Our aim was to investigate whether it is possible to predict post-operative kinematics (Post-Ope) from intra-operative kinematics (Intra-Ope) after total knee arthroplasty. Our study were performed for 11 patients (14 knees) who underwent primary PS TKA using CT-based navigation system between Sept.2012 and Sept.2014. The mean subject age was 71.5 ± 5.5 years at the time of surgery. Intra-Ope was measured using the navigation system after implantation during passive full extension and flexion imposed by the surgeon. Under fluoroscopic surveillance, each patient was asked to perform sequential deep knee flexion under both non-weight bearing (NWB) and weight bearing (WB) conditions from full extension to maximum flexion. To estimate the spatial position and orientation, we used a 2- to 3- dimensional (2D3D) registration technique. Intra-Ope and Post-Ope had a common coordinate axis for bones. Evaluations were range of motion (ROM), external rotation angles (ER). The level of statistical significant difference was set at 0.05. Mean ROM in Intra-Ope(130°± 7.9°) was statistically larger than both NWB(121.1°±10.5°) and WB(124.0°±14.7°). No Statistically significant difference was found in the mean ER from 10° to 120° among Intra-Ope (11.2°± 8.5°) and NWB(7.1°±6.0°) and WB(5.3°±3.2°). It is suggested that we could predict Post-Ope from Intra-Ope by considering the increase of the range of motion due to the muscle relaxation condition and the amount of change in the ER.
Bi-cruciate stabilized (BCS) TKA is the prosthesis that aims to substitute bi-cruciate ligament with post-cam engagement. We estimated to describe the
There are few studies that have compared between continuous flexion activities and extension activities of normal knees. The purpose of this study is to compare
This study was to investigate the effect of posterior tibial slope (PTS) on the kinematics in the cruciate-retaining total knee arthroplasty (CR-TKA) using 2- to 3- dimensional registration technique. A total of 75 knees in 58 patients were recruited and categorized into the following two groups according to PTS. Group A was categorized PTS under 7degrees (n = 33) and group B was categorized PTS over 7 degrees (n = 42). The average age of group A and group B at the time of fluoroscopic surveillance date was 73.5 ± 7.4 years and 74.3 ± 4.5 years, respectively and the average follow-up period from operation date to fluoroscopic surveillance date was 13.8 ± 9.3 months and 16.7 ± 8.6 months, respectively. In vivo kinematics during sequential deep knee bending under weight-bearing condition were evaluated using fluoroscopic image analysis and 2- to 3- dimensional registration technique. Range of motion (ROM), axial rotation, anteroposterior (AP) translations of medial and lateral nearest points of the femoral component relative to the tibial component were measured and compared between the two groups. The nearest points were determined by calculating the closest distance between the surfaces of femoral component model and the axial plane of coordinate system of the tibial component. We defined external rotation and anterior translation as positive. P values under 0.05 was defined as statistically significant.Purpose
Material & Methods
In Asia and the Middle-East, people often flex their knees deeply
in order to perform activities of daily living. The purpose of this
study was to investigate the 3D kinematics of normal knees during
high-flexion activities. Our hypothesis was that the femorotibial
rotation, varus-valgus angle, translations, and kinematic pathway
of normal knees during high-flexion activities, varied according
to activity. We investigated the Aims
Materials and Methods
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
We hypothesized that using the navigation system, intra-operative knee kinematics after implantation measured may predict that post-operative kinematic in activities of daily living. Our aim was to compare intra-operative knee kinematics by a computed tomography (CT)-based navigation system and post-operative by the 2- to 3-dimensional registration techniques (2D3D). This study were performed for 8 patients (10 knees, medial osteoarthritis) who underwent primary PS TKA using CT-based navigation system. The median follow-up period from operation date to fluoroscopic surveillance date was 13 months (range 5 – 37 months). Navigation and 2D3D had a common coordinate origin for components. Medial and lateral femoral condyle anterior-posterior translation (MFT and LFT) were respectively defined as the distance of the projection of the points (which was set on the top of the posterior femoral pegs) onto the axial plane of the tibial coordinate system. Intraoperative kinematics was measured using the navigation system after final implantation and closure of the retinaculum during passive full flexion and extension imposed by the surgeon. Under fluoroscopic surveillance in the sagittal plane, each patient was asked to perform sequential deep knee flexion under both weight bearing (WB) and non-weight bearing (NWB) conditions from full extension to maximum flexion. Repeated two-way ANOVA (tasks × flexion angles) were used, and then post-hoc test (paired t-tests with Boferroni correction) were performed. The level of statistical significant difference was set at 0.05 on two-way ANOVAs and 0.05 / 3 on post-hoc paired t-tests. Mean range of motion between femoral and tibial components were Intra-operative (Intra): 28.0 ± 9.7, NWB conditions: 120.6 ± 11.1, WB conditions: 125.1 ± 12.9°, respectively. Mean ER (+) / IR (−) from 0° to 120° were Intra-operative (Intra): 9.3 ± 10.2°, NWB conditions: 8.1 ± 8.9, WB conditions: 5.2 ± 7.0, respectively. Mean MFT /LFT from 0° to 90° were Intra; 4.4 ±14.8/ 4.2± 8.5mm, NWB; 6.2 ± 6.9 / 9.2 ± 3.1 mm, WB; 9.2 ± 3.5 / 7.4 ± 2.8 mm, respectively. Mean MFT /LFT from 90° to 120° were Intra; −4.4 ± 2.5 / −5.7 ± 2.9 mm, NWB; −5.5 ± 1.8 / −8.2 ± 0.6 mm, WB; −4.0 ± 1.9 / −5.4 ± 2.3mm, respectively. Mean ADD/ABD from 0° to 120° were Intra;-4.2 ± 3.0, NWB; −0.2 ± 2.1, WB; −0.1 ± 0.8, respectively. Repeated two-way ANOVA showed a significant all interaction on kinematic variables (p<0.05). No statistically significant difference at post-hoc test was found in ER/ IR of all tasks and MFT /LFT of Intra vs NWB and Intra vs WB from 0° to 120° (p>0.05 / 3). The Conditions of these tasks were different from each others. Our study demonstrated that intra-operative kinematics could predict post-operative kinematics.
The purpose of this study is to investigate the three-dimensional (3D) kinematics of normal knees in deep knee-bending motions like squatting and kneeling. Material & Methods: We investigated the in vivo kinematics of 4 Japanese healthy male volunteers (8 normal knees in squatting, 7 normal knees in kneeling). Each sequential motion was performed under fluoroscopic surveillance in the sagittal plane. Femorotibial motion was analyzed using 2D/3D registration technique, which uses computer-assisted design (CAD) models to reproduce the spatial position of the femur and tibia from single-view fluoroscopic images. We evaluated the femoral rotation relative to the tibia and anteroposterior (AP) translation of the femoral sulcus and lateral epicondyle on the plane perpendicular to the tibial mechanical axis. Student's t test was used to analyze differences in the absolute value of axial rotation and AP translation of the femoral sulcus and lateral epicondyle during squatting and kneeling. Values of P < 0.05 were considered statistically significant. During squatting, knees were gradually flexed from −2.8 ± 1.3° to 145.5 ± 5.1° on average. Knees were gradually flexed from 100.8 ± 3.9° to 155.6 ± 3.2° on average during kneeling. Femurs during squatting displayed sharp external rotation relative to the tibia from 0° to 30° of flexion and it reached 12.5 ± 3.3° on average. From 30° to 130° of flexion, the femoral external rotation showed gradually, and it reached 19.1 ± 7.3° on average. From 130° to 140° of flexion, it was observed additionally, and reached 22.4 ± 6.1° on average. All kneeling knees displayed femoral external rotation relative to the tibia sharply from 100° to 150° of flexion, and it reached 20.7 ± 7.5° on average. From 100° to 120° of flexion, the femoral external rotation during squatting was larger than that during kneeling significantly. From 120° to 140° of flexion, there was no significant difference between squatting and kneeling. The sulcus during squatting moved 4.1 ± 4.8 mm anterior from 0° to 60° of flexion. From 60° of flexion it moved 13.6 ± 13.4 mm posterior. The sulcus during kneeling was not indicated significant movement with the knee flexion. The lateral epicondyle during squatting moved 39.4 ± 7.7 mm posterior from 0° to 140° of flexion. The lateral epicondyle during kneeling moved 22.0 ± 5.4 mm posterior movement from 100° to 150° of flexion. In AP translation of the sulcus from 100° to 140° of flexion, there was no significant difference between squatting and kneeling. However in that of the lateral epicondyle, squatting groups moved posterior significantly. Even if they were same deep knee-bending, the kinematics were different because of the differences of daily motions. The results in this study demonstrated that in vivo kinematics of deep knee-bending were different between squatting and kneeling.
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.
The effect of the geometry of the tibial polyethylene insert was investigated in vivo loaded conditions. The decision to choose CR (cruciate retaining) insert or CS (condylar stabilised) insert during TKA remains a controversial issue. Triathlon CS type has a condylar stabilised 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 between CR and CS insert remains unclear. This study measured knee kinematics of deep knee flexion under load in two insert designs using 2D/3D registration technique.Summary
Introduction
We retrospectively assessed the value of identifying
impinging osteophytes using dynamic computer simulation of CT scans
of the elbow in assisting their arthroscopic removal in patients
with osteoarthritis of the elbow. A total of 20 patients were treated
(19 men and one woman, mean age 38 years (19 to 55)) and followed
for a mean of 25 months (24 to 29). We located the impinging osteophytes
dynamically using computerised three-dimensional models of the elbow
based on CT data in three positions of flexion of the elbow. These
were then removed arthroscopically and a capsular release was performed. The mean loss of extension improved from 23° (10° to 45°) pre-operatively
to 9° (0° to 25°) post-operatively, and the mean flexion improved
from 121° (80° to 140°) pre-operatively to 130° (110° to 145°) post-operatively.
The mean Mayo Elbow Performance Score improved from 62 (30 to 85)
to 95 (70 to 100) post-operatively. All patients had pain in the
elbow pre-operatively which disappeared or decreased post-operatively.
According to their Mayo scores, 14 patients had an excellent clinical
outcome and six a good outcome; 15 were very satisfied and five
were satisfied with their post-operative outcome. We recommend this technique in the surgical management of patients
with osteoarthritis of the elbow. Cite this article:
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
