INTRODUCTION

The medial-stabilised (MS) knee implant, characterised by a spherical medial condyle on the femoral component and a medially congruent tibial bearing, was developed to improve knee kinematics and stability relative to performance obtained in posterior-stabilised (PS) and cruciate-retaining (CR) designs. We aimed to compare in vivo six-degree-of-freedom (6-DOF) kinematics during overground walking for these three knee designs.

INTRODUCTION

Accurate knowledge of knee joint kinematics following total knee arthroplasty (TKA) is critical for evaluating the functional performance of specific implant designs. Biplane fluoroscopy is currently the most accurate method for measuring 3D knee joint kinematics in vivo during daily activities such as walking. However, the relatively small imaging field of these systems has limited measurement of knee kinematics to only a portion of the gait cycle. We developed a mobile biplane X-ray (MoBiX) fluoroscopy system that enables concurrent tracking and imaging of the knee joint for multiple cycles of overground gait. The primary aim of the present study was to measure 6-degree-of-freedom (6-DOF) knee joint kinematics for one complete cycle of overground walking. A secondary aim was to quantify the position of the knee joint centre of rotation (COR) in the transverse plane during TKA gait.

Objectives

Orthopaedic surgeons use stems in revision knee surgery to obtain stability when metaphyseal bone is missing. No consensus exists regarding stem size or method of fixation. This in vitro study investigated the influence of stem length and method of fixation on the pattern and level of relative motion at the bone–implant interface at a range of functional flexion angles.

Iterative finite element (FE) models are used to simulate bone remodelling that takes place due to the surgical insertion of an implant or to simulate fracture healing. In such simulations element material properties are calculated after each iteration of solving the model. New material properties are calculated based on the results derived by the model during the last iteration. Once the FE model has gone through a number of such iterations it is often necessary to assess the remodelling that has taken place. The method widely used to do this is to analyse element Young's modulus plots taken at particular sections through the model. Although this method gives relevant information which is often helpful when comparing different implants, the information is rather abstract and is difficult to compare with patient data which is commonly in the form of radiographs.

The authors suggest a simple technique that can be used to generate synthetic radiograph images from FE models. These images allow relatively easy comparisons of FE derived information with patient radiographs. Another clear advantage of this technique is that clinicians (who are familiar with reading radiographs) are able to understand and interpret them readily.

To demonstrate the technique a three dimensional (3D) model of the proximal tibia implanted with an Oxford Unicompartmental Knee replacement was created based on CT data obtained from a cadaveric tibia. The model's initial element material properties were calculated from the same CT data set using a relationship between radiographic density and Young's modulus.

The model was subject to simplified loading conditions and solved over 365 iterations representing one year of in vivo remodelling. After each iteration the element material properties were recalculated based on previously published remodelling rules. Next, synthetic anteroposterior radiographs were generated by back calculating radiographic densities from material properties of the model after 365 iterations. A 3D rectangular grid of sampling points which encapsulated the model was defined. For each of the elements in the FE model radiographic densities were back calculated based on the same relationships used to calculate material properties from radiographic densities. The radiographic density of each element was assigned to all the sampling grid points within the element. The 3D array of radiographic densities was summed in the anteroposterior direction thereby creating a 2D array of radiographic densities. This 2D array was plotted giving an image analogous to anteroposterior patient radiographs. Similar to a patient radiograph denser material appeared lighter while less dense material appeared darker.

The resulting synthetic radiographs were compared to patient radiographs and found to have similar patterns of dark and light regions.

The synthetic radiographs were relatively easy to produce based on the FE model results, represented FE results in a manner easily comparable to patient radiographs, and represented FE results in a clinician friendly manner.

Introduction: Radiolucent lines (RLL) underneath the tibial component are common findings following the Oxford Uni-compartmental Knee Arthroplasty (OUKA)[1]. Many theories have been proposed to explain the cause of RLL, such as poor cementing, osteonecrosis, micromotion, and thermal necrosis, however, the true aetiology and clinical significance remain unclear. We undertook a retrospective study analysing the association between RLL and pre-operative, intra-operative factors, as well as clinical outcome scores.

Method: One hundred and sixty-one knees which had undergone primary Phase 3 medial Oxford OUKA were included in the study. Fluoroscopic radiography films were assessed at five years post-operatively for areas of tibial RLL. The presence of RLL was compared to

patients’ pre-operative demographics for age, weight, height, BMI,

Results: Of the 161 knees in the study, 126 (78%) were found to have tibial RLL. No statistical difference was found between knees with RLL and those without in terms of preoperative demographics, intra-operative factors, or clinical assessment criteria.

Discussion: No clear relationship between RLL, preoperative demographics, and intra-operative factors has been identified in this study. We conclude that tibial RLL following OUKA is a common finding but do not seem to affect medium term clinical outcome.

In finite element (FE) analysis of long bones it is now common practice to calculate the material properties based on CT data. Although a unique material property is calculated for each element, assigning each element an individual material property results in excessively large models. To avoid this, it is usual to group the elements based on their material properties and to assign each group a single material property (Zannoni 1998). No study has analysed the effect the number of material properties used in a long bone FE model has on the accuracy of the results.

The aim of this study was to evaluate the variation in the calculated mechanical environment as a function of the number of material properties used in an FE model.

An FE mesh of a cadaveric human tibia containing 47,696 ten-node tetrahedron elements and 75,583 nodes was created using CT scans. Material properties were calculated for each element of the mesh based on previous work (Rho 1995, 1996). Eleven FE models were created by varying the number of groups (1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024) the elements were divided into. A single material property was assigned to each group. All models were subject to an axial point load of 300N applied on the medial condyle of the tibial plateau while the distal end was fixed. The variation in maximum and minimum principal strains and deflections, at 17 well distributed surface nodes and at 65 randomly distributed nodes within the bone were plotted against the number of element groups. The total strain energy was also plotted against the number of groups. The errors for strain, deflection, and total strain energy were calculated for each model assuming that the model using 1024 element groups was accurate.

The parameter to converge with the least number of element groups was the total strain energy. At 512 element groups the error was less than 0.001% (0.7% for the two material model). The next to converge were the displacements. Using 512 materials the maximum error in displacement at the surface nodes was 0.001% (4.7% for the 2 material model), while for the internal nodes the maximum error was 0.53% (36.7% for the 2 material model). The least convergence occurred for principal strains. The maximum errors when 512 materials were used were 1.06% (57.7% for the 2 material model) and 3.02% (104.5% for the 2 material model) for the surface and the internal nodes respectively.

This study demonstrates the relationship between the accuracy of calculated mechanical environment and the number of material properties assigned to the model. While this study will allow the analyst to make an informed decision on the number of material properties for modelling the human tibia it also helps examine the validity of previous studies which, usually due to limited resources, used fewer material properties.

Accurate placement of unicompartmental knee arthroplasty components is thought to be essential for the long-term survival and efficacy of the prosthesis. Computer navigation is being explored as a means of improving the accuracy of component position. There are few published studies comparing conventional and computer-navigated techniques using the same prosthesis.

Twenty-two Allegretto [Zimmer] medial unicompartmental knee prostheses were placed in 18 patients using the AxiEM [Medtronic] computer-navigated system. The immediate post-operative AP and lateral radiographs were analysed and compared with an equivalent cohort of 30 prostheses in 29 patients with medial unicompartmental arthritis in whom the Allegretto was placed without the aid of computer navigation. All operations were performed by the senior author in a rural Queensland hospital.

No cases were lost to follow-up. The data was not normally distributed. The mean, SD and variance of the data sets was calculated and significance tested with a 2-tailed Mann-Whitney U-test. Computer navigated tibial components were implanted with a mean of 2 degrees of varus compared with 1 degree of valgus with conventional navigation [p = 0.027]. Our target was 0–4 degrees of varus. Eighteen of the 20 computer-navigated cases, 90% fell within the recommended range [0–4 degrees of varus] compared with only 40%, 12 of the 30 conventionally-implanted cases. This is demonstrated by the greater range and variance of the conventional navigation data set. Posterior slope for the computer navigated components was 1 degree compared with 3 degrees for conventional navigation [0.010]; only 1 computed navigated component [5%] was implanted with anterior slope compared with 4 cases for conventional navigation [13%]. Measurements of femoral component flexion and position with respect to the tibial component were not significantly different but demonstrated greater variance for the conventionally navigated data set.

Accurate component positioning improves efficacy and prosthesis survival for patients who meet the indications for unicompartmental surgery. However proponents acknowledge the weaknesses of conventional jigs for unicompartmental prostheses. In this study computer navigation has been shown to improve the accuracy of component placement.

Statement of purpose: The aim of this study is to evaluate different designs of unicompartmental knee replacement (UKR) by comparing the peak von Mises and contact stresses in polyethylene (PE) bearings over a step-up activity.

Summary of Methods: A validated finite element (FE) model was used in this study. Three UKR designs were modelled: a spherical femoral component with a spherical PE bearing (fully-congruent), a poly-radial femoral component with a concave PE bearing (semi-congruent), and a spherical femoral component with a flat bearing (non-congruent).

Kinematic data from in-vivo fluoroscopy measurements during a step-up activity was used to determine the relative tibial-femoral position as a function of knee flexion angle for each model. Medial and lateral force distribution was adapted from loads measured in-vivo with an instrumented implant during a step-up activity. The affect that varying the bearing thickness has on the stresses in the bearing was investigated. In addition, varus-valgus mal-alignment was investigated by rotating the femoral component through 10 degrees.

Summary of Results: Only the fully congruent bearing experienced peak von Mises and contact stresses below the PE lower fatigue limit (17MPa) for the step-up activity (fully congruent PE peak contact stress, 5MPa). The highest PE contact stresses were observed for the semi-congruent and non-congruent designs, which experienced approximately 3 times the PE lower fatigue limit. Peak PE von Mises stresses for the semi-congruent and non-congruent designs were similar, peaking at approximately 25MPa. Peak PE von Mises stresses were ameliorated with increased bearing thickness. Varus-valgus mal-alignment had little effect on the peak stresses in the three UKR designs.

Statement of Conclusions: Fully congruent articulating surfaces significantly reduce the peak contact stresses and von Mises stresses in the bearing. The FE model demonstrates that fully congruent bearings as thin as 2.5mm can be used without increasing the contact stresses significantly. Fully congruent designs can use thinner bearings and enable greater bone preservation.

Statement of purpose: Finite element (FE) models of bone can be used to evaluate new and modified knee replacements. Validation of FE models is seldom used, and the quantification of modelling parameters has a considerable effect on the results obtained. The aim of this study is to develop a FE model of a cadaveric tibia and validate it against a comprehensive set of experiments.

Summary of Methods: Seventeen tri-axial rosettes were attached to a cleaned, fresh frozen cadaveric human tibia and the tibia was subjected to 13 loading conditions. Deflection and strain data were used for comparison with the FE model. A geometric model was created on the basis of computed tomography (CT) scans. The CT data was used to map 600 orthotropic material properties to the tibia. All experiments were simulated on the FE model. Measured principal strains were compared to their corresponding FE values using regression analysis. The validated tibia model was reduced in size (75mm to the proximal) and then re-modelled to represent only the proximal tibia. This re-modelled tibia was validated against the reduced size FE model. Virtual surgery was performed on the validated proximal model to implant a UKR.

Summary of Results: For the whole tibia model, the regression line for all axial loads combined had a slope of 0.999, an intercept of −6.24 micro-strain, and an R2 value of 0.962. The root mean square error as a percentage was 5%. For the proximal tibia model, correlation coefficients of 0.989 and 0.976 were obtained for the maximum and minimum principal strains respectively.

Statement of Conclusions: An FE model of an implanted proximal tibia has been validated against experimental data. This model is able to accurately predict the deflection and stresses in a replaced knee joint to obtain clinically relevant information. This will provide a virtual model of unicompartmental arthroplasty, where variables such as fixation method and bearing mechanics can be assessed.

Purpose: To identify associative factors for radiolucency (RL) under the tibial component following the Oxford unicompartmental arthroplasty (UKA), and to evaluate its effect on clinical outcome scores.

Method: One hundred and sixty-one knees which had undergone primary Phase 3 medial Oxford UKA were included. Fluoroscopic radiography films were assessed at five years post-operatively for areas of tibial RL. The two groups of patients, with and without RL, were compared to

patients’ pre-operative demographics for age, weight, height, BMI,

Results: 101 (62%) knees were found to have tibial RL. All RL were categorised as physiological or they were < 1mm thick, with sclerotic margins and non-progressive. No statistical difference was found between knees with RL and those without, in terms of pre-operative demographics, intra- or post-operative factors, and clinical outcome scores (p> 0.1 in all variables).

Discussion: Radiolucency (RL) under the tibial component is a common finding following the Oxford UKA. Many theories have been proposed to explain the cause of RL, such as poor cementing, osteonecrosis, micromotion, and thermal necrosis. However, the true aetiology and clinical significance remain unclear. We attempted to address this.

We found no significant relationship between physiological RL, pre-operative demographics, intra-operative variables and clinical outcome scores in this study. Tibial RL remains a common finding following the Oxford UKA yet we do not know why it occurs but in the medium term, clinical outcome is not influenced by RL. In particular, it is not a sign of loosening. Physiological RL can therefore be ignored even if associated with adverse symptoms following the Oxford UKA.

Narrow, well-defined radiolucent lines commonly observed at the bone-implant interface of unicompartmental knee replacement tibial components have been referred to as physiological radiolucencies. These should be distinguished from pathological radiolucencies, which are poorly defined, wide and progressive, and associated with loosening and infection. We studied the incidence and clinical significance of tibial radiolucent lines in 161 Oxford unicondylar knee replacements five years after surgery. All the radiographs were aligned with fluoroscopic control to obtain views parallel to the tibial tray to reveal the tibial bone-implant interface.

We found that 49 knees (30%) had complete, 52 (32%) had partial and 60 (37%) had no radiolucent lines. There was no relationship between the incidence of radiolucent lines and patient factors such as gender, body mass index and activity, or operative factors including the status of the anterior cruciate ligament and residual varus deformity. Nor was any statistical relationship established between the presence of radiolucent lines and clinical outcome, particularly pain, assessed by the Oxford Knee score and the American Knee Society score.

We conclude that radiolucent lines are common after Oxford unicompartmental knee replacement but that their aetiology remains unclear. Radiolucent lines were not a source of adverse symptoms or pain. Therefore, when attempting to identify a source of postoperative pain after Oxford unicompartmental knee replacement the presence of a physiological radiolucency should be ignored.

Finite element (FE) analysis is widely used to calculate stresses and strains within human bone in order to improve implant designs. Although validated FE models of the human femur have been created (Lengsfeld et al., 1998), no equivalent yet exists for the tibia. The aim of this study was to create such an FE model, both with and without the tibial component of a knee replacement, and to validate it against experimental Results: A set of reference axes was marked on a cleaned, fresh frozen cadaveric human tibia. Seventeen triaxial stacked strain rosettes were attached along the bone, which was then subjected to nine axial loading conditions, two four-point bending loading conditions, and a torsional loading condition using a materials testing machine (MTS 858). Deflections and strain readings were recorded. Axial loading was repeated after implantation of a knee replacement (medial tibial component, Biomet Oxford Unicompartmental Phase 3). The intact tibia was CT scanned (GE HiSpeed CT/i) and the images used to create a 3D FE mesh. The CT data was also used to map 600 transversely isotropic material properties (Rho, 1996) to individual elements. All experiments were simulated on the FE model. Measured principal strains and displacements were compared to their corresponding FE values using regression analysis.

Experimental results were repeatable (mean coefficients of variation for intact and implanted tibia, 5.3% and 3.9%). They correlated well with those of the FE analysis (R squared = 0.98, 0.97, 0.97, and 0.99 for axial (intact), axial (implanted), bending, torsional loading). For each of the load cases the intersects of the regression lines were small in comparison to the maximum measured strains (< 1.5%). While the model was more rigid than the bone under torsional loading (slope =0.92), the opposite was true for axial (slope = 1.14 (intact) 1.24 (implanted)) and bending (slope = 1.06) loads. This is probably due to a discrepancy in the material properties of the model.

Purpose: The purpose of this study was to investigate the relationship between self reported disability, physical performance testing (PPT) and everyday physical activity in people with Chronic Low Back Pain (CLBP).

Background: Disability is currently assessed using self-report and PPT. Little is known about the relationship between these two constructs and everyday physical activity. Increased knowledge of the relationship may enhance understanding of disability, and lead to the development of more robust methods of disability measurement.

Methods: A group of 30 (20f10m) people with non-specific CLBP completed the Roland Morris Disability questionnaire (RMDQ) [self-report], and performed two PPTs (5min walk test, 50ft walk test). Each participant then wore a physical activity monitor for a one week period and mean daily step count was calculated. Correlations were performed between self-report, performance testing and activity monitoring.

Results: Relatively weak but statistically significant relationships were found between the three measurement techniques. The strongest relationship existed between the RMDQ and step count (r= −0.494, p=0.006). Step count was also related to performance on the 50ft walk test (r=−.393, (p=0.032). While the relationship between the overall RMDQ score and physical performance did not reach significance, a significant relationship did exist between the 50ft walk test and the third question in the RMDQ (r=0.369, p=0.045), which specifically questions perceived walking behaviour.

Conclusion: Everyday physical activity is related to self-reported disability and physical performance capacity. As such, activity monitoring may be a useful objective adjunct to current techniques used to assess disability in people with CLBP.

Finite element (FE) analysis is widely used to calculate stresses and strains within human bone in order to improve implant designs. Although validated FE models of the human femur have been created (Lengsfeld et al., 1998), no equivalent yet exists for the tibia. The aim of this study was to create such an FE model, both with and without the tibial component of a knee replacement, and to validate it against experimental results.

A set of reference axes was marked on a cleaned, fresh frozen cadaveric human tibia. Seventeen triaxial stacked strain rosettes were attached along the bone, which was then subjected to nine axial loading conditions, two four-point bending loading conditions, and a torsional loading condition using a materials testing machine (MTS 858). Deflections and strain readings were recorded. Axial loading was repeated after implantation of a knee replacement (medial tibial component, Biomet Oxford Unicompartmental Phase 3). The intact tibia was CT scanned (GE HiSpeed CT/i) and the images used to create a 3D FE mesh. The CT data was also used to map 600 transversely isotropic material properties (Rho, 1996) to individual elements. All experiments were simulated on the FE model. Measured principal strains and displacements were compared to their corresponding FE values using regression analysis.

Experimental results were repeatable (mean coeffi-cients of variation for intact and implanted tibia, 5.3% and 3.9%). They correlated well with those of the FE analysis (R squared = 0.98, 0.97, 0.97, and 0.99 for axial (intact), axial (implanted), bending, torsional loading). For each of the load cases the intersects of the regression lines were small in comparison to the maximum measured strains (< 1.5%). While the model was more rigid than the bone under torsional loading (slope =0.92), the opposite was true for axial (slope = 1.14 (intact) 1.24 (implanted)) and bending (slope = 1.06) loads. This is probably due to a discrepancy in the material properties of the model.