Objective . Dunkin Hartley guinea pigs, a commonly used animal model of osteoarthritis,
were used to determine if high frequency ultrasound can ensure intra-articular
injections are accurately positioned in the knee joint. Methods. A high-resolution small animal ultrasound system with a 40 MHz
transducer was used for image-guided injections. A total of 36 guinea
pigs were anaesthetised with isoflurane and placed on a heated stage.
Sterile needles were inserted directly into the knee joint medially,
while the transducer was placed on the lateral surface, allowing
the femur, tibia and fat pad to be visualised in the images. B-mode
cine loops were acquired during 100 µl. We assessed our ability
to visualise 1) important anatomical landmarks, 2) the needle and
3) anatomical changes due to the injection. . Results. From the ultrasound images, we were able to visualise clearly
the movement of anatomical landmarks in 75% of the injections. The
majority of these showed separation of the fat pad (67.1%), suggesting
the injections were correctly delivered in the joint space. We also
observed dorsal joint expansion (23%) and patellar tendon movement
(10%) in a smaller subset of injections. Conclusion. The results demonstrate that this image-guided technique can
be used to visualise the location of an intra-articular injection
in the joints of guinea pigs. Future studies using an ultrasound-guided
approach could help improve the injection
Aims. The diagnosis of periprosthetic joint infection (PJI) can be challenging as the symptoms are similar to other conditions, and the markers used for diagnosis have limited sensitivity and specificity. Recent research has suggested using blood cell ratios, such as platelet-to-volume ratio (PVR) and platelet-to-lymphocyte ratio (PLR), to improve diagnostic
Aims. 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. Methods. 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. Results. OpenPose had excellent test-retest reliability (intraclass correlation coefficient (1,1) = 1.000). The R. 2. of all regression models indicated large correlations (0.747 to 0.927). In the flexion position, the intraclass correlation coefficients (2,1) of OpenPose indicated excellent agreement (0.953) with radiography. In the extension position, the intraclass correlation coefficients (2,1) indicated good agreement of OpenPose and radiography (0.815) and moderate agreement of goniometry with radiography (0.593). OpenPose had no systematic error in the flexion position, and a 2.3° fixed error in the extension position, compared to radiography. Conclusion. OpenPose is a reliable and valid tool for measuring flexion and extension positions after TKA. It has better
Aims. To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Methods. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models. Results. Of the 5,600 patients included in this study, 342 (6.1%) underwent SDD. The random forest (RF) model performed the best overall, with an internally validated AUC of 0.810. The ten crucial factors favoring SDD in the RF model include operating time, anaesthesia type, age, BMI, American Society of Anesthesiologists grade, race, history of diabetes, rTKA type, sex, and smoking status. Eight of these variables were also found to be significant in the MLR model. Conclusion. The RF model displayed excellent
Aims. The aims of this study were: 1) to describe extended restricted kinematic alignment (E-rKA), a novel alignment strategy during robotic-assisted total knee arthroplasty (RA-TKA); 2) to compare residual medial compartment tightness following virtual surgical planning during RA-TKA using mechanical alignment (MA) and E-rKA, in the same set of osteoarthritic varus knees; 3) to assess the requirement of soft-tissue releases during RA-TKA using E-rKA; and 4) to compare the
Aims. Accurate identification of the ankle joint centre is critical for estimating tibial coronal alignment in total knee arthroplasty (TKA). The purpose of the current study was to leverage artificial intelligence (AI) to determine the
Limb alignment in total knee arthroplasty (TKA) influences periarticular soft-tissue tension, biomechanics through knee flexion, and implant survival. Despite this, there is no uniform consensus on the optimal alignment technique for TKA. Neutral mechanical alignment facilitates knee flexion and symmetrical component wear but forces the limb into an unnatural position that alters native knee kinematics through the arc of knee flexion. Kinematic alignment aims to restore native limb alignment, but the safe ranges with this technique remain uncertain and the effects of this alignment technique on component survivorship remain unknown. Anatomical alignment aims to restore predisease limb alignment and knee geometry, but existing studies using this technique are based on cadaveric specimens or clinical trials with limited follow-up times. Functional alignment aims to restore the native plane and obliquity of the joint by manipulating implant positioning while limiting soft tissue releases, but the results of high-quality studies with long-term outcomes are still awaited. The drawbacks of existing studies on alignment include the use of surgical techniques with limited
Aims. No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the
Aims. The purpose of this study was to compare the radiological outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Methods. Postoperative radiological outcomes from 86 consecutive robotic-assisted UKAs (RAUKA group) from a single academic centre were retrospectively reviewed and compared to 253 manual UKAs (MUKA group) drawn from a prior study at our institution. Femoral coronal and sagittal angles (FCA, FSA), tibial coronal and sagittal angles (TCA, TSA), and implant overhang were radiologically measured to identify outliers. Results. When assessing the
Aims. An algorithm to determine the constitutional alignment of the lower limb once arthritic deformity has occurred would be of value when undertaking kinematically aligned total knee arthroplasty (TKA). The purpose of this study was to determine if the arithmetic hip-knee-ankle angle (aHKA) algorithm could estimate the constitutional alignment of the lower limb following development of significant arthritis. Methods. A matched-pairs radiological study was undertaken comparing the aHKA of an osteoarthritic knee (aHKA-OA) with the mechanical HKA of the contralateral normal knee (mHKA-N). Patients with Grade 3 or 4 Kellgren-Lawrence tibiofemoral osteoarthritis in an arthritic knee undergoing TKA and Grade 0 or 1 osteoarthritis in the contralateral normal knee were included. The aHKA algorithm subtracts the lateral distal femoral angle (LDFA) from the medial proximal tibial angle (MPTA) measured on standing long leg radiographs. The primary outcome was the mean of the paired differences in the aHKA-OA and mHKA-N. Secondary outcomes included comparison of sex-based differences and capacity of the aHKA to determine the constitutional alignment based on degree of deformity. Results. A total of 51 radiographs met the inclusion criteria. There was no significant difference between aHKA-OA and mHKA-N, with a mean angular difference of −0.4° (95% SE −0.8° to 0.1°; p = 0.16). There was no significant sex-based difference when comparing aHKA-OA and mHKA-N (mean difference 0.8°; p = 0.11). Knees with deformities of more than 8° had a greater mean difference between aHKA-OA and mHKA-N (1.3°) than those with lesser deformities (-0.1°; p = 0.009). Conclusion. This study supports the arithmetic HKA algorithm for prediction of the constitutional alignment once arthritis has developed. The algorithm has similar
Aims. The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty. Methods. Using an US system, which is fitted with an electromagnetic (EM) tracker that is integrated into the US probe, allows 3D tracking of the probe, femur, and tibia. The raw US radiofrequency (RF) signals are acquired and, using real-time signal processing, bone boundaries are extracted. Bone boundaries and the tracking information are fused in a 3D point cloud for the femur and tibia. Using a statistical shaping model, the patient-specific surface is reconstructed by optimizing bone geometry to match the point clouds. An
Aims. Unicompartmental knee arthroplasty (UKA) is a bone-preserving treatment option for osteoarthritis localized to a single compartment in the knee. The success of the procedure is sensitive to patient selection and alignment errors. Robotic arm-assisted UKA provides technological assistance to intraoperative bony resection
Aims. The mobile bearing Oxford unicompartmental knee arthroplasty (OUKA) is recommended to be performed with the leg in the hanging leg (HL) position, and the thigh placed in a stirrup. This comparative cadaveric study assesses implant positioning and intraoperative kinematics of OUKA implanted either in the HL position or in the supine leg (SL) position. Methods. A total of 16 fresh-frozen knees in eight human cadavers, without macroscopic anatomical defects, were selected. The knees from each cadaver were randomized to have the OUKA implanted in the HL or SL position. Results. Tibial base plate rotation was significantly more variable in the SL group with 75% of tibiae mal-rotated. Multivariate analysis of navigation data found no difference based on all kinematic parameters across the range of motion (ROM). However, area under the curve analysis showed that knees placed in the HL position had much smaller differences between the pre- and post-surgery conditions for kinematics mean values across the entire ROM. Conclusion. The sagittal tibia cut, not dependent on standard instrumentation, determines the tibial component rotation. The HL position improves
Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A DL workflow was created to measure the FMAA and validated against human measurements. To reflect potential intramedullary guide placement during manual TKA, two different FMAAs were calculated either using a line approximating the entire diaphyseal shaft, and a line connecting the apex of the femoral intercondylar sulcus to the centre of the diaphysis. The proportion of FMAAs outside a range of 5.0° (SD 2.0°) was calculated for both definitions, and FMAA was compared using univariate analyses across sex, BMI, knee alignment, and femur length.Aims
Methods
Unicompartmental knee arthroplasty (UKA) is the preferred treatment for anterior medial knee osteoarthritis (OA) owing to the rapid postoperative recovery. However, the risk factors for UKA failure remain controversial. The clinical data of Oxford mobile-bearing UKAs performed between 2011 and 2017 with a minimum follow-up of five years were retrospectively analyzed. Demographic, surgical, and follow-up data were collected. The Cox proportional hazards model was used to identify the risk factors that contribute to UKA failure. Kaplan-Meier survival was used to compare the effect of the prosthesis position on UKA survival.Aims
Methods
This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA. Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization.Aims
Methods
This Delphi study assessed the challenges of diagnosing soft-tissue knee injuries (STKIs) in acute settings among orthopaedic healthcare stakeholders. This modified e-Delphi study consisted of three rounds and involved 32 orthopaedic healthcare stakeholders, including physiotherapists, emergency nurse practitioners, sports medicine physicians, radiologists, orthopaedic registrars, and orthopaedic consultants. The perceived importance of diagnostic components relevant to STKIs included patient and external risk factors, clinical signs and symptoms, special clinical tests, and diagnostic imaging methods. Each round required scoring and ranking various items on a ten-point Likert scale. The items were refined as each round progressed. The study produced rankings of perceived importance across the various diagnostic components.Aims
Methods
Objectives. An important measure for the diagnosis and monitoring of knee osteoarthritis is the minimum joint space width (mJSW). This requires accurate alignment of the x-ray beam with the tibial plateau, which may not be accomplished in practice. We investigate the feasibility of a new mJSW measurement method from stereo radiographs using 3D statistical shape models (SSM) and evaluate its sensitivity to changes in the mJSW and its robustness to variations in patient positioning and bone geometry. Materials and Methods. A validation study was performed using five cadaver specimens. The actual mJSW was varied and images were acquired with variation in the cadaver positioning. For comparison purposes, the mJSW was also assessed from plain radiographs. To study the influence of SSM model
Patient dissatisfaction following primary total knee arthroplasty (TKA) with manual jig-based instruments has been reported to be as high as 30%. Robotic-assisted total knee arthroplasty (RA-TKA) has been increasingly used in an effort to improve patient outcomes, however there is a paucity of literature examining patient satisfaction after RA-TKA. This study aims to identify the incidence of patients who were not satisfied following RA-TKA and to determine factors associated with higher levels of dissatisfaction. This was a retrospective review of 674 patients who underwent primary TKA between October 2016 and September 2020 with a minimum two-year follow-up. A five-point Likert satisfaction score was used to place patients into two groups: Group A were those who were very dissatisfied, dissatisfied, or neutral (Likert score 1 to 3) and Group B were those who were satisfied or very satisfied (Likert score 4 to 5). Patient demographic data, as well as preoperative and postoperative patient-reported outcome measures, were compared between groups.Aims
Methods
While residual fixed flexion deformity (FFD) in unicompartmental knee arthroplasty (UKA) has been associated with worse functional outcomes, limited evidence exists regarding FFD changes. The objective of this study was to quantify FFD changes in patients with medial unicompartmental knee arthritis undergoing UKA, and investigate any correlation with clinical outcomes. This study included 136 patients undergoing robotic arm-assisted medial UKA between January 2018 and December 2022. The study included 75 males (55.1%) and 61 (44.9%) females, with a mean age of 67.1 years (45 to 90). Patients were divided into three study groups based on the degree of preoperative FFD: ≤ 5°, 5° to ≤ 10°, and > 10°. Intraoperative optical motion capture technology was used to assess pre- and postoperative FFD. Clinical FFD was measured pre- and postoperatively at six weeks and one year following surgery. Preoperative and one-year postoperative Oxford Knee Scores (OKS) were collected.Aims
Methods