Promising short-term outcomes of free-hand burring technique to implant second-generation metaphyseal cone in Asian knees - a case series.

BACKGROUND: The second-generation metaphyseal cone was useful in managing bone defects in revision knee arthroplasty. However, due to the anatomical constraints in Asian osteometry, the authors utilized a novel free-hand burring technique instead of cannulated reaming for bone preparation. We reported the short-term outcomes of our surgical techniques specific to Asian osteometry. METHODS: We conducted a case series by consecutively recruiting 13 female and 12 male patients (involving 25 knees), with a mean age of 71 years (range, 54-88 years). The patients underwent revision total knee arthroplasty during the period from April 2017 to June 2022. Twenty-three tibial cones and 4 femoral cones using free-hand burring technique were implanted. The mean follow-up duration was 51 months (range 18-80 months). Due to the relatively small bone size and meta-diaphyseal center mismatch in the Asian knees, the free-hand burring technique instead of the cannulated reaming technique was adopted in preparing for cone implantation. The clinical outcomes were knee ranges of motion, the Knee Society Knee scores (KSS), end-of-stem pain, infection, and the need for revision surgery. The radiological outcomes included osteointegration, fracture, and loosening. RESULTS: Mean knee range of motion improved from 83 degrees (range 0°-120°) preoperatively to 106 degrees (range 60°-125°) postoperatively (P < 0.001). Mean KSS improved significantly from 29 (range 0-70) to 69 (range 5-100) (P < 0.001). All cones were osteointegrated. One case had transient end-of-stem pain, two developed intraoperative minor femoral fractures and one suffered from recurrent infection that did not require cone revision. Cone revision-free survivorship was 100%. There was no aseptic loosening. CONCLUSIONS: The second-generation cone implanted with free-hand burring bone preparation yielded promising short-term outcomes in Asian knees.

Comparison of the cost-effectiveness and safety between staged bilateral total knee arthroplasty and simultaneous bilateral total knee arthroplasty: a retrospective cohort study between 2001 and 2022.

INTRODUCTION: A substantial proportion of Hong Kong's aging population suffers from osteoarthritis in both knees. Bilateral total knee arthroplasty (BTKA) is a surgical option for addressing this condition and can be performed via two approaches: simultaneous (SimBTKA) and staged (StaBTKA) bilateral TKAs. We compared the cost-effectiveness and safety of these two methods in our institution. METHODS: We retrospectively reviewed 2,372 patients (SimBTKA, 772; StaBTKA, 1,600; female, 1,780; male, 592; mean age at SimBTKA, 70.4 ± 7.99 years; mean age at StaBTKA, 66.4 ± 7.50 years; p < 0.001) who underwent bilateral TKA in our institution from 2001 to 2022. Patients were categorized according to surgical approach. Patients undergoing BTKA in our institution were included. Particularly for SimBTKA, patients were assessed by anesthetists to be medically fit before undergoing SimBTKA according to their age, American Society of Anesthesiologists status, and osteoarthritis severity. Primary outcome was the length-of-stay (LOS) after surgery. Secondary outcomes were the 30-day unintended readmission, intensive care unit (ICU) admission, and death. RESULTS: SimBTKA had a short mean total LOS (acute hospital + rehabilitation center; SimBTKA, 13.09 days; StaBTKA, 18.12 days; p < 0.001) and mean LOS in acute hospital (SimBTKA, 7.70 days; StaBTKA, 10.42 days; p < 0.001). However, no significant difference was found in mean LOS in rehabilitation centers (SimBTKA, 5.47 days; StaBTKA, 6.32 days; p > 0.05) between the two approaches. The 30-day unintended readmission rate was low in SimBTKA (SimBTKA, 2.07%; StaBTKA, 3.30%; OR = 1.60; p > 0.05) but statistically insignificant. SimBTKA was less costly than StaBTKA by US$8,422.22. per patient. No significant differences in ICU admission and death rates were found (p > 0.05) between the two groups. CONCLUSION: SimBTKA had a shorter LOS and lower cost than StaBTKA and comparable complication rates. Therefore, SimBTKA should be indicated in medically stable patients.

Reducing edge loading and alignment outliers with image-free robotic-assisted unicompartmental knee arthroplasty: a case controlled study.

BACKGROUND: Survivorship of medial unicompartmental knee arthroplasty (UKA) is technique-dependent. Correct femoral-tibial component positioning associates with improved survivorship. Image-free robotic-assisted unicompartmental knee arthroplasty enables preoperative and intraoperative planning of alignment and assessment of positioning prior to execution. This study aimed to compare the radiological outcomes between robotic-assisted UKA (R-UKA) and conventional UKA (C-UKA). METHODS: This retrospective case control study involved 140 UKA (82 C-UKA and 58 R-UKA) performed at an academic institution between March 2016 to November 2020, with a mean follow-up of 3 years. Postoperative radiographs were evaluated for mechanical axis and femoral-tibial component position. Component position was measured by two methods: (1) femoral-tibial component contact point with reference to four medial-to-lateral quadrants of the tibial tray and (2) femoral-tibial component contact point deviation from the center of the tibial tray as a percentage of the tibial tray width. Baseline demographics and complications were recorded. RESULTS: There was a higher mean component deviation in C-UKA compared with R-UKA using method 2 (17.2% vs. 12.8%; P = 0.007), but no difference in proportion of zonal outliers using method 1 (4 outliers in C-UKA, 5.1% vs. 1 outlier in R-UKA, 1.8%; P = 0.403). R-UKA showed no difference in mean mechanical alignment (C-UKA 5° vs. R-UKA 5°; P = 0.250). 2-year survivorship was 99% for C-UKA and 97% for R-UKA. Mean operative time was 18 min longer for R-UKA (P < 0.001). CONCLUSION: Image-free robotic-assisted UKA had improved component medio-lateral alignment compared with conventional technique.

Preoperative weight loss interventions before total hip and knee arthroplasty: a systematic review of randomized controlled trials.

BACKGROUND: The high co-prevalence of obesity and end-stage osteoarthritis requiring arthroplasty, with the former being a risk factor for complications during arthroplasty, has led to increasing interest in employing preoperative weight loss interventions such as bariatric surgery and diet modification. However, the current evidence is conflicting, and this study aimed to investigate the effect of weight loss intervention before arthroplasty in prospective randomized controlled trials. METHODS: Four electronic databases (MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials) were searched for prospective randomized controlled trials that compared weight loss interventions with usual care from inception to October 2023 by following the PRISMA guidelines. The Cochrane risk of bias tool and GRADE framework were used to assess the quality of the studies. Meta-analyses were performed when sufficient data were available from 2 or more studies. RESULTS: Three randomized controlled trials involving 198 patients were identified. Two studies employed diet modification, and one study utilized bariatric surgery. All three studies reported significant reductions in body weight and body mass index (BMI), and intervention groups had fewer postoperative complications. There was no difference in the length of stay between the intervention group and the control group. Variable patient-reported outcome measures were used by different research groups. CONCLUSION: Weight loss intervention can achieve significant reductions in body weight and body mass index before arthroplasty, with fewer postoperative complications reported. Further studies with different populations could confirm the effect of these interventions among populations with different obesity characteristics.

Subchondral bone expansion in advanced knee osteoarthritis: Relation with radiographic severity and role in surgical decision-making.

Background: Joint space width (JSW) is a traditional imaging marker for knee osteoarthritis (OA) severity, but it lacks sensitivity in advanced cases. We propose tibial subchondral bone area (TSBA), a new CT imaging marker to explore its relationship with OA radiographic severity, and to test its performance for classifying surgical decisions between unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) compared to JSW. Methods: We collected clinical, radiograph, and CT data from 182 patients who underwent primary knee arthroplasty (73 UKA, 109 TKA). The radiographic severity was scored using Kellgren-Lawrence (KL) grading system. TSBA and JSW were extracted from 3D CT-reconstruction model. We used independent t-test to investigate the relationship between TSBA and KL grade, and binary logistic regression to identify factors associated with TKA risk. The accuracy of TSBA, JSW and established classification model in differentiating between UKA and TKA was assessed using AUC. Results: All parameters exhibited inter- and intra-class coefficients greater than 0.966. Patients with KL grade 4 had significantly larger TSBA than those with KL grade 3. TSBA (0.708 of AUC) was superior to minimal/average JSW (0.547/0.554 of AUC) associated with the risk of receiving TKA. Medial TSBA, together with gender and Knee Society Knee Score, emerged as independent classification factors in multivariate analysis. The overall AUC of composite model for surgical decision-making was 0.822. Conclusion: Tibial subchondral bone area is an independent imaging marker for radiographic severity, and is superior to JSW for surgical decision-making between UKA and TKA in advanced OA patients.

Radiomics signature of osteoarthritis: Current status and perspective.

Osteoarthritis (OA) is one of the fast-growing disability-related diseases worldwide, which has significantly affected the quality of patients' lives and brings about substantial socioeconomic burdens in medical expenditure. There is currently no cure for OA once the bone damage is established. Unfortunately, the existing radiological examination is limited to grading the disease's severity and is insufficient to precisely diagnose OA, detect early OA or predict OA progression. Therefore, there is a pressing need to develop novel approaches in medical image analysis to detect subtle changes for identifying early OA development and rapid progressors. Recently, radiomics has emerged as a unique approach to extracting high-dimensional imaging features that quantitatively characterise visible or hidden information from routine medical images. Radiomics data mining via machine learning has empowered precise diagnoses and prognoses of disease, mainly in oncology. Mounting evidence has shown its great potential in aiding the diagnosis and contributing to the study of musculoskeletal diseases. This paper will summarise the current development of radiomics at the crossroads between engineering and medicine and discuss the application and perspectives of radiomics analysis for OA diagnosis and prognosis. The translational potential of this article: Radiomics is a novel approach used in oncology, and it may also play an essential role in the diagnosis and prognosis of OA. By transforming medical images from qualitative interpretation to quantitative data, radiomics could be the solution for precise early OA detection, progression tracking, and treatment efficacy prediction. Since the application of radiomics in OA is still in the early stages and primarily focuses on fundamental studies, this review may inspire more explorations and bring more promising diagnoses, prognoses, and management results of OA.

Radiomics analysis of patellofemoral joint improves knee replacement risk prediction: Data from the Multicenter Osteoarthritis Study (MOST).

Objective: Knee replacement (KR) is the last-resort treatment for knee osteoarthritis. Although radiographic evidence of tibiofemoral joint has been widely adopted for prognostication, patellofemoral joint has gained little attention and may hold additional value for further improvements. We aimed to quantitatively analyse patellofemoral joint through radiomics analysis of lateral view radiographs for improved KR risk prediction. Design: From the Multicenter Osteoarthritis Study dataset, we retrospectively retrieved the initial-visit lateral left knee radiographs of 2943 patients aged 50 to 79. They were split into training and test cohorts at a 2:1 ratio. A comprehensive set of radiomic features were extracted within the best-performing subregion of patellofemoral joint and combined into a radiomics score (RadScore). A KR risk score, derived from Kellgren-Lawrence grade (KLG) of tibiofemoral joint and RadScore of patellofemoral joint, was developed by multivariate Cox regression and assessed using time-dependent area under receiver operating characteristic curve (AUC). Results: While patellofemoral osteoarthritis (PFOA) was insignificant during multivariate analysis, RadScore was identified as an independent risk factor (multivariate Cox p-value < 0.001) for KR. The subgroup analysis revealed that RadScore was particularly effective in predicting rapid progressor (KR occurrence before 30 months) among early- (KLG < 2) and mid-stage (KLG â€‹= â€‹2) patients. Combining two joints radiographic information, the AUC reached 0.89/0.87 for predicting 60-month KR occurrence. Conclusions: The RadScore of the patellofemoral joint on lateral radiographs emerges as an independent prognostic factor for improving KR prognosis prediction. The KR risk score could be instrumental in managing progressive knee osteoarthritis interventions.

Adaptive Fusion of Deep Learning With Statistical Anatomical Knowledge for Robust Patella Segmentation From CT Images.

Kneeosteoarthritis (KOA), as a leading joint disease, can be decided by examining the shapes of patella to spot potential abnormal variations. To assist doctors in the diagnosis of KOA, a robust automatic patella segmentation method is highly demanded in clinical practice. Deep learning methods, especially convolutional neural networks (CNNs) have been widely applied to medical image segmentation in recent years. Nevertheless, poor image quality and limited data still impose challenges to segmentation via CNNs. On the other hand, statistical shape models (SSMs) can generate shape priors which give anatomically reliable segmentation to varying instances. Thus, in this work, we propose an adaptive fusion framework, explicitly combining deep neural networks and anatomical knowledge from SSM for robust patella segmentation. Our adaptive fusion framework will accordingly adjust the weight of segmentation candidates in fusion based on their segmentation performance. We also propose a voxel-wise refinement strategy to make the segmentation of CNNs more anatomically correct. Extensive experiments and thorough assessment have been conducted on various mainstream CNN backbones for patella segmentation in low-data regimes, which demonstrate that our framework can be flexibly attached to a CNN model, significantly improving its performance when labeled training data are limited and input image data are of poor quality.

Long-term follow-up of an uncemented proximally hydroxyapatite-coated femoral stem in total hip arthroplasty.

Aims: The aim of this study was to evaluate the survival of a collarless, straight, hydroxyapatite-coated femoral stem in total hip arthroplasty (THA) at a minimum follow-up of 20 years. Methods: We reviewed the results of 165 THAs using the Omnifit HA system in 138 patients, performed between August 1993 and December 1999. The mean age of the patients at the time of surgery was 46 years (20 to 77). Avascular necrosis was the most common indication for THA, followed by ankylosing spondylitis and primary osteoarthritis. The mean follow-up was 22 years (20 to 31). At 20 and 25 years, 113 THAs in 91 patients and 63 THAs in 55 patients were available for review, respectively, while others died or were lost to follow-up. Kaplan-Meier analysis was performed to evaluate the survival of the stem. Radiographs were reviewed regularly, and the stability of the stem was evaluated using the Engh classification. Results: A total of seven stems (4.2%) were revised during the study period: one for aseptic loosening, three for periprosthetic fracture, two for infection, and one for recurrent dislocation. At 20 years, survival with revision of the stem for any indication and for aseptic loosening as the endpoint was 96.0% (95% confidence interval (CI) 92.6 to 99.5) and 98.4% (95% CI 96.2 to 100), respectively. At 25 years, the corresponding rates of survival were 94.5% (95% CI 89.9 to 99.3) and 98.1% (95% CI 95.7 to 99.6), respectively. There was radiological evidence of stable bony fixation in 86 stems (76.1%) and evidence of loosening in four (3.5%) at 20 years. All patients with radiological evidence of loosening were asymptomatic. Conclusion: The Omnifit HA femoral stem offered promising long-term survival into the third decade.