The purpose of this study is to elucidate longitudinal kinematic changes of the hip joint during heels-down squatting after THA. 66 patients with 76 primary cementless THAs using a CT-based navigation system were investigated using fluoroscopy. An acetabular component and an anatomical femoral component were used through the mini-posterior approach with repair of the short rotators. The femoral head size was 28mm (9 hips), 32mm (12 hips), 36mm (42 hips), and 40mm (12 hips). Longitudinal evaluation was performed at 3 months, 1 year, and 2≤ years postoperatively. Successive hip motion during heels-down squatting was recorded as serial digital radiographic images in a DICOM format using a flat panel detector. The coordinate system of the acetabular and femoral components based on the neutral standing position was defined. The images of the hip joint were matched to 3D-CAD models of the components using a2D/3D registration technique. In this system, the root mean square errors of rotation was less than 1.3°, and that of translation was less than 2.3 mm. We estimated changes in the relative angle of the femoral component to the acetabular component, which represented the hip ROM, and investigated the incidence of bony and/or prosthetic impingement during squatting (Fig.1). We also estimated changes in the pelvic posterior tilting angle (PA) using the acetabular component position change. In addition, when both components were positioned most closely during squatting, we estimated the minimum angle (MA) up to theoretical prosthetic impingement as the safety margin (Fig.2).INTRODUCTION
METHODS
To achieve 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques, which use X-ray fluoroscopic images and computer aided design model of the knee implants, have been applied to clinical cases. However, most conventional methods have needed time-consuming and labor-intensive manual operations in some process. In particular, for the 3D pose estimation of tibial component model from X-ray images, these manual operations were carefully performed because the pose estimation of symmetrical tibial component get severe local minima rather than that of unsymmetrical femoral component. In this study, therefore, we propose an automated 3D kinematic estimation method of tibial component based on statistical motion model, which is created from previous analyzed 3D kinematic data of TKA. The used 2D/3D registration technique is based on a robust feature-based (contour-based) algorithm. In our proposed method, a statistical motion model which represents average and variability of joint motion is incorporated into the robust feature-based algorithm, particularly for the pose estimation of tibial component. The statistical motion model is created from previous a lot of analyzed 3D kinematic data of TKA. In this study, a statistical motion model for relative knee motion of the tibial component with respect to the femoral component was created and utilized. Fig. 1 shows each relative knee motion model for six degree of freedom (three translations and three rotations parameter). Thus, after the pose estimation of the femoral component model, 3D pose of the tibial component model is determined by maximum a posteriori (MAP) estimation using the new cost function introduced the statistical motion model.Purpose
Methods
Most of in vivo kinematic studies of total knee arthroplasty (TKA) have reported on varus knee. TKA for the valgus knee deformity is a surgical challenge. The purposes of the current study are to analyze the in vivo kinematic motion and to compare kinematic patterns between weight-bearing (WB) and non-weight-bearing (NWB) knee flexion in posterior-stabilized (PS) fixed-bearing TKA with pre-operative valgus deformity. A total of sixteen valgus knees in 12 cases that underwent TKA with Scorpio NRG PS knee prosthesis operated by modified gap balancing technique were evaluated. The mean preoperative femorotibial angle (FTA) was 156°±4.2°. During the surgery, distal femur and proximal tibia was cut perpendicular to the mechanical axis of each bone. After excision of the menisci and cruciate ligaments, balancer (Stryker joint dependent kinematics balancer) was inserted into the gap between both bones for evaluation of extension gap. Lateral release was performed in extension. Iliotibial bundle (ITB) was released from Gerdy tubercle then posterolateral capsule was released at the level of the proximal tibial cut surface. If still unbalanced, pie-crust ITB from inside-out was added at 1 cm above joint line until an even lateral and medial gap had been achieved. Flexion gap balance was obtained predominantly by the bone cut of the posterior femoral condyle. Good postoperative stability in extension and flexion was confirmed by stress roentgenogram and axial radiography of the distal femur. We evaluated the in vivo kinematics of the knee using fluoroscopy and femorotibial translation relative to the tibial tray using a 2-dimentional to 3-dimensional registration technique.Backgrounds
Methods
The deformity in osteoarthritis (OA) of the knee has been evaluated mainly in the frontal plane two dimensional X-ray using femorotibial angle. Although the presence of underlying rotational deformity in the varus knee and coexisting hip abnormality in the valgus knee have been suggested, three dimensional (3D) deformities in the varus and valgus knee were still unknown. We evaluated the 3D deformities of the varus and valgus knee using 3D bone models. Preoperative computed tomography (CT) scans of twenty seven OA knees (fifteen varus and twelve valgus) undergoing total knee arthroplasty were assessed in this study. CT scans of each patient's femur and tibia, with a 2 mm interval, obtained before surgery. We created the 3D digital model of the femur and tibia using visualization and modeling software developed in our institution. The femoral coordinate system was calculated by the 3D mechanical axis and clinical transepicondylar axis and the tibial coordinate system was calculated by the 3D mechanical axis and Akagi's line. The 3D deformities of the knee were determined by the relative position of the femorotibial coordinate system, and described by the tibial position relative to the femur. The anteversion of the femoral neck were calculated to evaluate the relationship between the valgus knee and hip region.Introduction
Methods
Posterior cruciate ligament (PCL) preservation in total knee arthroplasty (TKA) is adovocated on the grounds that it provides better restoration of knee joint kinematics as opposed to PCL sacrifice. Mobile-bearing (MB) total knee prostheses have been in the market for a long time, but the PFC-Sigma Rotating Platform (RP) prosthesis (DePuy Orthopaedics, Inc, Warsaw, Ind) has been introduced in the market since 2000. Since, little is known about the in vivo kinematics of MB prostheses especially with cruciate retaining (CR). The objective of this study is to investigate the in vivo kinematics of MB RP-CR total knee arthroplasty during weight-bearing deep knee bending motion. We investigated the in vivo knee kinematics of 20 knees (17 patients) implanted with PFC-Sigma RP-CR. All TKAs were judged clinically successful (Hospital for Special Surgery scores >90), with no ligamentous laxity or pain. Mean patient age at the time of operation was 78.0 ± 6.0 years. Mean period between operation and surveillance was 15.0 ± 9.0 months. Under fluoroscopic surveillance, each patient did a wight-bearing deep knee bending motion. Femorotibial motion was analyzed using 2D/3D registration technique, which uses computer-assisted design (CAD) models to reproduce the spatial position of the femoral, tibial components from single-view fluoroscopic images. We evaluated the range of motion, axial rotation, and antero-posterior (AP) translation of the nearest point between the femoral and tibial component.Introduction
Patients and methods
To achieve 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques which use X-ray fluoroscopic images and computer-aided design (CAD) model of the knee implants, have been applied to clinical cases. These techniques are highly valuable for dynamic 3D kinematic measurement of TKA implants, but have needed time-consuming and labor-intensive manual operations in some process. To overcome a manual operations problem of initial pose estimation for 2D/3D registration, this study proposes an improvement method for semi-automated 3D kinematic measurement of TKA using X-ray fluoroscopic images. To automatically estimate the initial pose of the implant CAD model, we utilise a transformation with feature points extracted from the previous and next frames. A transform matrix which has three degree of freedom (translations parallel to the image, and a rotation perpendicular to the image) is calculated by registration of corresponding feature points between the previous and next frame extracted with speeded up robust features (SURF) algorithm. While, the corresponding point sets extracted by SURF sometimes include some error sets. Therefore, in this study, least median of squares method is employed to detect the error corresponding sets and calculate a transform matrix accurately. Finally, the 3D pose of the model estimated (by the 2D/3D registration) in previous frame is transformed with the accurately calculated transform matrix, and the transformed pose is used as an initial 3D pose of the model (for the 2D/3D registration) in next frame. To validate the feasibility of the improved semi-automated 3D kinematic measurement method, experiments using X-ray fluoroscopic images of four TKA patients during knee motions were performed. In order to assess the performance of the improved method, automation rate was calculated, and the rate was defined as the X-ray frame number of satisfying clinical required accuracy (error within 1mm, 1 degree) relative to all X-ray frame number. As results of the experiments, 3D pose of the model for all X-ray images except for the first frame is automatically stably-estimated, the automation rate of the femoral and tibial component were 83.7 % and 73.5 %, respectively. The improved method doesn't need labor-intensive manual operations for 3D kinematic measurement of TKA, and is thought to be very helpful for actual clinical practice.
Patella resection has been the least controlled element of total knee arthroplasty (TKA). We have developed an intraoperative guide system involving a custom-made surgical template designed on the basis of a three-dimensional computer simulation incorporating computed tomography (CT) data for several years. This time we have applied this intraoperative guide system for the patella resection in TKA. We investigated the accuracy of CT-based patient-specific templating (PST) for patella resection using cadaveric knee joints in vitro. To plan the corrective patella resection, we attempted to simulate a three-dimensional patella resection with the use of computer models of the patella. From CT images of the patella we obtained three-dimensional surface models of the patella by performing a three-dimensional surface generation of the bone cortex. After the patella resection using CT-based custom-made surgical templating instrumentation, CT scan was performed again and we compared the patella shape in three-dimensional patella bone model reconstructed from pre and after cut from CT data. We compared the accuracy of patella cut using three-dimensional patella bone model reconstructed from pre and after cut from CT data. Statistical analysis was performed using paired t test. The difference between patella cut with CT-based custom-made surgical templating instrumentation and pre-operative planning were 0.8±1.2mm (medial side) and 0.1±1.4mm (lateral side). More than 60% resulted within 2mm from the pre-operative planning. There were significant differences both in flexion/extension, external/internal rotation and bone cut depth between CT-based custom-made surgical templating instrumentation and conventional instrument. The results in this study demonstrated the usefulness of CT-based custom-made surgical templating instrumentation for patella resection in TKA.
To materialize 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques, which use X-ray fluoroscopic images and the knee implants CAD, have been applied to clinical cases. However, most conventional methods have needed time-consuming and labor-intensive manual operations in some process. In previous study, we addressed a manual operations problem when setting initial pose of implants model for 2D/3D registration, and reported a semi-automated initial pose estimation method based on an interpolation technique. However, this method still required appropriate initial pose estimation of the model with manual operations for some X-ray images (key frames). Additionally, in the situation like fast knee motion and use of low frame rate, good registration results were not obtained because of the large displacement between each frame silhouette. To overcome these problems, this study proposes an improved semi-automated 3D kinematic estimation method. Our 2D/3D registration technique is based on a robust feature-based algorithm. In improved initial pose estimation method, for the only first frame, the initial pose is manually adjusted as close as possible. That is, we automatically estimate appropriate initial pose of the model for X-ray images except for the first frame. To automatically estimate the initial pose of the model, we utilize a transformation with feature points extracted from the previous and next frames. A transform matrix which has three DOF (translations parallel to the image, and a rotation perpendicular to the image) is calculated by registration of corresponding feature points between the previous and next frame extracted with SURF algorithm. While, the corresponding point sets extracted by SURF sometimes include some error sets. Therefore, in this study, LmedS method was employed to detect the error corresponding sets and calculate a transform matrix accurately. In Fig. 1(a) and (b), the orange square shows the region defined with the boundary box of the model, and some lines show the combined corresponding point sets. The blue lines are correct corresponding point sets, and the pink lines are error corresponding point sets detected with LmedS method. Finally, 3D pose of the model estimated in previous frame is transformed with accurately calculated transform matrix, and the transformed pose is used as an initial 3D pose of the model in next frame.Purpose:
Methods:
The decision to choose CR (cruciate retaining) insert or CS (condylar stabilized) insert during TKA remains a controversial issue. Triathlon CS type has a condylar stabilized insert with an increased anterior lip that can be used in cases where the PCL is sacrificed but a PS insert is not used. The difference of the knee kinematics remains unclear. This study measured knee kinematics of deep knee flexion under load in two insert designs using 2D/3D registration technique. Five fresh-frozen cadaver lower extremity specimens were surgically implanted with Triathlon CR components (Stryker Orthopedics, Mahwah, NJ). CR insert with retaining posterior cruciate ligament were measured firstly, and then CS insert after sacrificing posterior cruciate ligament were measured. Under fluoroscopic surveillance, the knees were mounted in a dynamic quadriceps-driven closed-kinetic chain knee simulator based on the Oxford knee rig design. The data of every 10° knee flexion between 0° and 140° were corrected. Femorotibial motion including tibial polyethylene insert were analyzed using 2D/3D registration technique, which uses computer-assisted design (CAD) models to reproduce the spatial position of the femoral, tibial components from single-view fluoroscopic images. We evaluated the knee flexion angle, femoral axial rotation, and anteroposterior translation of contact points.Background
Materials and methods
For 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques which use X-ray fluoroscopic images and computer-aided design model of the knee implants, have been applied to clinical cases. These techniques are highly valuable for dynamic 3D kinematic analysis, but have needed time-consuming and labor-intensive manual operations in some process. In previous study, we reported a robust method to reduce manual operations to remove spurious edges and noises in edge detection process of X-ray images. In this study, we address another manual operations problem occurred when setting initial pose of TKA implants model for 2D/3D registration. To set appropriate initial pose of the model with manual operations for each X-ray image is important to obtain the good registration results. However, the number of X-ray images for a knee performance is very large, and thus to set initial pose with manual operations is very time-consuming and a problem for practical clinical applications. Therefore, this study proposes an initial pose estimation method for automated 3D kinematic analysis of TKA. 3D pose of an implant model is estimated using a 2D/3D registration technique based on a robust feature-based algorithm. To reduce labor-intensive manual operations of initial pose setting for large number of X-ray images, we utilize an interpolation technique with an approximate function. First, for some X-ray images (key frames), initial poses are manually adjusted to be as close as possible, and 3D poses of the model are accurately estimated for each key frame. These key frames were appropriately selected from the 2D feature point of knee motion in the X-ray images. Next, the 3D pose data estimated for each key frame are interpolated with an approximate function. In this study, we employed a multilevel B-spline function. Thus, we semi-automatically estimate the initial 3D pose of the implant model in X-ray images except for key frames. Fig. 1 shows the algorithm of initial pose estimation, and Fig. 2 shows the scheme of the data interpolation with an approximate function.Purpose
Methods
Regarding TKA, patient specific cutting guides (PSCG), which have the same fitting surface with patient's bones or cartilages and uniquely specify the resection plane by fitting guides with bones, have been developed to assist easy, low cost and accurate surgery. They have already been used clinically in Europe and the USA. However little has been reported on clinical positioning accuracy of PSCG. Generally, the methods of making PSCG can be divided into 3 methods; construct 3D bone models with Magnetic Resonance (MR) images, construct 3D bone models with Computed Tomography (CT) images, and the last is to construct 3D bone models with both MR and CT images. In the present study, PSCG were made based on 3D bone models with CT images, examined the positioning accuracy with fresh-frozen cadavers. Two fresh-frozen cadavers with four knees were scanned by CT. Image processing software for 3D design (Mimics Ver. 14, Marialise Inc.) was used to construct 3D bone model by image thresholding. We designed femoral cutting guides and tibial cutting guides by CAD software (NX 5.0, Siemens PLM Software Co.). CT free navigation system (VectorVision Knee, BrainLab, Inc.) was used to measure positioning error. Average absolute value of positioning error for each PSCG was derived.Introduction
Materials and Methods
Various postoperative evaluations using fluoroscopy have reported in vivo knee flexion kinematics under weight bearing conditions. This method has been used to investigate which design features are more important for restoring normal knee function. The objective of this study is to evaluate the kinematics of a Low Contact Stress total knee arthroplasty (LCS TKA) in weight bearing deep knee flexion using 2D/3D registration technique. We investigated the in vivo knee kinematics of 6 knees (4 patients) implanted with the LCS meniscal bearing TKA (LCS Mobile-Bearing Knee System, Depuy, Warsaw, IN). Mean period between operation and surveillance was 170.7±14.2 months. Under fluoroscopic surveillance, each patient did a deep knee flexion under weight-bearing condition. Femorotibial motion was analyzed using 2D/3D registration technique, which uses computer-assisted design (CAD) models to reproduce the spatial position of the femoral, tibial components from single-view fluoroscopic images. We evaluated the knee flexion angle, femoral axial rotation, and antero-posterior translation of contact positions.Background
Patients and methods
The outcome after total knee arthroplasty is influenced by the postoperative orientation of the component. For accurate implantation, the surgeon performs a three dimensional preoperative planning and performs the surgery with reference to the anatomical bony landmarks. However, the assessment of orientation after TKA is generally performed on two dimensional radiographs. Despite the accurate implantation, radiographic assessment may not able to accurately evaluate the orientation of the component. CT images obtain a three dimensional information after TKA, but reliable identification of the anatomical bony landmarks remains the problem due to artifacts of metal components. In this study, we evaluate the three dimensional orientation of the component relative to the bone axis of anatomical landmarks using pre- and post-operative CT scanning. Two knees after primary TKA were assessed by one observer using preoperative and postoperative CT images. 3D models of pre-operative bone and post-operative bone with the exclusion of component data were constructed. Surface-based registration was performed by independently implementing the iterative closest point algorithm with the least-squares method to match the pre-operative bone model with the post-operative bone model. 3D surface model of the metal component from postoperative CT images was constructed. 3D surface model of the metal component was superimposed on original computer-aided design (CAD) data of the component using surface-based registration. The registration of the metal component was performed three times. Intra-observer reliability of the superimposed CAD models was evaluated. The orientation of the component was measured in INTRODUCTION
PATIENTS AND METHODS
The in vivo kinematics of squatting after total hip arthroplasty (THA) has remained unclear. The purpose of the present study was to elucidate range of motion (ROM) of the hip joint and the incidence of prosthetic impingement during heels-down squatting after THA. 23 primary cementless THAs using a computed tomography-based navigation system (CT-HIP, Stryker Navigation, Freiberg, Germany) were investigated using fluoroscopy. An acetabular component with concavities around the rim (TriAD HA PSL, Stryker Orthopaedics, Mahwah, NJ) and a femoral component with reduced neck geometry (CentPiller, Stryker Orthopaedics), which provided a large oscillation angle, were used. The femoral head size was 28mm (8 hips), 32mm (10 hips), and 36mm (5 hips). Post-operative analysis was performed within 6 months in 6 hips, and at 6 months to 2 years in 17 hips. Successive hip motion during heels-down squatting was recorded as serial digital radiographic images in a DICOM format using a flat panel detector. The coordinate system of the acetabular and femoral components based on the neutral standing position was defined. The images of the hip joint were matched to three-dimensional computer aided design models of the acetabular and femoral components using a two-dimensional to three-dimensional (2D/3D) registration technique. In the previous computer simulation study of THA, the root mean square errors of rotation was less than 1.3°, and that of translation was less than 2.3 mm. We estimated changes in the relative angle of the femoral component to the acetabular component, which represented the hip ROM, and investigated the incidence of prosthetic impingement during squatting. We also estimated changes in the flexion angle of the acetabular component, which represented the pelvic posterior tilting angle (PA), and the flexion angle of the femoral component, which represented the femoral flexion angle (FA). The contribution of the PA to the FA at maximum squatting was evaluated as the pelvic posterior tilting ratio (PA/FA). In addition, when both components were positioned most closely during squatting, we estimated the minimum angle (MA) up to theoretical prosthetic impingement. No prosthetic impingement occurred in any hips. The maximum hip flexion ROM was mean 92.7° (SD; 15.7°, range; 55.1°–119.1°) and was not always consisted with the maximum squatting. The maximum pelvic posterior tilting angle (PA) was mean 27.3° (SD; 11.0°, range; 5.5°–46.5°). The pelvis began to tilt posteriorly at 50°–70° of the hip flexion ROM. The maximum femoral flexion angle (FA) was mean 118.9° (SD; 10.4°, range; 86.4°–136.7°). At the maximum squatting, the ratio of the pelvic posterior tilting angle to the femoral flexion angle (pelvic posterior tilting ratio, PA/FA) was mean 22.9% (SD; 10.4%, range; 3.8%–45.7%). The minimum angle up to the theoretical prosthetic impingement was mean 22.7° (SD; 7.5°, range; 10.0°–37.9°). The maximum hip flexion of ROM in 36 mm head cases was larger than that in 32 mm or 28 mm head cases, while the minimum angle up to the prosthetic impingement in 36 mm head cases was also larger than that in 32 mm or 28 mm head cases. Three-dimensional assessment of dynamic squatting motion after THA using the 2D/3D registration technique enabled us to elucidate hip ROM, and to assess the prosthetic impingement, the contribution of the pelvic posterior tilting, and the minimum angle up to theoretical prosthetic impingement during squatting.
To achieve 3D kinematic analysis of total knee arthroplasty (TKA), 2D/3D registration techniques, which use X-ray fluoroscopic images and computer-aided design model of the knee implants, have been applied to clinical cases. In previous feature-based registration methods, only edge contours originated from knee implants are assumed to be extracted from X-ray images before 2D/3D registration. Due to the influence of bone and bone-cement close to knee implants, however, edge detection methods extract unwanted spurious edges and noises in clinical images. Thus, time-consuming and labor-intensive manual operations are often necessary to remove the unwanted edges. It has been a serious problem for clinical applications, and there is a strong demand for development of improved method. The purpose of this study was to develop a pose estimation method to perform accurate 2D/3D registration even if spurious edges and noises exist in knee images. Our 2D/3D registration technique is based on a feature-based algorithm, and contour points from X-ray images are extracted by Gaussian Laplacian filter and zero crossing methods. The basic principle of the algorithm is that the 3D pose of a model can be determined by projecting rays from contour points in an image back to the X-ray focus and noting that all of these rays are tangential to the model surface. Therefore, 3D poses are estimated by minimizing the sum of Euclidean distances between all projected rays and the model surface. Additionally, we introduce robust statistics into the 3D pose estimation method to perform accurate 2D/3D registration even if spurious edges and noises exist in knee images. The robust estimation method employs weight functions to reduce the influence of spurious edges and noises. The weight functions are defined for each contour point, and optimization is performed after the weight functions are multiplied to a cost function.Purpose
Methods
Various postoperative evaluations using fluoroscopy have reported in vivo knee flexion kinematics under weight bearing conditions. This method has been used to investigate which design features are more important for restoring normal knee function. The objective of this study is to evaluate the kinematics of a Posterior-Stabilized TKA in weight bearing deep knee flexion using 2D/3D registration technique. We investigated the in vivo knee kinematics of 9 knees (9 patients) implanted with a Posterior Stabilized TKA (Triathlon PS, Stlyker Orthopedics, Mahwah, NJ). Under fluoroscopic surveillance, each patient did a deep knee flexion under weight-bearing condition. Femorotibial motion including tibial polyethylene insert were analyzed using 2D/3D registration technique, which uses computer-assisted design (CAD) models to reproduce the spatial position of the femoral, tibial components from single-view fluoroscopic images. We evaluated the knee flexion angle, femoral axial rotation, antero-posterior translation of contact points, and post-cam engagement were evaluated.Background
Patients and methods
It is widely accepted that navigation system for TKA improves precision in component alignment. Furthermore, some of the system can measure knee kinematics during surgery. On the other hand, the measurements of kinematics during surgery have limitations because of anesthesia and usage of air tourniquet. The purpose of the present study is to compare the knee kinematics during surgery using navigation system and that after surgery using 2D/3D Registration Technique. Our final goal of the study is to improve clinical outcome by performing feedback of good clinical results to operating theater by means of kinematic analysis. Kinematics of ten TKA knees for female (average age 71 years old) medial compartmental osteoarthritic knees concerning axial rotation and anterior-posterior translation were measured twice, the time during surgery and 4 weeks after surgery. During surgery, measurement was performed using CT based navigation system (Vector Vision 1.6, Brain LAB, Heimstetten, Germany). Four weeks after surgery, knee kinematics was measured again using a 2-dimensional to 3-dimensional registration technique, which used computer-assisted design models to reproduce the position of metallic implants from single-view fluoroscopic images. Surgery was performed by single surgeon using subvastus approach to eliminate the influence of approach to muscle balance. Implant using the present study was P.F.C. Sigma RP-F (DePuy, Warsaw, USA). Axial rotation in navigation and 2D/3D are 12.3+/−2.3, and 12.6+/−3.8, respectively. Axial rotations in both of the measurement have the same pattern. A-P translations also have the same pattern between measurement in navigation and that in 2D/3D technique. These results suggested that intraoperative kinematic measurement links to postoperative kinematics. Studies of correlations between kinematics and good clinical results are ongoing.
Mobile-bearing (MB) total knee prostheses have been developed to achieve lower contact stress and higher conformity compared to fixed-bearing total knee prostheses. However, little is known about the in vivo kinematics of MB prostheses especially the motion of the polyethylene insert (PE) during various daily performances. And the in vivo motion of the PE during stairs up and down has not been clarified. The objective of this study is to clarify the in vivo motion of MB total knee arthroplasty including the PE during stairs up and down. We investigated the in vivo knee kinematics of 11 knees (10 patients) implanted with PFC-Sigma RP-F (DePuy). Under fluoroscopic surveillance, each patient did stairs up and down motion. And motion between each component was analyzed using two- to three-dimensional registration technique, which used computer-assisted design (CAD) models to reproduce the spatial position of the femoral, tibial components, and PE (implanted with four tantalum beads intra-operatively) from single-view fluoroscopic images. We evaluated the range of motion between the femoral and tibial components during being grounded, axial rotation between the femoral component and PE, the femoral and tibial component, and the PE and tibial component during being grounded.Background
Patients and methods
Mobile-bearing (MB) total knee prostheses have been developed to achieve lower contact stress and higher conformity compared to fixed-bearing total knee prostheses. However, little is known about the in vivo kinematics of MB prostheses especially about the kinematics of polyethylene insert (PE). In vivo motion of PE during squatting still remains unclear. The objective of this study is to investigate the in vivo motion of MB total knee arthroplasty including PE during squatting. We investigated the in vivo knee kinematics of 11 knees (10 patients) implanted with Vanguard Rotationg Platform High Flex (Biomet(r)). Under fluoroscopic surveillance, each patient did a wight-bearing deep knee bending motion. Motion between each component was analyzed using two- to three-dimensional registration technique, which uses computer-assisted design (CAD) models to reproduce the spatial position of the femoral, tibial components, and PE (implanted with five tantalum beads intra-operatively) from single-view fluoroscopic images. We evaluated the range of motion between the femoral and tibial components, axial rotation between the femoral component and PE, the femoral and tibial component, and the PE and tibial component, and AP translation of the nearest point between the femoral and tibial component and between the femoral component and PE.Background
Patients and methods
