INTRODUCTION

Highly cross-linked polyethylene (XLPE) inserts have shown significant improvements in decreasing wear and osteolysis in total hip arthroplasty [1]. In contrast to that, XLPE has not shown to reduce wear or aseptic loosening in total knee arthroplasty [2,3,4].

One major limitation is that current wear testing in vitro is mainly focused on abrasive-adhesive wear due to level walking test conditions and does not reflect “delamination” as an essential clinical failure mode [5,6].

The objective of our study was to use a highly demanding daily activities wear simulation to evaluate the delamination risk of polyethylene materials with and without vitamin E stabilisation.

Musculoskeletal loading plays an important role in the primary stability of THA. There are about 210,000 primary THA interventions p.a. in Germany. Consideration of biomechanical aspects during computer-assisted orthopaedic surgery is recommendable in order to obtain satisfactory long-term results. For this purpose simulation of the pre- and post-operative magnitude of the resultant hip joint force R and its orientation is of interest. By means of simple 2D-models (Pauwels, Debrunner, Blumentritt) or more complex 3D-models (Iglič), the magnitude and orientation of R can be computed patient-individually depending on their geometrical and anthropometrical parameters. In the context of developing a planning module for computer-assisted THA, the objective of this study was to evaluate the mathematical models. Therefore, mathematical model computations were directly compared to in-vivo measurements obtained from instrumented hip implants.

With patient-specific parameters the magnitude and orientation of R were model-based computed for three patients (EBL, HSR, KWR) of the OrthoLoad-database. Their patient-specific parameters were acquired from the original patient X-rays. Subsequently, the computational results were compared with the corresponding in-vivo telemetric measurements published in the OrthoLoad-database. To obtain the maximum hip joint load, the static single-leg-stance was considered. A reference value for each patient for the maximum hip load under static conditions was calculated from OrthoLoad-data and related to the respective body weights (BW).

On average there are large deviations of the results for the magnitude (Ø=147%) and orientation (Ø=14.35° too low) of R obtained by using Blumentritt's model from the in-vivo results/measurements. The differences might be partly explained by the supplemental load of 20% BW within Blumentritt's model which is added to the input parameter BW in order to consider dynamic gait influences. Such a dynamic supplemental load is not applied within the other static single-leg-stance models. Blumentritt's model assumptions have to be carefully reviewed due to the deviations from the in-vivo measurement data.

Iglič's 3D-model calculates the magnitude (Ø17%) and the orientation (Ø49%) of R slightly too low. For the magnitude one explanation could be that his model considers nine individual 3D-sets of muscle origins and insertion points taken from literature. This is different from other mathematical models. The patient-individual muscle origin and insertion points should be used.

Pauwels and Debrunner's models showed the best results. They are in the same range compared to in-vivo data. Pauwels's model calculates the magnitude (Ø5%) and the orientation (Ø28%) of R slightly higher. Debrunner's model calculates the magnitude (Ø1%) and the orientation (Ø14%) of R slightly lower.

In conclusion, for the orientation of R, all the computational results showed variations which tend to depend on the used model.

There are limitations coming along with our study: as our previous studies showed, an unambiguous identification of most landmarks in an X-ray (2D) image is hardly possible. Among the study limitations there is the fact that the OrthoLoad-database currently offers only three datasets for direct comparison of static single leg stance with in-vivo measurement data of the same patient. Our ongoing work is focusing on further validation of the different mathematical models.

Introduction

Realistic knee contact forces and moments are needed for testing implant wear, fatigue and static strength, for analysing strains and remodelling at interfaces, as ‘gold standard’ for analytical musculo-skeletal models, or as input for finite element models. ISO 14243 defines the loading conditions for wear tests, but the defined loads from walking are based on very old data.

Accurate in vivo knee joint contact forces are required for joint simulator protocols and finite element models during the development and testing of total knee replacements (Varadarajan et al., 2008.) More accurate knowledge of knee joint contact forces during high flexion activities may lead to safer high flexion implant designs, better understanding of wear mechanisms, and prevention of complications such as aseptic loosening (Komistek et al., 2005.) High flexion is essential for lifestyle and cultural activities in the developing world, as well as in Western cultures, including ground-level tasks and chores, prayer, leisure, and toileting (Hemmerich et al., 2006.) In vivo tibial loads have been reported while kneeling; but only while the subject was at rest in the kneeling position (Zhao et al., 2007), meaning that the loads were submaximal due to muscle relaxation and thigh-calf contact support. The objective of this study was to report the in vivo loads experienced during high flexion activities and to determine how closely the measured axial joint contact forces can be estimated using a simple, non-invasive model. It provides unique data to better interpret non-invasively determined joint-contact forces, as well as directly measured tiobiofemoral joint contact force data for two subjects.

Two subjects with instrumented tibial implants performed kneeling and deep knee bend activities. Two sets of trials were carried out for each activity. During the first set, an electromagnetic tracking system and two force plates were used to record lower limb kinematics and ground reaction forces under the foot and under the knee when it was on the ground. In the second set, three-dimensional joint contact forces were directly measured in vivo via instrumented tibial implants (Heinlein et al., 2007.) The measured axial joint contact forces were compared to estimates from a non-invasive joint contact force model (Smith et al., 2008.)

The maximum mean axial forces measured during the deep knee bend were 24.2 N/kg at 78.2° flexion (subject A) and 31.1 N/kg at 63.5° flexion (subject B) during the deep knee bend (Figure 1.) During the kneeling activity, the maximum mean axial force measured was 29.8 N/kg at 86.8° flexion (subject B.) While the general shapes of the model-estimated curves were similar to the directly measured curves, the axial joint contact force model underestimated the measured contact forces by 7.0 N/kg on average (Figure 2.) The most likely contributor to this underestimation is the lack of co-contraction in the model.

The study protocol was limited in that data could not be simultaneously collected due to electromagnetic interference between the motion tracking system and the inductively powered instrumented tibial component. Because skin-mounted markers were used, kinematics may be affected by skin motion artefacts. Despite these limitations, this study presents valuable information that will advance the development of high flexion total knee replacements. The study provides in vivo measurements and non-invasive estimates of joint contact forces during high flexion activities that can be used for joint simulator protocols and finite element modeling.