In patients with neural disorders such as cerebral palsy, three-dimensional marker-based motion analysis has evolved to become a well standardized procedure with a large impact on the clinical decision-making process. On the other hand, in knee arthroplasty research, motion analysis has been little used as a standard tool for objective evaluation of knee joint function. Furthermore, in the available literature, applied methodologies are diverse, resulting in inconsistent findings [1]. Therefore we developed and evaluated a new motion analysis framework to enable standardized quantitative assessment of knee joint function. The proposed framework integrates a custom-defined motion analysis protocol with associated reference database and a standardized post-processing step including statistical analysis. Kinematics are collected using a custom-made marker set defined by merging two existing protocols and combine them with a knee alignment device. Following a standing trial, a star-arc hip motion pattern and a set of knee flexion/extension cycles allowing functional, subject-specific calibration of the underlying kinematic model, marker trajectories are acquired for three trials of a set of twelve motor tasks: walking, walking with crossover turn, walking with sidestep turn, stair ascent, stair descent, stair descent with crossover turn, stair descent with sidestep turn, trunk rotations, chair rise, mild squat, deep squat and lunge. This specific set of motor tasks was selected to cover as much as possible common daily life activities. Furthermore, some of these induce greater motion at the knee joint, thus improving the measurement-to-error ratio. Kinetics are acquired by integrating two forceplates in the walkway. Bilateral muscle activity of 8 major muscles is monitored with a 16 channel wireless electromyography (EMG) system. Finally, custom-built software with an associated graphical user interface was created for automated and flexible analysis of gait lab data, including repeatability analysis, analysis of specific kinematic, kinetic and spatiotemporal parameters and statistical comparisons.INTRODUCTION
MATERIALS AND METHODS
After total knee arthroplasty (TKA) with a PCL-retaining implant the location of the tibiofemoral contact point should be restored in order to obtain normal kinematics. The difficulty during surgery is to control this location since the position of the femur on the tibia cannot easily be measured from the back of the joint. Therefore, we developed a simple “spacer technique” to check the contact point indirectly in 90° flexion after all bone cuts are made by measuring the step-off between the distal cut of the femur and the anterior edge of the tibia with a spacer in place. The goal of this experiment was to investigate whether this new PCL balancing approach with the spacer technique created the correct contact point location. Nine fresh-frozen full leg cadaver specimens were used. After native testing, prototype components of a new PCL-retaining implant were implanted using navigation and a bone-referenced technique. After finishing the bone cuts of tibia and femur, the spacer was inserted in flexion and positioned on the anterior edge of the bony surface to measure the step-off. If necessary, an extra cut was made to balance the PCL. The specimen was mounted on the knee kinematics rig and a squat with constant vertical ankle force (130N) and constant medial and lateral hamstrings forces (50N) was performed between 30° and 130° of knee flexion. The trajectories of the reflective tibial and femoral markers were continuously recorded using six infrared cameras. The projections of the femoral condylar centers on the horizontal plane of the tibia were calculated and compared.Introduction
Methods
Proper positioning of the components of a knee prosthesis for obtaining post-operative knee joint alignment is vital to obtain good and long term performance of a knee replacement. Although the reasons for failure of knee arthroplasty have not been studied in depth, the few studies that have been published claim that as much as 25% of knee replacement failures are related to malpositioning or malalignment [x]. The use of patient-matched cutting blocks is a recent development in orthopaedics. In contrast to the standard cutting blocks, they are designed to fit the individual anatomy based on 3D medical images. Thus, landmarks and reference axes can be identified with higher accuracy and precision. Moreover, stable positioning of the blocks with respect to the defined axes is easier to achieve. Both may contribute to better alignment of the components. The objective of this study was to check the accuracy of femoral component orientation in a cadaver study using specimen-matched cutting blocks in six specimens; first for a bi-compartmental replacement, and then for a tri-compartmental replacement in the same specimen. Frames with infrared reflective spherical markers were fixed to six cadaveric femurs and helical CT scans were made. A bone surface reconstruction was created and the relevant landmarks for describing alignment were marked using 3D visualisation software (Mimics). The centres of the spherical markers were also determined. Based on the geometry of the articular surface and the position of the landmarks, custom-made cutting blocks were designed. One cutting block was prepared to guide implantation of a bi-compartmental device and another one to guide implantation of the femoral component of a total knee replacement. The knee was opened and the custom-made cutting block for the bi-compartmental implant was seated onto the surface. The block was used to make the anterior cut, after which it was removed and replaced with the conventional cutting block using the same pinning holes to ensure the same axial rotational alignment. The other cuts were made using the conventional cutting block and the bi-compartmental femoral component was implanted. Afterwards, a similar procedure was used to make the extra cuts for the total knee component. The position of the components with respect to the reflective markers was measured by locating three reference points and “painting” the articular surface with a wand with reflective markers. The position of all marker spheres was continuously recorded with four infrared cameras and Nexus software.Purpose
Materials and Methods
