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Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_20 | Pages 48 - 48
1 Dec 2017
Verstraete M Arnout N De Baets P Vancouillie T Van Hoof T Victor J
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INTRODUCTION

To assess and compare the effect of new orthopedic surgical procedures, in vitro evaluation remains critical during the pre-clinical validation. Focusing on reconstruction surgery, the ability to restore normal kinematics and stability is thereby of primary importance. Therefore, several simulators have been developed to study the kinematics and create controlled boundary conditions.

To simultaneously capture the kinematics in six degrees of freedom as outlined by Grood & Suntay, markers are often rigidly connected to the moving bone segments. The position of these markers can subsequently be tracked while their position relative to the bones is determined using computed tomography (CT) of the test specimen with the markers attached. Although this method serves as golden standard, it clearly lacks real-time feedback. Therefore, this paper presents the validation of a newly developed real-time framework to assess knee kinematics at the time of testing.

MATERIALS & METHODS

A total of five cadaveric fresh frozen lower limb specimens have been used to quantitatively assess the difference between the golden standard, CT based, method and the newly developed real-time method. A schematic of the data flow for both methods. Prior to testing, both methods require a CT scan of the full lower limb. During the tests, the proximal femur and distal tibia are necessarily resected to fit the knees in the test setup, thus also removing the anatomical landmarks needed to evaluate their mechanical axis. Subsequently, a set of three passive markers are rigidly attached to the femur and tibia, referred to as M3F and M3T respectively. For the CT based method, the marker positions are captured during the tests and a second CT scan is eventually performed to link the marker positions to the knee anatomy. Using in-house developed software, this allowed to offline evaluate the knee kinematics in six degrees of freedom by combining both CT datasets with the tracked marker positions. For the newly developed real-time method, a calibration procedure is first performed. This calibration aims to link the position of the 3D reconstructed bone and landmarks with the attached markers. A set of bone surface points is therefore registered. These surface points are obtained by tracking the position of a pen while touching the bone surface. The pen's position is thereby tracked by three rigidly attached markers, denoted M3P. The position of the pen tip is subsequently calculated from the known pen geometry. The iterative closest point (ICP) algorithm is then used to match the 3D reconstructed bone to the registered surface points. Two types of 3D reconstructions have therefore been considered. First, the original reconstructions were used, obtained from the CT data. Second, a modified reconstruction was used. This modification accounted for the finite radius (r = 1.0 mm) of the registration pen, by shifting the surface nodes 1.0 mm along the direction of the outer surface normal. During the tests, the positions of the femur and tibia markers are tracked and streamed in real-time to an in-house developed, Matlab based software framework (MathWorks Inc., Natick, Massachussets, USA). This software framework simultaneously calculates the bone positions and knee kinematics in six degrees of freedom, displaying this information to the surgeons and operators. To assess the accuracy, all knee specimens have been subjected to passive flexion-extension movement ranging from 0 to 120 degrees of flexion. For each degree of freedom, the average root mean square (RMS) difference between both measurement methods has been evaluated during this movement. In addition, the distribution of the registered surface points has been assessed along the principal directions of the uniformly meshed 3D reconstructions (average mesh size of 1.0 mm).


Orthopaedic Proceedings
Vol. 99-B, Issue SUPP_6 | Pages 64 - 64
1 Mar 2017
Van Onsem S Van Der Straeten C Arnout N Deprez P Van Damme G Victor J
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Background

Total knee arthroplasty (TKA) is a proven and cost-effective treatment for osteoarthritis. Despite the good to excellent long-term results, some patients remain dissatisfied. Our study aimed at establishing a predictive model to aid patient selection and decision-making in TKA.

Methods

Using data from our prospective arthroplasty outcome database, 113 patients were included. Pre- and postoperatively, the patients completed 107 questions in 5 questionnaires: KOOS, OKS, PCS, EQ-5D and KSS. First, outcome parameters were compared between the satisfied and dissatisfied group. Secondly, we developed a new prediction tool using regression analysis. Each outcome score was analysed with simple regression. Subsequently, the predictive weight of individual questions was evaluated applying multiple linear regression. Finally, 10 questions were retained to construct a new prediction tool.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_10 | Pages 105 - 105
1 May 2016
Verstraete M Van Onsem S Stevens C Arnout N Victor J
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For evaluating the impact of knee surgery, cadaveric knee simulators are commonly applied. However, most of the knee simulators are based on the Oxford type as originally described by Zavatsky (Zavatsky, J. of Biomechanics, 1997). These simulators mainly focus on the squatting motion. Although a wide range of flexion angles can be examined while performing this motion, the significance for activities of daily living is limited.

To that extent a new knee simulator has recently been developed at Ghent University. In this simulator, the ankle motion is dynamically controlled in the sagittal plane; both in the proximal/distal direction and the anterior/posterior direction. As a result, this simulator allows simulating random motion patterns, e.g. cycling, stair ascent and descent, … The ankle translation is unrestrained in the medial/lateral direction. In addition, all rotational degrees of freedom are unrestrained at the ankle, resulting in four degrees of freedom at the ankle. The hip adds one rotational degree of freedom being the rotation in the sagittal plane. This leaves 5 degrees of freedom (DOF) to the knee; the sixth being flexion/extension that is controlled by the actuators at the ankle. During the simulation of different motion patterns, the quadriceps and hamstring force are actively controlled to mimic realistic conditions obtained through musculoskeletal simulations.

In this study, five cadaveric experiments have been performed on the simulator. While mounting the cadaveric specimens in the test rig, the initial alignment remains crucial. Whilst the rig leaves 5 DOF to the knee, it is important to restore the anatomical position of the hip and ankle. To minimize the impact of the mounting procedure, cadaver specific 3D printed guides are used to assure the alignment of the cadaver in the test rig. As a result, the kinematics are more likely to represent physiological conditions. These kinematics have been evaluated in accordance to the methodology described by Grood&Suntay (Grood & Suntay, Transactions of the ASME, 1983). Therefore, a CT scan of the examined knee is combined with motion tracking data from rigidly attached markers on both the femur and the tibia. The cadaveric knees have been subjected to a variety of motion patterns, i.e. squatting and cycling. The squatting experiments provide evidence that the knee simulator creates adequate boundary conditions as the kinematic patterns coincide with literature reportings. The cycling experiments however significantly differ from the squatting patterns. Most noteworthy is the difference in terms of internal/external rotation for these native knees (Figure 1). This internal/external rotations is highly fluctuating from flexion to extension. This is understood as the quadriceps force is not constant during the extension phase, representing physiological conditions.

Conclusion

Significant difference in knee kinematics between squatting and cycling indicates the importance of testing a variety of conditions. Furthermore, this reveals the need to study clinically relevant motion patterns, selected from patient reported outcomes.


Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_10 | Pages 106 - 106
1 May 2016
Verstraete M Van Onsem S Biebouw S Cortens W Arnout N Victor J
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Total knee arthroplasty aims at restoring the function of the native knee. An important aspect at this point are the knee kinematics, as it can be assumed that following TKA surgery these should resemble the native conditions. The use of cadaveric testing is since long an important step in the development and validation of implant designs and surgical techniques. However, this cadaveric testing has primarily focused on squatting under load bearing conditions. The main research question of this paper is therefore to evaluate the impact of TKA surgery on the knee kinematics under a range of boundary conditions.

A set of five cadaveric knees have been tested in a newly developed and validated knee simulator at Ghent University. In contrast to other simulators, this simulator allows simulating a wide range of conditions as it facilitates a controlled movement of the ankle in the sagittal plane under continuously variable hamstring and quadriceps loading. In the framework of this study, two different motion patterns have been studied. First, the knees were subjected to a traditional squatting motion maintaining constant quadriceps loading. Second, the knees were tested while performing a cycling movement with a highly variable quadriceps load during the extension phase. For both cases, the studied motion patterns have been repeated five times. Following the evaluation of the native knee kinematics, TKA surgery was performed using a single radius implant. During surgery, the implant alignment has been controlled using computer navigation. Subsequently, the same boundary conditions have been applied and the kinematics again recorded.

Focusing on the native knee, the measured kinematic patterns for the squatting motion significantly differ from the ones observed for the cycling movement for similar flexion angles. This is attributed to a difference in quadriceps loading. However, following TKA surgery, the kinematic patterns are remarkably comparable between the squatting and cycling experiments. These observations suggest that the TKA design considered in this study displays a highly constrained behavior. More specifically, the design appears to favor the squatting behavior. Further study is however required to thoroughly evaluate this observation for other implant designs and a wider range of motion patterns.