We aimed to assess the reliability and validity of OpenPose, a posture estimation algorithm, for measurement of knee range of motion after total knee arthroplasty (TKA), in comparison to radiography and goniometry. In this prospective observational study, we analyzed 35 primary TKAs (24 patients) for knee osteoarthritis. We measured the knee angles in flexion and extension using OpenPose, radiography, and goniometry. We assessed the test-retest reliability of each method using intraclass correlation coefficient (1,1). We evaluated the ability to estimate other measurement values from the OpenPose value using linear regression analysis. We used intraclass correlation coefficients (2,1) and Bland–Altman analyses to evaluate the agreement and error between radiography and the other measurements.Aims
Methods
Access to health care, including physiotherapy, is increasingly occurring through virtual formats. At-home adherence to physical therapy programs is often poor and few tools exist to objectively measure low back physiotherapy exercise participation without the direct supervision of a medical professional. The aim of this study was to develop and evaluate the potential for performing automatic, unsupervised video-based monitoring of at-home low back physiotherapy exercises using a single mobile phone camera. 24 healthy adult subjects performed seven exercises based on the McKenzie low back physiotherapy program while being filmed with two smartphone cameras. Joint locations were automatically extracted using an open-source
A method is proposed to assess risk parameters of anterior cruciate ligament (ACL) injury using human
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
Introduction. Real-time tracking of surgical tools has applications for assessment of surgical skill and OR workflow. Accordingly, efforts have been devoted to the development of low-cost systems that track the location of surgical tools in real-time without significant augmentation to the tools themselves. Deep learning methodologies have recently shown success in a multitude of computer vision tasks, including object detection, and thus show potential for the application of surgical tool tracking. The objective of the current study was to develop and evaluate a deep learning-based computer vision system using a single camera for the detection and
Conventional marker based optical motion capture (mocap) methods for estimating the position and orientation (pose) of anatomical segments use assumptions that anatomical segments are rigid bodies and the position of tracking markers is invariant relative to bones. Soft tissue artefact (STA) is the error in
Despite of the high success of TKA, 20% of recipients remain dissatisfied with their surgery. There is an increasing discordance in the literature on what is an optimal goal for component alignment. Furthermore, the unique patient specific anatomical characteristics will also play a role. The dynamic characteristic of a TKR is a product of the complex interaction between a patient's individual anatomical characteristics and the specific alignment of the components in that patient knee joint. These interactions can be better understood with computational models. Our objective was to characterise ligament characteristics by measuring knee joint laxity with functional radiograph and with the aid of a computational model and an optimisation study to estimate the subject specific free length of the ligaments. Pre-operative CT and functional radiographs, varus and valgus stressed X-rays assessing the collateral ligaments, were captured for 10 patients. CT scan was segmented and 3D–2D
Static radiostereometric analysis (RSA) using implanted markers is considered the most accurate system for the evaluation of prosthesis migration. By using CT bone models instead of markers, combined with a dynamic RSA system, a non-invasive measurement of joint movement is enabled. This method is more accurate than current 3D skin marker-based tracking systems. The purpose of this study was to evaluate the accuracy of the CT model method for measuring knee joint kinematics in static and dynamic RSA using the marker method as the benchmark. Bone models were created from CT scans, and tantalum beads were implanted into the tibia and femur of eight human cadaver knees. Each specimen was secured in a fixture, static and dynamic stereoradiographs were recorded, and the bone models and marker models were fitted to the stereoradiographs.Objectives
Methods
Introduction. Surgical planning for Patient Specific Instrumentation (PSI) in total knee arthroplasty (TKA) is based on static non-functional imaging (CT or MRI). Component alignment is determined prior to any assessment of clinical soft tissue laxity. This leads to surgical planning where assumptions of correctability of preoperative deformity are false and a need for intraoperative variation or abandonment of the PSI blocks occurs. The aim of this study is to determine whether functional radiology complements pre-surgical planning by identifying non-predictable patient variation in laxity. Method. Pre-operative CT's, standing radiographs and functional radiographs assessing coronal laxity at 20° flexion were collected for 20 patients. Varus/valgus laxity was assessed using the TELOS stress device (TELOS GmbH, Marburg, Germany, see Figure 1). The varus/valgus load was incrementally increased to either a maximum load of 150N or until the patient could not tolerate the discomfort. Radiographs were taken whilst the knee was held in the stressed position. CT scans were segmented and anatomical points landmarked. 2D–3D
Purpose. 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
Despite being demonstrably better than conventional surgical techniques with regards to implant alignment and outlier reduction, computer navigation systems have not faced widespread adoption in surgical operating rooms. We believe that one of the reasons for the low uptake stems from the bulky design of the optical tracker assemblies. These trackers must be rigidly fixed to a patient's bone and they occupy a significant portion of the surgical workspace, which makes them difficult to use. In this study we introduce the design for a new optical tracker system, and subsequently we evaluate the tracker's performance. The novel tracker consists of a set of low-profile flexible pins that can be placed into a rigid body and individually deflect without greatly affecting the
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
Purpose:. 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
Surgical navigation systems enable surgeons to carry out surgical interventions more accurately and less invasively, by tracking the surgical instruments inside human body with respect to the target anatomy. Currently, optical tracking (OPT) is the gold standard in surgical instrument tracking because of its sub-millimeter accuracy, but is constrained by direct line of sight (LOS) between camera sensors and active or passive markers. Electromagnetic tracking (EMT) is an alternative without the requirement of LOS, but subject to environmental ferromagnetic distortion. An intuitive idea is to integrate respective strengths of them to overcome respective weakness and we aim to develop a tightly-coupled method emphasising the interactive coupled sensor fusion from magnetic and optical tracking data. In order to get real-time position and orientation of surgical instruments in the surgical field, we developed a new tracking system, which is aiming to overcome the constraints of line-of-sight and paired-point interference in surgical environment. The primary contribution of this study is that the LOS and point correspondence problems can be mitigated using the initial measurements of EMT, and in turn the OPT result can provide initial value for non-linear iterative solver of EMT sensing module. We developed an integrated optical and electromagnetic tracker comprised of custom multiple infrared cameras, optical marker, field generator and sensing coils, because the current commercial optical or magnetic tracker typically consists of unchangeable lower level proprietary hardware and firmware. For the instrument-affixed markers, the relative pose between passive optical markers and magnetic coils is calibrated. The pose of magnetic sensing coils calculated by electromagnetic sensing module, can speed up the extraction of fiducial points and the point correspondences due to the reduced search space. Moreover, the magnetic tracking can compensate the missing information when the optical markers are temporarily occluded. For magnetic sensing subsystem comprised of 3-axis transmitters and 3-axis receiving coils, the objective function for nonlinear pose estimator is given by the summation of the square difference between the measured sensing data and theoretical data from the dipole model. Non-linear optimisation is computational intensive and requires initial
Purpose. 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
The location of the hip joint center (HJC) allows correct prosthesis aligning and positioning in Computer-Assisted Orthopaedic Surgery (CAOS) applications. For the kinematic HJC localisation, the femur is moved around the pelvis with ad hoc motion trials (“pivoting”). The “Pivoting algorithm” [Siston et al., J Biomech 39 (2006) 125–130] is the functional state-of-the-art method for the hip center localisation. A source of systematic error in HJC localisation algorithms is represented by the pelvis motion during the pivoting. In computer assisted total knee arthroplasty applications, the pelvis pose is not acquired during passive movements. In motion capture applications, Kalman Filter (KF) methodology was used to estimate the pose of hidden segment for rigid body
The verification of the alignment of the lower limb is critical for reconstructive surgery as well as trauma surgery in order to prevent osteoarthritis. The mechanical axis is a straight line defined by the center of the femoral head and the center of the ankle joint, ideally passing the knee joint in its center. Whereas the usual preoperative method to determine the mechanical axis of the lower limbs is still the long standing radiograph, common intra-operative methods are the use of an electrocautery cord or an X-ray grid consisting of wire lines underneath the patient. Both methods require the surgeon to bring the femoral head and the ankle joint exactly to overlay with a radiopaque line that passes through both points. The distance of the knee center from this line is defined as the mechanical axis deviation (MAD). In order to reduce the errors introduced by perspective projection effects, the joint centers must be placed in the center of the c-arm images, which definitely requires time, experience and additional radiation. We propose a computer aided X-ray stitching method that puts individual X-ray images into a panoramic image frame combining the Camera Augmented Mobile C-arm (CamC) system, which features a video camera with its optical center virtually coinciding with the origin of the X-rays, with an optical tracking marker pattern underneath the operating table. The camera image of the marker pattern is used to perform
Purpose. 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
Purpose. The purpose of this study was to assess the biomechanical stability of the a total ankle arthroplasty system using longitudinal migration (LM) and inducible displacement (ID) measures. This study is the first study of its kind to assess total ankle arthroplasty (TAA) implant micromotion using model-based radiostereometric analysis (MBRSA). Method. Twenty patients underwent TAA that implanted the Mobility(TM) (DePuy, Warsaw IN). The mean (SD) age was 60.4 (12.5) and BMI was 29.1 (2.8) kg/m. 2. One surgeon performed all surgeries. All patients included in this study had given informed consent. Capital Health Research Ethics Board had approved this study. Uniplanar medial-lateral RSA X-ray exams were taken postop (double exam), at six wk, three mth, six mth, one yr and two yr followup times using a supine, unloaded position. Standing medial-lateral exams were taken at three mth, six mth, one yr and two yr followup intervals. LM and ID micromotions were assessed using Model-based RSA 3.2 software (Medis specials, Leiden, The Netherlands). Implant micromotions (x, y, z, Rx, Ry, Rz, MTPM) were determined and assessed for each subject using model-based