Objectives. The
Aims. The aim of this study was to systematically compare the safety and
Aims. Hip arthroplasty aims to accurately recreate joint biomechanics. Considerable attention has been paid to vertical and horizontal offset, but femoral head centre in the anteroposterior (AP) plane has received little attention. This study investigates the
Objectives. Computed tomography (CT) plays an important role in evaluating wear and periacetabular osteolysis (PAO) in total hip replacements. One concern with CT is the high radiation exposure since standard pelvic CT provides approximately 3.5 millisieverts (mSv) of radiation exposure, whereas a planar radiographic examination with three projections totals approximately 0.5 mSv. The objective of this study was to evaluate the lowest acceptable radiation dose for dual-energy CT (DECT) images when measuring wear and periacetabular osteolysis in uncemented metal components. Materials and Methods. A porcine pelvis with bilateral uncemented hip prostheses and with known linear wear and acetabular bone defects was examined in a third-generation multidetector DECT scanner. The examinations were performed with four different radiation levels both with and without iterative reconstruction techniques. From the high and low peak kilo voltage acquisitions, polychrmoatic images were created together with virtual monochromatic images of energies 100 kiloelectron volts (keV) and 150 keV. Results. We could assess wear and PAO while substantially lowering the effective radiation dose to 0.7 mSv for a total pelvic view with an
Objectives. To assess the
Aims. The aim of this study was to evaluate the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens from synovial fluid of prosthetic joint infection (PJI) patients. Methods. A group of 75 patients who underwent revision knee or hip arthroplasties were enrolled prospectively. Ten patients with primary arthroplasties were included as negative controls. Synovial fluid was collected for mNGS analysis. Optimal thresholds were determined to distinguish pathogens from background microbes. Synovial fluid, tissue, and sonicate fluid were obtained for culture. Results. A total of 49 PJI and 21 noninfection patients were finally included. Of the 39 culture-positive PJI cases, mNGS results were positive in 37 patients (94.9%), and were consistent with culture results at the genus level in 32 patients (86.5%) and at the species level in 27 patients (73.0%). Metagenomic next-generation sequencing additionally identified 15 pathogens from five culture-positive and all ten culture-negative PJI cases, and even one pathogen from one noninfection patient, while yielding no positive findings in any primary arthroplasty. However, seven pathogens identified by culture were missed by mNGS. The sensitivity of mNGS for diagnosing PJI was 95.9%, which was significantly higher than that of comprehensive culture (79.6%; p = 0.014). The specificity is similar between mNGS and comprehensive culture (95.2% and 95.2%, respectively; p = 1.0). Conclusion. Metagenomic next-generation sequencing can effectively identify pathogens from synovial fluid of PJI patients, and demonstrates high
Aims. Histology is an established tool in diagnosing periprosthetic joint infections (PJIs). Different thresholds, using various infection definitions and histopathological criteria, have been described. This study determined the performance of different thresholds of polymorphonuclear neutrophils (≥ 5 PMN/HPF, ≥ 10 PMN/HPF, ≥ 23 PMN/10 HPF) , when using the European Bone and Joint Infection Society (EBJIS), Infectious Diseases Society of America (IDSA), and the International Consensus Meeting (ICM) 2018 criteria for PJI. Methods. A total of 119 patients undergoing revision total hip (rTHA) or knee arthroplasty (rTKA) were included. Permanent histology sections of periprosthetic tissue were evaluated under high power (400× magnification) and neutrophils were counted per HPF. The mean neutrophil count in ten HPFs was calculated (PMN/HPF). Based on receiver operating characteristic (ROC) curve analysis and the z-test, thresholds were compared. Results. Using the EBJIS criteria, a cut-off of ≥ five PMN/HPF showed a sensitivity of 93% (95% confidence interval (CI) 81 to 98) and specificity of 84% (95% CI 74 to 91). The optimal threshold when applying the IDSA and ICM criteria was ≥ ten PMN/HPF with sensitivities of 94% (95% CI 79 to 99) and 90% (95% CI 76 to 97), and specificities of 86% (95% CI 77 to 92) and 92% (95% CI 84 to 97), respectively. In rTKA, a better performance of histopathological analysis was observed in comparison with rTHA when using the IDSA criteria (p < 0.001). Conclusion. With high
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
We performed A total of 12 cadaveric lower limbs were tested with a commercial
image-free navigation system using trackers secured by bone screws.
We then tested a non-invasive fabric-strap system. The lower limb
was secured at 10° intervals from 0° to 60° of knee flexion and
100 N of force was applied perpendicular to the tibia. Acceptable
coefficient of repeatability (CR) and limits of agreement (LOA)
of 3 mm were set based on diagnostic criteria for anterior cruciate
ligament (ACL) insufficiency.Objectives
Methods
Aims. This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated. Methods. A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification
Aims. The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the
Aims. Manual impaction, with a mallet and introducer, remains the standard method of installing cementless acetabular cups during total hip arthroplasty (THA). This study aims to quantify the
Aims. Serum inflammatory parameters are widely used to aid in diagnosing a periprosthetic joint infection (PJI). Due to their limited performances in the literature, novel and more accurate biomarkers are needed. Serum albumin-to-globulin ratio (AGR) and serum CRP-to-albumin ratio (CAR) have previously been proposed as potential new parameters, but results were mixed. The aim of this study was to assess the diagnostic
Aims. The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test
Aims. To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Methods. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology. Results. Overall, 152 patients without and 58 with a history of surgical revision following surgery for ASD were observed; the mean age was 68.9 years (SD 8.7) and 66.9 years (SD 6.6), respectively. On implementing a random forest model, the classification of URO events resulted in a balanced
Aims. An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. Methods. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data. Results. The patient-specific approach with engineered features achieved the highest in-clinic performance for differentiating physiotherapy exercise from non-exercise activity (area under the receiver operating characteristic (AUROC) = 0.924). Including non-exercise data in algorithm training further improved classifier performance (random forest, AUROC = 0.985). The highest
Aims. This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. Methods. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm. 3. ). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the
Aims. The use of 3D printing has become increasingly popular and has been widely used in orthopaedic surgery. There has been a trend towards an increasing number of publications in this field, but existing literature incorporates limited high-quality studies, and there is a lack of reports on outcomes. The aim of this study was to perform a scoping review with Level I evidence on the application and effectiveness of 3D printing. Methods. A literature search was performed in PubMed, Embase, and Web of Science databases. The keywords used for the search criteria were ((3d print*) OR (rapid prototyp*) OR (additive manufactur*)) AND (orthopaedic). The inclusion criteria were: 1) use of 3D printing in orthopaedics, 2) randomized controlled trials, and 3) studies with participants/patients. Risk of bias was assessed with Cochrane Collaboration Tool and PEDro Score. Pooled analysis was performed. Results. Overall, 21 studies were included in our study with a pooled total of 932 participants. Pooled analysis showed that operating time (p < 0.001), blood loss (p < 0.001), fluoroscopy times (p < 0.001), bone union time (p < 0.001), pain (p = 0.040),
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. This study aimed to explore the diagnostic value of synovial fluid neutrophil extracellular traps (SF-NETs) in periprosthetic joint infection (PJI) diagnosis, and compare it with that of microbial culture, serum ESR and CRP, synovial white blood cell (WBC) count, and polymorphonuclear neutrophil percentage (PMN%). Methods. In a single health centre, patients with suspected PJI were enrolled from January 2013 to December 2021. The inclusion criteria were: 1) patients who were suspected to have PJI; 2) patients with complete medical records; and 3) patients from whom sufficient synovial fluid was obtained for microbial culture and NET test. Patients who received revision surgeries due to aseptic failure (AF) were selected as controls. Synovial fluid was collected for microbial culture and SF-WBC, SF-PNM%, and SF-NET detection. The receiver operating characteristic curve (ROC) of synovial NET, WBC, PMN%, and area under the curve (AUC) were obtained; the diagnostic efficacies of these diagnostic indexes were calculated and compared. Results. The levels of SF-NETs in the PJI group were significantly higher than those of the AF group. The AUC of SF-NET was 0.971 (95% confidence interval (CI) 0.903 to 0.996), the sensitivity was 93.48% (95% CI 82.10% to 98.63%), the specificity was 96.43% (95% CI 81.65% to 99.91%), the