Previously more femoral rollback has been reported in posterior-stabilized implants, but so far the kinematic change after post-cam engagement has been still unknown. The tri-condylar implants were developed to fit a life style requiring frequent deep flexion activities, which have the ball and socket third condyle as post-cam mechanism. The purpose of the current study was to examine the kinematic effects of the ball and socket third condyle during deep knee flexion. The tri-condylar implant analyzed in the current study is the Bi-Surface Knee System developed by Kyocera Medical (Osaka, Japan). Seventeen knees implanted with a tri-condylar implant were analyzed using 3D to 2D registration approach. Each patient was asked to perform a weight-bearing deep knee bend from full extension to maximum flexion under fluoroscopic surveillance. During this activity, individual fluoroscopic video frames were digitized at 10°increments of knee flexion. A distance of less than 1 mm initially was considered to signify the ball and socket contact. The translation rate as well as the amount of translation of medial and lateral AP contact points and the axial rotation was compared before and after the ball and socket joint contact. The average angle of ball and socket joint contact were 64.7° (SD = 8.7), in which no separation was observed after initial contact. The medial contact position stayed from full extension to ball and socket joint contact and then moved posteriorly with knee flexion. The lateral contact position showed posterior translation from full extension to ball and socket joint contact, and then greater posterior translation after contact (Figure 1). Translation and translation rate of contact positions were significantly greater at both condyles after ball and socket joint contact. The femoral component rotated externally from full extension to ball and socket joint contact, and then remained after ball and socket joint contact (Figure 2). There was no statistical significance in the angular rotation between ball and socket joint contact and maximum flexion. Translation of angular rotation was significantly greater before ball and socket joint contact, however, there was no significance in translation rate before and after ball and socket joint contact. The ball and socket joint was proved to induce posterior rollback intensively. In terms of axial rotation, the ball and socket joint did not induce reverse rotation, but had slightly negative effects after contact. The ball and socket provided enough functions as a posterior stabilizing post-cam mechanism and did not prevent axial rotation.
The low-cost, no-harm conditions associated with vibroarthography, the study of listening to the vibrations and sound patterns of interaction at the human joints, has made this method a promising tool for diagnosing joint pathologies. This current study focuses on the knee joint and aims to synchronize computational models with vibroarthographic signals via a comprehensive graphical user interface (GUI) to find correlations between kinematics, vibration signals, and joint pathologies. This GUI is the first of its kind to synchronize computational models with vibroarthographic signals and gives researchers a new advantage of analyzing kinematics, vibration signals, and pathologies simultaneously in an easy-to-use software environment. The GUI (Figure 1) has the option to view live or previously captured fluoroscopic videos, the corresponding computational model, and/or the pre- or post-processed vibration signals. Having more than one signal axes available allows for comparison of different filtering techniques to the same signal, or comparison of signals coming from different sensor placements (ex: medial vs. lateral femoral condyle). Using computational models derived using fluoroscopic data synchronized with the vibration signals, the areas of contact between articulating surfaces can be mapped for the in vivo signal (figure 2). This new method gives the opportunity to find correlations between the different sensor signals and contact maps with the diagnosis and cartilage degeneration map, provided by a surgeon, during arthroscopy or TKA implantation (figure 3).Introduction
Methods
In-vivo data pertaining to the actual cam-post engagement mechanism in PS and Bi-Cruciate Stabilized (BCS) knees is still very limited. Therefore, the objective of this study was to determine the cam-post mechanism interaction under in-vivo, weight-bearing conditions for subjects implanted with either a Rotating Platform (RP) PS TKA, a Fixed Bearing (FB) PS TKA or a FB BCS TKA. In-vivo, weight-bearing, 3D knee kinematics were determined for eight subjects (9 knees) having a RP-PS TKA (DePuy Inc.), four subjects (4 knees) with FB-PS TKA (Zimmer Inc.), and eight subjects (10 knees) having BCS TKA (Smith&Nephew Inc.), while performing a deep knee bend. 3D-kinematics was recreated from fluoroscopic images using a previously published 3D-to-2D registration technique (Figure 1). Images from full extension to maximum flexion were analyzed at 10° intervals. Once the 3D-kinematics of implant components was recreated, the cam-post mechanism was scrutinized. The distance between the interacting surfaces was monitored throughout flexion and the predicted contact map was calculated.INTRODUCTION
METHODS
Previous fluoroscopic studies compared total knee arthroplasty (TKA) kinematics to normal knees. It was our hypothesis that comparing TKA directly to its non-replaced controlateral knee may provide more realistic kinematics information. Using fluoroscopic analysis, we aimed to compare knee flexion angles, femoral roll-back, patellar tracking and internal and external rotation of the tibia. 15 patients (12 women and 3 men) with a mean age of 71.8 years (SD=7.4) operated by the same surgeon were included in this fluoroscopic study. For each patient at a minimum one year after mobile-bearing TKA, kinematics of the TKA was compared to the controlateral knee during three standardized activities: weight-bearing deep-knee bend, stair climbing and walking. A history of trauma, pain, instability or infection on the non-replaced knee was an exclusion criteria. A CT-scan of the non-replaced knee was performed for each patient to obtain a 3-D model of the knee. The Knee Osteoarthitis Outcome Score (KOOS) was also recorded.Introduction
Material and methods
Posterior stabilized (PS) total knee arthroplasty (TKA) provides posterior stability with the use of a cam-post mechanism which performs the function of the posterior cruciate ligament. The tibial post engages with the femoral cam, prevents the femur from sliding anteriorly and provides the posterior femoral rollback necessary for achieving deep flexion of the knee. However, these designs do not substitute the resection of the anterior cruciate ligament. In order to overcome this deficit, other TKA designs have been recently introduced to provide dual support, with the help of dual cam-post engagement mechanism. Various studies conducted on the PS TKA have suggested that the cam-post mechanism does not engage as designed, resulting in tibial post wear and increased stresses resulting in backside wear of the polyethylene insert component. Also, the in vivo data pertaining to the actual cam-post engagement mechanism in bi-cruciate stabilized knees is still very limited. Therefore, the objective of this study was to determine the cam-post mechanism interaction under in vivo, weight bearing conditions for subjects implanted with either a Rotating Platform (RP) Posterior Stabilized (PS) TKA or a bi-cruciate stabilizing TKA (BCS). In-vivo, weight-bearing, 3D knee kinematics were determined for eight subjects (9 knees) having a RP-PS TKA (DePuy Inc.) and eight subjects (10 knees) having BCS TKA (Smith&Nephew Inc.), while performing a deep knee bend. 3D kinematics was recreated from the fluoroscopic images using a previously published 3D-to-2D registration technique (Figure 1). Images from full extension to maximum flexion were analyzed at 10° intervals. Once the 3D kinematics of all implant components was recreated, the cam-post mechanism was scrutinized. The distance between the interacting surfaces was monitored throughout the flexion and the predicted contact map was calculated. The instances, when the minimum distance between the cam and post surfaces dropped to zero was considered to indicate the engagement of the mechanism. This analysis was carried out for both the, anterior and posterior cam-post engagement sites.INTRODUCTION
METHODS
Knee simulators are being used to evaluate wear. The current international standards have been developed from clinical investigations of the normal knee [1, 2] or from a single TKA patient [3, 4]. However, the forces and motions in a TKA patient differ from a normal knee and, furthermore, the resulting kinematic outcomes after TKA will depend on the design of the device [5]. Consequently, these standard tests may not recreate in-vivo conditions; therefore, the goal of this study was to perform a novel wear simulation using design-specific inputs that have been derived from fluoroscopic images of a deep knee bend. A wear simulation was developed using fluoroscopic data from a pool of eighteen TKA patients performing a deep knee bend. All patients had a Sigma CR Fixed Bearing implant (DePuy) and were well functioning (Knee Society Score > 90). A single patient was selected that represented the typical motions, which was characterized by early rollback followed by anterior motion with an overall modest internal tibial rotation (Figure 1). The relative motion between the femoral and tibial components was transformed to match the coordinate system of an AMTI knee wear simulator [6] and a compressive load input was derived using inverse dynamics [7]. The resulting force and motions (Figure 2) were then applied in a wear simulation with 5 MRad crosslinked and remelted polyethylene for 3 Mcyc at 1 Hz. Components were carefully positioned and each joint (n=3) was tested in 25% bovine calf serum (Hyclone Laboratories), which was recirculated at 37±2°C [3]. Serum was supplemented with sodium azide and EDTA. Wear was quantified gravimetrically every 0.5 Mcyc using a digital balance (XP250, Mettler-Toledo) with load soak compensation.INTRODUCTION
METHODS
Anterior knee pain is one of the most frequently reported musculoskeletal complaints in all age groups. However, patient's complaints are often nonspecific, leading to difficulty in properly diagnosing the condition. One of the causes of pain is the degeneration of the articular cartilage. As the cartilage deteriorates, its ability to distribute the joint reaction forces decreases and the stresses may exceed the pain threshold. Unfortunately, the assessment of the cartilage condition is often limited to a detailed interview with the patient, careful physical examination and x-ray imaging. The X-ray screening may reveal bone degeneration, but does not carry sufficient information of the soft tissues' conditions. More advanced imaging tools such as MRI or CT are available, but these are expensive, time consuming and are only suitable for detection of advanced arthritis. Arthroscopic surgery is often the only reliable option, however due to its semi-invasive nature, it cannot be considered as a practical diagnostic tool. However, as the articular cartilage degenerates, the surfaces become rougher, they produce higher vibrations than smooth surfaces due to higher friction during the interaction. Therefore, it was proposed to detect vibrations non-invasively using accelerometers, and evaluate the signals for their potential diagnostic applications. Vibration data was collected for 75 subjects; 23 healthy and 52 subjects suffering from knee arthritis. The study was approved by the IRB and an Informed Consent was obtained prior to data collection. Five accelerometers were attached to skin around the knee joint (at the patella, medial and lateral femoral condyles, tibial tuberosity and medial tibial plateau). Each subject performed 5 activities; (1) flexion-extension, (2) deep knee bend, (3) chair rising, (4) stair climbing and (5) stair descent. The vibration and motion components of the signals were separated by a high pass filter. Next, 33 parameters of the signals were calculated and evaluated for their discrimination effectiveness (Figure 1). Finally the pattern recognition method based on Baysian classification theorem was used for classify each signal to either healthy or arthritic group, assuming equal prior probabilities. The variance and mean of the vibration signals were significantly higher in the arthritic group (p=2.8e-7 and p=3.7e-14, respectively), which confirms the general hypothesis that the vibration magnitudes increase as the cartilage degenerates. Other signal features providing good discrimination included the 99th quantile, the integral of the vibration signal envelope, and the product of the signal envelope and the activity duration. The pattern classification yielded excellent results with the success rate of up to 92.2% using only 2 features, up to 94.8% using 3 (Figure 2), and 96.1% using 4 features. The current study proved that the vibrations can be studied non-invasively using a low-cost technology. The results confirmed the hypothesis that the degeneration of the cartilage increases the vibration of the articulating bones. The classification rate obtained in the study is very encouraging, providing over 96% accuracy. The presented technology has certainly a potential of being used as an additional screening methodology enhancing the assessment of the articular cartilage condition.
Total shoulder arthroplasty (TSA) implants are used to restore function to individuals whose shoulder motions are impaired by osteoarthritis. To improve TSA implant designs, it is crucial to understand the kinematics of healthy, osteoarthritic (OA), and post-TSA shoulders. Hence, this study will determine in vivo kinematic trends of the glenohumeral joints of healthy, OA, and post-TSA shoulders. In vivo shoulder kinematics were determined pre and post-operatively for five unilateral TSA subjects with one healthy and a contralateral OA glenohumeral joint. Fluoroscopic examinations were performed for all three shoulder categories (healthy, OA, and post-TSA) for each subject shoulder abduction and external rotation. Then, three-dimensional (3D) models of the left and right scapula and humerus were constructed using CT scans. For post-operative shoulders, 3D computer-aided design models of the implants were obtained. Next, the 3D glenohumeral joint kinematics were determined using a previously published 3D to 2D registration technique. After determining kinematics, relative Euler rotation angles between the humerus and scapula were calculated in MATLAB® to determine range of motion (ROM) and kinematic profiles for all three shoulder categories. The ROMs for each category were compared using paired t-tests for each exercise. Also, the location of the contact point of the humerus on the glenoid was found. This allowed the vertical translation from the most superior to most inferior contact point (SI contact range) to be calculated as well as the horizontal translation from the most anterior to most posterior contact point (AP contact range). The SI and AP contact ranges for all shoulder categories were compared using paired t-tests for each exercise.INTRODUCTION
Methods
