which was performed up to a knee flexion angle that was possible without discomfort (range, 80–120°). Skin marker-based video motion analysis was used to record knee kinematics. Preoperative CT scans were reconstructed to extract tibiofemoral bone geometry using MIMICS (Materialise, Belgium). Subject-specific musculoskeletal models of dynamic squatting were generated in a commercial software program (LifeMOD, LifeModeler, USA). Contact was modeled between tibiofemoral and patellofemoral articular surfaces and between the quadriceps and trochlear groove to simulate tendon wrapping. Knee ligaments were modeled with nonlinear springs: the attachments of these ligaments were adjusted to subject-specific anatomic landmarks and material properties were assigned from published reports.INTRODUCTION
METHODS
Aligning the tibial tray is a critical step in total knee arthroplasty (TKA). Malalignment, (especially in varus) has been associated with failure and revision surgery. While the link between varus malalignment and failure has been attributed to increased medial compartmental loading and generation of shear stress, quantitative biomechanical evidence to directly support this mechanism is incomplete. We therefore constructed and validated a finite element model of knee arthroplasty to test the hypothesis that varus malalignment of the tibial tray would increase the risk of tray subsidence.Introduction
Methods
While in vivo kinematics and forces in the knee have been studied extensively, these are typically measured during controlled activities conducted in an artificial laboratory environment and often do not reflect the natural day-to-day activities of typical patients. We have developed a novel algorithm that together with our electronic tibial component provide unsupervised simultaneous dynamic 3-D kinematics and forces in patients. An inverse finite element approach was used to compute knee kinematics from in vivo measured knee forces. In vitro pilot testing indicated that the accuracy of the algorithm was acceptable for all degrees of freedom except knee flexion angle. We therefore mounted an electrogoniometer on a knee sleeve to monitor knee flexion while simultaneously recording knee forces. A finite element model was constructed for each subject. The femur was flexed using the measured knee flexion angle and brought into contact with the fixed tibial insert using the three-component contact force vector applied as boundary conditions to the femoral component, which was free to translate in all directions. The relative femorotibial adduction-abduction and axial rotation were varied using an optimization program (iSIGHT, Simulia, Providence, RI) to minimize the difference between the resultant moments output by the model and the experimentally measured moments. Maximum absolute error was less than 1 mm in anteroposterior and mediolateral translation and was 1.2° for axial rotation and varus-valgus angulation. This accuracy is comparable to that reported for fluoroscopically measured kinematics. We miniaturized the external hardware and developed a wearable data acquisition system to monitor knee forces and kinematics outside the laboratory.Background
Methods
