The restoration of physiological kinematics is one of the goals of a total knee arthroplasty (TKA). Navigation systems have been developed to allow an accurate and precise placement of the implants. But its application to the intraoperative measurement of knee kinematics has not been validated. The hypothesis of this study was that the measurement of the knee axis, femoral rotation, femoral translation with respect to the tibia, and medial and lateral femorotibial gaps during continuous passive knee flexion by the navigation system would be different from that by fluoroscopy taken as reference. Five pairs of knees of preserved specimens were used. The e.Motion FP ® TKA (B-Braun Aesculap, Tuttlingen, Germany) was implanted using the OrthoPilot TKA 4.3 version and Kobe version navigation system (B-Braun Aesculap, Tuttlingen, Germany). Kinematic recording by the navigation system was performed simultaneously with fluoroscopic recording during a continuous passive flexion-extension movement of the prosthetic knee. Kinematic parameters were extracted from the fluoroscopic recordings by image processing using JointTrack Auto ® software (University of Florida, Gainesville, USA). The main criteria were the axis of the knee measured by the angle between the center of the femoral head, the center of the knee and the center of the ankle (HKA), femoral rotation, femoral translation with respect to the tibia, and medial and lateral femorotibial gaps. The data analysis was performed by a Kappa correlation test. The agreement of the measurements was assessed using the intraclass correlation coefficient (ICC) and its 95% confidence interval.INTRODUCTION
MATERIAL – METHODS
Sensor technology is seeing increased utility in joint arthroplasty, guiding surgeons in assessing the soft tissue envelope intra-operatively (OrthoSensor, FL, USA). Meanwhile, surgical navigation systems are also transforming, with the recent introduction of inertial measurement unit (IMU) based systems no longer requiring optical trackers and infrared camera systems in the operating room (i.e. OrthAlign, CA, USA). Both approaches have now been combined by embedding an IMU into an intercompartmental load sensor. As a result, the alignment of the tibial varus/valgus cut is now measured concurrently with the mediolateral tibiofemoral contact load magnitudes and locations. The wireless sensor is geometrically identical to the tibial insert trial and is placed on the tibial cutting plane after completing the proximal tibial cut. Subsequently, the knee is moved through a simple calibration maneuver, rotating the tibia around the heel. As a result, the sensor provides a direct assessment of the obtained tibial varus/valgus alignment. This study presents the validation of this measurement. In an in-vitro setting, sensor-based alignment measurements were repeated for several simulated conditions. First, the tibia was cut in near-neutral alignment as guided by a traditional, marker-based surgical navigation system (Stryker, MI, USA). Subsequently, the sensor was inserted and a minimum of five repeated sensor measurements were performed. Following these measurements, a 3D printed shim was inserted between the sensor and the tibial cutting plane, introducing an additional 2 or 4 degrees of varus or valgus, with the measurements then being repeated. Again, for each condition, a minimum of five sensor measurements were performed. Following completion of the tests, a computed tomography (CT) scan of the tibia was obtained and reconstructed using open source software (3DSlicer).Introduction and Aims
Method
There have been many attempts to define the criteria by which prosthetic joint infection (PJI) is diagnosed. Our aim is to validate the 2021 European Bone and Joint Infection Society (EBJIS) definition of PJI. This is a multicenter retrospective study of patients who have undergone total hip or knee revision surgery in four different European institutions between 2013–2018. Cases with less than four intraoperative microbiology samples; no preoperative/intraoperative synovial fluid differential leukocyte count or intraoperative histology were excluded. Minimum follow-up of at least two years after revision surgery if no subsequent infection and/or the need for implant removal was also required. All cases were classified using the 2021 EBJIS, the 2018 International Consensus Meeting (ICM) and the 2013 Musculoskeletal Infection Society (MSIS) PJI definitions.Aim
Method
In clinical routine surgeons depend largely on 2D x-ray radiographs and their experience to plan and evaluate surgical interventions around the knee joint. Numerous studies have shown that pure 2D x-ray radiography based measurements are not accurate due to the error in determining accurate radiography magnification and the projection characteristics of 2D radiographs. Using 2D x-ray radiographs to plan 3D knee joint surgery may lead to component misalignment in Total Knee Arthroplasty (TKA) or to over- or under-correction of the mechanical axis in Lower Extremity Osteotomy (LEO). Recently we developed a personalized X-ray reconstruction-based planning and post-operative treatment evaluation system called “iLeg” for TKA or LEO. Based on a patented X-ray image calibration cage and a unique 2D–3D reconstruction technique, iLeg can generate accurate patient-specific 3D models of a complete lower extremity from two standing X-rays for true 3D planning and evaluation of surgical interventions at the knee joint. The goal of this study is to validate the accuracy of this newly developed system using digitally reconstructed radiographs (DRRs) generated from CT data of cadavers. CT data of 12 cadavers (24 legs) were used in the study. For each leg, two DRRs, one from the antero-posterior (AP) direction and the other from the later-medial (LM) direction, were generated following clinical requirements and used as the input to the iLeg software. The 2D–3D reconstruction was then done by non-rigidly matching statistical shape models (SSMs) of both femur and tibia to the DRRs (seee Fig. 1). In order to evaluate the 2D–3D reconstruction accuracy, we conducted a semi-automatic segmentation of all CT data using the commercial software Amira (FEI Corporate, Oregon, USA). The reconstructed surface models of each leg were then compared with the surface models segmented from the associated CT data. Since the DRRs were generated from the associated CT data, the surface models were reconstructed in the local coordinate system of the CT data. Thus, we can directly compare the reconstructed surface models with the surface models segmented from the associated CT data, which we took as the ground truth. Again, we used the software Amira to compute distances from each vertex on the reconstructed surface models to the associated ground truth models.Introduction
Methods
Recently we developed a personalised X-ray reconstruction-based planning and post-operative treatment evaluation system called iLeg for total knee arthroplasty or lower extremity osteotomy. Based on a patented X-ray image calibration cage and a unique 2D-3D reconstruction technique, iLeg can generate accurate patient-specific 3D models of a complete lower extremity from two standing X-rays for true 3D planning and evaluation of surgical interventions at the knee joint. The goal of this study is to validate the accuracy of this newly developed system using digitally reconstructed radiographs (DRRs) generated from CT data of 12 cadavers (24 legs). Our experimental results demonstrated an overall reconstruction accuracy of 1.3±0.2mm.
Correct placement of the acetabular cup is a crucial step in hip replacement to achieve a satisfactory result and remains a challenge with free hand techniques. Imageless navigation may provide a viable alternative to freehand technique and improve placement significantly. The purpose of this project was to assess and validate intra-operative placement values as displayed by an imageless navigation system to postoperative measurement of cup position using high resolution CT scans. Thirty-two subjects who underwent primary hip joint arthroplasty using imageless navigation were included. The average age was 66.5 years (range 32–87). 23 non-cemented and 9 cemented acetabular cups were implanted. The desired position for the cup was 45 degrees of inversion and 15 degrees of anteversion. A pelvic CT scan using a multi-slice CT was used to assess the position of the cup radiographically.Purpose:
Methods:
Bony deformities in the hip that cause femoroacetabular impingement (FAI) can be resected in order to delay the onset of osteoarthritis and improve hip range of motion. However, achieving accurate osteoplasty arthroscopically is challenging because the narrow hip joint capsule limits field of view. Recently, image-based navigation using a preoperative plan has been shown to improve the accuracy of femoral bone surfaces following arthroscopic osteoplasty for FAI. The current standard for intraoperative monitoring, 3D x-ray fluoroscopy, is accurate at the initial registration step to within 0.8±0.5mm but involves radiation. Intraoperative 3D ultrasound (US) is a promising radiation-free alternative for providing real-time visual feedback during FAI osteoplasty. The objective was to determine if intraoperative 3D US of the femoral head/neck region can be registered to a CT-based preoperative plan with comparable accuracy to fluoroscopic navigation in order to visualise progress during arthroscopic FAI osteoplasty. The experiment used a plastic femur model that had a cam deformity on the femoral head/neck. Thirty metal fiducial markers were placed on the US-accessible anterior and lateral surfaces of the femur. A CT image was acquired and reconstructed, then used to develop a preoperative plan for resection of the cam deformity. Twenty-two sets of 3D US data were then gathered from the phantom using a clinical ultrasound machine and 3D transducer while the phantom was submerged in water. US surfaces from the anterior/lateral regions of the femur were extracted using a recently proposed image processing algorithm. Fiducials in the US volume were manually registered to corresponding CT fiducials to provide a reference standard registration. The reference standard fiducial registration error (FRE) was measured as the average distance between corresponding fiducials. After fiducial-based registration, each US surface was randomly misaligned and re-registered using a coherent point-drift algorithm. The resulting surface registration error (SRE) was measured using average distance between US and CT surfaces. Finally, a plastic model of the preoperative cam deformity resection plan was 3D-printed to represent the postoperative femur. Five US scans were acquired of the postoperative model near the femoral head/neck. Each US scan was initialised for 20 trials using three reference points, and then registered using coherent point drift. Surgical outcome accuracy was reported using final surface registration error (fSRE).Introduction
Methods
Studies show that cup malpositioning using conventional techniques occurs in 50 to 74% of cases defined. Assessment of the utility of improved methods of placing acetabular components depends upon the accuracy of the method of measuring component positioning postoperatively. The current study reports on our preliminary experience assessing the accuracy of EOS images and application specific software to assess cup orientation as compared to CT. Eighteen patients with eighteen unilateral THA had pre-operative EOS images were obtained for preoperative assessment of leg-length difference and standing pelvic tilt. All of these patients also had preoperative CT imaging for surgical navigation of cup placement. This allows us to compare cup orientation as measured by CT to cup orientation as measured using the EOS images. Application specific software modules were developed to measure cup orientation using both CT and EOS images (HipSextant Research Application 1.0.13 Surgical Planning Associates Inc., Boston, Massachusetts). Using CT, cup orientation was determined by identifying Anterior Pelvic Plane coordinate system landmarks on a 3D surface model. A multiplanar reconstruction module allows for creation of a plane parallel with the opening plane of the acetabulum and subsequent calculation of plane orientation in the AP Plane coordinate space according to Murray's definitions of operative anteversion and operative inclination. Using EOS DICOM images, spatial information from the images were used to reconstruct the fan beam projection model. Each image pair is positioned inside this projection model. Anterior Pelvic Plane coordinate points are digitized on each image and back-projected to the fan beam source. Corresponding beams are then used to compute the 3D intersection points defining the 3D position and orientation of the Anterior Pelvic Plane. Ellipses with adjustable radii were then used to define the cup border in each EOS image. By respecting the fan beam projection model, 3D planes defining the projected normal of the ellipse in each image are computed. 3D implant normal was estimated by determining 3D plane intersection lines for each image pair. Implant center points are defined by using the back-projected and intersected ellipse center beams in the image pairs (Figure 1).Introduction
Methods
