Cross-sectional associations of low body mass index and being underweight with joint damage in Chinese patients with rheumatoid arthritis.

Objective: To characterize BMI in Chinese patients with RA vs US patients and examine its association with joint damage in Chinese patients. Methods: Each of the 1318 patients from a real-world Chinese RA population was first stratified by gender and then individually age-matched with one American RA patient from the US National Health and Nutritional Examination Survey 1999-2018. Data on BMI, bilateral hand radiographs and risk factors at enrolment were collected but radiographs were unavailable for the American patients. Logistic regression was used to evaluate the association of BMI with radiographic joint damage (RJD) in Chinese patients. Results: Chinese patients had a significantly lower BMI [(weighted) median 21.8 vs 29.8 kg/m2; P < 0.001] and a higher prevalence of being underweight (15.2% vs 1.1%; P < 0.05) than their American counterparts. Underweight Chinese patients (BMI <18.5) had higher modified total Sharp scores (median 17 vs 10) and joint space narrowing (JSN) subscores (median 6 vs 2) (both P < 0.05) than normal-weight patients (BMI ≥18.5-<24). After controlling for confounding, continuous BMI was cross-sectionally negatively associated with RJD [adjusted prevalence odds ratio (OR) 0.90 (95% CI 0.85, 0.96)] and JSN [adjusted prevalence OR 0.92 (95% CI 0.87, 0.96)]; being underweight vs normal weight was associated with RJD [adjusted prevalence OR 2.14 (95% CI 1.37, 3.35)] and JSN [adjusted prevalence OR 1.77 (95% CI 1.10, 2.84)]. Conclusion: Low BMI and being underweight were cross-sectionally associated with joint damage in Chinese RA patients, especially JSN, suggesting the clinical importance of identifying underweight patients and focusing on weight gain to prevent joint damage.

Subtle Radiographic Progression at Six Months Can Be Detected Using Automated Quantitative Software in Rheumatoid Arthritis While Receiving Tocilizumab.

OBJECTIVES: We investigated whether our in-house software equipped with partial image phase-only correlation (PIPOC) can detect subtle radiographic joint space narrowing (JSN) progression at six months and predict JSN progression in rheumatoid arthritis (RA) patients receiving Tocilizumab. METHODS: The study included 39 RA patients who were treated with Tocilizumab. Radiological progression of the metacarpophalangeal and the proximal interphalangeal joints was evaluated according to the Genant-modified Sharp score (GSS) at 0, 6, and 12 months. Automatic measurements were performed with the software. We validated the software in terms of accuracy in detecting the JSN progression. RESULTS: The success rate of the software for joint space width (JSW) measurement was 96.8% (449/464). The 0-12-month JSW change by the software was significantly greater in joints with the 0-6-month PIPOC (+) group than the 0-6-month PIPOC (-) group (p < 0.001). The 0-12-month JSW change by the software was 0-12-month GSS (+) than with 0-12-month GSS (-) (p = 0.02). Here, "(+)" indicates the JSN progression during the follow-up period. Meanwhile, "(-)" indicates no JSN progression during the follow-up period. Linear regression tests showed significant correlations between the 0-6-month and the 0-12-month PIPOC in the left 2nd and 3rd MCP joints (R2 = 0.554 and 0.420, respectively). CONCLUSIONS: Our in-house software equipped with PIPOC could predict subsequent JSN progression with only short-term observations.

Evaluating high-resolution computed tomography derived 3-D joint space metrics of the metacarpophalangeal joints between rheumatoid arthritis and age- and sex-matched control participants.

Introduction: Rheumatoid arthritis (RA) is commonly characterized by joint space narrowing. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides unparalleled in vivo visualization and quantification of joint space in extremity joints commonly affected by RA, such as the 2nd and 3rd metacarpophalangeal joints. However, age, sex, and obesity can also influence joint space narrowing. Thus, this study aimed to determine whether HR-pQCT joint space metrics could distinguish between RA patients and controls, and determine the effects of age, sex and body mass index (BMI) on these joint space metrics. Methods: HR-pQCT joint space metrics (volume, width, standard deviation of width, maximum/minimum width, and asymmetry) were acquired from RA patients and age-and sex-matched healthy control participants 2nd and 3rd MCP joints. Joint health and functionality were assessed with ultrasound (i.e., effusion and inflammation), hand function tests, and questionnaires. Results: HR-pQCT-derived 3D joint space metrics were not significantly different between RA and control groups (p > 0.05), despite significant differences in inflammation and joint function (p < 0.05). Joint space volume, mean joint space width (JSW), maximum JSW, minimum JSW were larger in males than females (p < 0.05), while maximum JSW decreased with age. No significant association between joint space metrics and BMI were found. Conclusion: HR-pQCT did not detect group level differences between RA and age-and sex-matched controls. Further research is necessary to determine whether this is due to a true lack of group level differences due to well-controlled RA, or the inability of HR-pQCT to detect a difference.

Joint-preserving effect and patient-reported outcomes of transtrochanteric curved varus osteotomy for osteonecrosis of the femoral head.

BACKGROUND: This study assessed the hip survival rate and patient-reported outcome measures (PROMs) of transtrochanteric curved varus osteotomy (CVO) for osteonecrosis of the femoral head (ONFH) compared with those of conservative management. METHODS: The CVO group comprised 32 consecutive patients (39 hips) who underwent CVO for ONFH between 2000 and 2011. The conservative group consisted of 36 consecutive patients (37 hips) who were managed conservatively for at least 1 year after collapse and who had ONFH classified by the Japanese Investigation Committee of Health and Welfare as type B or C1, for which CVO is indicated. Kaplan-Meier analysis of hip survival used any ONFH-related therapeutic surgery as the endpoint. PROMs were evaluated for all patients with surviving hips and radiographs available at the latest follow-up. RESULT: The 10-year hip survival rate in the CVO group was 86.7%, which was significantly higher than the 51.0% 5-year survival rate in the conservative group (p < 0.0001). The Oxford Hip Score and UCLA Activity Score were significantly better in the CVO group without joint space narrowing than in the conservative group, with no significant differences between the CVO group with joint space narrowing and the conservative group. CONCLUSION: CVO could preserve hip joints more effectively than conservative follow-up after collapse, although the presence of joint space narrowing could reduce satisfaction levels even in patients with long-term hip survival.

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.

Survival analysis on subchondral bone length for total knee replacement.

OBJECTIVE: Use subchondral bone length (SBL), a new MRI-derived measure that reflects the extent of cartilage loss and bone flattening, to predict the risk of progression to total knee replacement (TKR). METHODS: We employed baseline MRI data from the Osteoarthritis Initiative (OAI), focusing on 760 men and 1214 women with bone marrow lesions (BMLs) and joint space narrowing (JSN) scores, to predict the progression to TKR. To minimize bias from analyzing both knees of a participant, only the knee with a higher Kellgren-Lawrence (KL) grade was considered, given its greater potential need for TKR. We utilized the Kaplan-Meier survival curves and Cox proportional hazards models, incorporating raw and normalized values of SBL, JSN, and BML as predictors. The study included subgroup analyses for different demographics and clinical characteristics, using models for raw and normalized SBL (merged, femoral, tibial), BML (merged, femoral, tibial), and JSN (medial and lateral compartments). Model performance was evaluated using the time-dependent area under the curve (AUC), Brier score, and Concordance index to gauge accuracy, calibration, and discriminatory power. Knee joint and region-level analyses were conducted to determine the effectiveness of SBL, JSN, and BML in predicting TKR risk. RESULTS: The SBL model, incorporating data from both the femur and tibia, demonstrated a predictive capacity for TKR that closely matched the performance of the BML score and the JSN grade. The Concordance index of the SBL model was 0.764, closely mirroring the BML's 0.759 and slightly below JSN's 0.788. The Brier score for the SBL model stood at 0.069, showing comparability with BML's 0.073 and a minor difference from JSN's 0.067. Regarding the AUC, the SBL model achieved 0.803, nearly identical to BML's 0.802 and slightly lower than JSN's 0.827. CONCLUSION: SBL's capacity to predict the risk of progression to TKR highlights its potential as an effective imaging biomarker for knee osteoarthritis.

Radiological progression and predictive factors in psoriatic arthritis: insights from a decade-long retrospective cohort study.

OBJECTIVES: Radiological alterations in psoriatic arthritis (PsA) are an established phenomenon frequently observed throughout the disease course. Our goal was to investigate the changes in the bone structure of PsA patients by conventional radiography. METHODS: This study designed as a retrospective cohort study and cross-sectional evaluation for disease activity. The disease activity and the severity of skin and nail involvement were assessed. The Simplified Psoriatic Arthritis Radiographic Score (SPARS) was used to investigate the radiological progression. Logistic regression analysis was used to determine the predictors of radiological changes. RESULTS: Joint space narrowing and bone proliferation in hands (p = 0.001 and p = 0.001, respectively) and joint space narrowing in feet (p = 0.047) were more common at the final evaluation than at the baseline assessment. Total scores of joint space narrowing and bone proliferation in hands and feet were higher at the last visit than at the initial assessment (p < 0.001). Male gender (p = 0.030, OR 4.32 (95%CI 1.15-16.15)], older age (for joint space narrowing [p = 0.026 OR 1.08 (95%CI 1.01-1.56)] and for proliferation [p = 0.025 OR 1.08 (95%CI 1.01-1.44)]), high Disease Activity index for Psoriatic Arthritis (DAPSA) scores at baseline [p = 0.032 OR 6.21 (95%CI 1.17-32.92)], and symmetrical polyarticular involvement at baseline [p = 0.025 OR 5.3 (95% CI 1.23-22.4)] were found as predictors of structural changes. CONCLUSION: By the end of the decade, joint space narrowing and proliferation were observed to be more common than erosion. Male gender, older age, higher initial DAPSA scores, and initial polyarticular involvement were identified as predictors of radiological damage. Key Points • The radiological changes of Psoriatic arthritis are a well-known entity. However, studies investigating the progression of joint involvement over time are scarce. • This study reveals that joint space narrowing and proliferation are the most prominent radiological alterations in Psoriatic Arthritis patients at the end of the decade. • Male gender, older age, higher baseline DAPSA scores, and initial polyarticular involvement are predictive factors influencing the progression of bone destruction  in Psoriatic Arthritis patients.

Assessment of a novel deep learning-based software developed for automatic feature extraction and grading of radiographic knee osteoarthritis.

BACKGROUND: The Kellgren-Lawrence (KL) grading system is the most widely used method to classify the severity of osteoarthritis (OA) of the knee. However, due to ambiguity of terminology, the KL system showed inferior inter- and intra-observer reliability. For a more reliable evaluation, we recently developed novel deep learning (DL) software known as MediAI-OA to extract each radiographic feature of knee OA and to grade OA severity based on the KL system. METHODS: This research used data from the Osteoarthritis Initiative for training and validation of MediAI-OA. 44,193 radiographs and 810 radiographs were set as the training data and used as validation data, respectively. This AI model was developed to automatically quantify the degree of joint space narrowing (JSN) of medial and lateral tibiofemoral joint, to automatically detect osteophytes in four regions (medial distal femur, lateral distal femur, medial proximal tibia and lateral proximal tibia) of the knee joint, to classify the KL grade, and present the results of these three OA features together. The model was tested by using 400 test datasets, and the results were compared to the ground truth. The accuracy of the JSN quantification and osteophyte detection was evaluated. The KL grade classification performance was evaluated by precision, recall, F1 score, accuracy, and Cohen's kappa coefficient. In addition, we defined KL grade 2 or higher as clinically significant OA, and accuracy of OA diagnosis were obtained. RESULTS: The mean squared error of JSN rate quantification was 0.067 and average osteophyte detection accuracy of the MediAI-OA was 0.84. The accuracy of KL grading was 0.83, and the kappa coefficient between the AI model and ground truth was 0.768, which demonstrated substantial consistency. The OA diagnosis accuracy of this software was 0.92. CONCLUSIONS: The novel DL software known as MediAI-OA demonstrated satisfactory performance comparable to that of experienced orthopedic surgeons and radiologists for analyzing features of knee OA, KL grading and OA diagnosis. Therefore, reliable KL grading can be performed and the burden of the radiologist can be reduced by using MediAI-OA.

Stratifying knee osteoarthritis features through multitask deep hybrid learning: Data from the osteoarthritis initiative.

BACKGROUND AND OBJECTIVE: Knee osteoarthritis (OA) is a debilitating musculoskeletal disorder that causes functional disability. Automatic knee OA diagnosis has great potential of enabling timely and early intervention, that can potentially reverse the degenerative process of knee OA. Yet, it is a tedious task, concerning the heterogeneity of the disorder. Most of the proposed techniques demonstrated single OA diagnostic task widely based on Kellgren Lawrence (KL) standard, a composite score of only a few imaging features (i.e. osteophytes, joint space narrowing and subchondral bone changes). However, only one key disease pattern was tackled. The KL standard fails to represent disease pattern of individual OA features, particularly osteophytes, joint-space narrowing, and pain intensity that play a fundamental role in OA manifestation. In this study, we aim to develop a multitask model using convolutional neural network (CNN) feature extractors and machine learning classifiers to detect nine important OA features: KL grade, knee osteophytes (both knee, medial fibular: OSFM, medial tibial: OSTM, lateral fibular: OSFL, and lateral tibial: OSTL), joint-space narrowing (medial: JSM, and lateral: JSL), and patient-reported pain intensity from plain radiography. METHODS: We proposed a new feature extraction method by replacing fully-connected layer with global average pooling (GAP) layer. A comparative analysis was conducted to compare the efficacy of 16 different convolutional neural network (CNN) feature extractors and three machine learning classifiers. RESULTS: Experimental results revealed the potential of CNN feature extractors in conducting multitask diagnosis. Optimal model consisted of VGG16-GAP feature extractor and KNN classifier. This model not only outperformed the other tested models, it also outperformed the state-of-art methods with higher balanced accuracy, higher Cohen's kappa, higher F1, and lower mean squared error (MSE) in seven OA features prediction. CONCLUSIONS: The proposed model demonstrates pain prediction on plain radiographs, as well as eight OA-related bony features. Future work should focus on exploring additional potential radiological manifestations of OA and their relation to therapeutic interventions.

A deep registration method for accurate quantification of joint space narrowing progression in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to progressive articular destruction and severe disability. Joint space narrowing (JSN) has been regarded as an important indicator for RA progression and has received significant attention. Radiology plays a crucial role in the diagnosis and monitoring of RA through the assessment of joint space. A new framework for monitoring joint space by quantifying joint space narrowing (JSN) progression through image registration in radiographic images has emerged as a promising research direction. This framework offers the advantage of high accuracy; however, challenges still exist in reducing mismatches and improving reliability. In this work, we utilize a deep intra-subject rigid registration network to automatically quantify JSN progression in the early stages of RA. In our experiments, the mean-square error of the Euclidean distance between the moving and fixed images was 0.0031, the standard deviation was 0.0661 mm and the mismatching rate was 0.48%. Our method achieves sub-pixel level accuracy, surpassing manual measurements significantly. The proposed method is robust to noise, rotation and scaling of joints. Moreover, it provides misalignment visualization, which can assist radiologists and rheumatologists in assessing the reliability of quantification, exhibiting potential for future clinical applications. As a result, we are optimistic that our proposed method will make a significant contribution to the automatic quantification of JSN progression in RA. Code is available at https://github.com/pokeblow/Deep-Registration-QJSN-Finger.git.

Baseline knee osteoarthritis radiographic severity as a predictor of symptom response to diet and exercise program: A secondary analysis.

OBJECTIVE: To investigate whether baseline joint space narrowing (JSN) predicted disease remission, knee pain, and physical function changes in persons with knee osteoarthritis (OA). METHODS: This study is a secondary analysis of a two-armed randomized controlled trial. Participants were aged ≥50 years (n = 171) with a body mass index ≥28 kg/m2 and radiographic medial tibiofemoral OA. Participants in the intervention group received diet and exercise programs and special treatment (cognitive behavioral therapy, knee brace, and muscle strengthening exercises) according to the disease remission. Remission of pain and remission of patient global assessment of disease activity and/or functional impairment were used to define the disease remission. The control group were provided with an education pamphlet. The primary outcome was disease remission at 32 weeks, and the secondary outcomes were the changes in knee pain and physical function at 20 and 32 weeks. Baseline JSN was scored from 0 to 3, and the association between baseline JSN and outcomes was assessed using multiple regression. RESULTS: There was no association of baseline JSN with disease remission at 32 weeks when the disease remission has been achieved. The baseline JSN grade 3 was associated with changes in knee pain at 20 weeks (p < .05). There was no association between baseline JSN and physical function. CONCLUSION: Baseline JSN severity predicted changes in knee pain but not the disease remission or changes in physical functions. Identification of baseline radiographic severity may be helpful in identifying differences in response to diet and exercise programs in knee OA.

Lumbosacral fusion increases the risk of hip osteoarthritis.

OBJECTIVE: There may be biomechanical changes in the adjacent hip joint after lumbosacral fusion. The literature has limited information on how these biomechanical changes may result in hip joint space. MATERIAL: METHOD: Our retrospective study examined hip joint space narrowing in patients who underwent lumbosacral fusion between 2020 and 2022. In addition, spinopelvic parameters such as sacral slope, the sagittal vertical axis, pelvic incidence, lumbar lordosis, and pelvic tilt were compared in patients who underwent short-segment (up to three levels, S group) and long-segment (4 and higher levels, L group) fusions. RESULTS: Our study found no significant relationship between spinopelvic parameters and joint space narrowing in the S and L groups. In addition, it was determined that there was more narrowing in the hip joint space in the long-segment group, and there was a positive correlation between the segment length and the narrowing in the hip joint space. CONCLUSION: After lumbosacral fusion, narrowing of the hip joint space was observed. Particularly patients with long-segment lumbosacral fusion should be followed closely regarding hip osteoarthritis risk.

Hands and feet radiologic involvements in systemic sclerosis.

AIM: Systemic sclerosis (SSc) is a rare autoimmune disorder characterized by vascular and fibrosing involvement of the skin and internal organs. In this study, we determined the prevalence and characteristics of radiological hands and feet involvements in Iranian SSc patients to identify the associations between clinical features and radiologic findings. METHODS: 43 SSc patients (41 women and 2 men), with a median age of 44.8 years (ranges 26-70 years) and a mean disease duration of 11.8 years (ranges 2-28 years) were studied in this cross-sectional study. RESULTS: 42 patients had radiological changes both in their hands and feet. Only one patient had alteration just in hand. The most frequent changes that we found in hand were Juxta-articular Osteoporosis (93%), Acro-osteolysis (58.2%), and Joint Space Narrowing (55.8%). The prevalence of joint space narrowing or acro-osteolysis was higher in subjects with active skin involvement [modified Rodnan skin score (mRSS) > 14] [16/21 vs. 4/16 for patients with inactive skin involvement (mRSS < 14); p = 0.002]. The most frequent changes that we found in the foot were Juxta-articular Osteoporosis (93%), Acro-osteolysis (46.5%), Joint Space Narrowing (58.1%), and subluxation (44.2%). The presence of anti-ccp antibody was detected in 4 (9.3%), while positive rheumatoid factor was found in 13 (30.2%) of SSc patients. CONCLUSION: This study corroborates that arthropathy is common in SSc patients. The introduction of the specific radiological involvements of SSc needs to be confirmed by further studies, in order to define the appropriate prognosis and treatment of patients.

A Framework of Faster CRNN and VGG16-Enhanced Region Proposal Network for Detection and Grade Classification of Knee RA.

We developed a framework to detect and grade knee RA using digital X-radiation images and used it to demonstrate the ability of deep learning approaches to detect knee RA using a consensus-based decision (CBD) grading system. The study aimed to evaluate the efficiency with which a deep learning approach based on artificial intelligence (AI) can find and determine the severity of knee RA in digital X-radiation images. The study comprised people over 50 years with RA symptoms, such as knee joint pain, stiffness, crepitus, and functional impairments. The digitized X-radiation images of the people were obtained from the BioGPS database repository. We used 3172 digital X-radiation images of the knee joint from an anterior-posterior perspective. The trained Faster-CRNN architecture was used to identify the knee joint space narrowing (JSN) area in digital X-radiation images and extract the features using ResNet-101 with domain adaptation. In addition, we employed another well-trained model (VGG16 with domain adaptation) for knee RA severity classification. Medical experts graded the X-radiation images of the knee joint using a consensus-based decision score. We trained the enhanced-region proposal network (ERPN) using this manually extracted knee area as the test dataset image. An X-radiation image was fed into the final model, and a consensus decision was used to grade the outcome. The presented model correctly identified the marginal knee JSN region with 98.97% of accuracy, with a total knee RA intensity classification accuracy of 99.10%, with a sensitivity of 97.3%, a specificity of 98.2%, a precision of 98.1%, and a dice score of 90.1% compared with other conventional models.

Radiographically detectable intra-articular mineralization: Predictor of knee osteoarthritis outcomes or only an indicator of aging? A brief report from the osteoarthritis initiative.

Objective: To determine the association between Intra-articular mineralization (IAM) and knee osteoarthritis (OA) outcomes stratified according to participants' age. Methods: Participants from the Osteoarthritis Initiative (OAI) with baseline radiographic OA (i.e., Kellgren-Lawrence grade ≥2 with Osteoarthritis Research Society International (OARSI) atlas joint space narrowing (JSN)) in either knee were identified. Both knees and dominant hand baseline radiographs were evaluated for the presence of IAM. Whole-grade OARSI-JSN radiographic progression and increased Western Ontario and McMaster universities osteoarthritis index scores of the knees with baseline radiographic OA (assessed annually) were defined as radiographic and symptomatic progression, respectively. Cox proportional-hazards and longitudinal multilevel regression models investigated radiographic and symptomatic progression, respectively. Results: 2010 participants with baseline radiographic OA in either one or both knees (N â€‹= â€‹2976) were identified. 178 participants had baseline IAM (hand radiographs â€‹= â€‹46, knee radiographs â€‹= â€‹166, both â€‹= â€‹34). An adjusted logistic regression model suggests an association between age and IAM (Odds Ratio: 1.06, 95% Confidence Interval (CI): 1.04-1.08). Presence of any IAM was not associated with whole-grade OARSI-JSN (Hazard Ratio (HR): 1.00, 95% CI: 0.73-1.37) or symptomatic progression (Estimated difference: 1.24, p-value: 0.13) in all participants. Using stratification analysis, in younger participants <60 years old, presence of any IAM was associated with radiographic progression (HR: 1.90, 95% CI: 1.01-3.60). Conclusion: Although the presence of any radiographic IAM increases with higher age and does not predict knee OA outcomes across the entire sample of OAI participants, it is associated with knee OA radiographic progression in participants aged <60.

Effect of spinal fusion on joint space narrowing of the hip: comparison among non-fusion, short fusion, and middle or long fusion.

BACKGROUND: Lumbar fusion corrects spinal deformities and improves spinal complications. Hip osteoarthritis (OA) is strongly correlated with spinal mobility, and joint space narrowing of the hip after spinal fusion has gained attention. This study aimed to elucidate the effect of spinal fusion on hip joint space narrowing. MATERIALS AND METHODS: We retrospectively examined 530 hips of 270 patients who underwent spinal surgery. All the patients underwent whole-spine radiography before and at the final follow-up. Patients were divided into three groups (N group: non-spinal fusion, S group: up to three interbody fusions, and L group: more than four interbody fusions). The rates of joint space narrowing, spinal parameters (sagittal vertical axis, thoracic kyphosis, lumbar lordosis, sacral slope, pelvic tilt, and pelvic incidence), and limb length discrepancy at the final follow-up were compared. A multilinear regression analysis was performed to identify the risk factors for the rate of joint space narrowing. RESULTS: The rate of joint space narrowing was significantly higher in the L group than in the N and S groups (P < 0.001). No significant difference in the rate of joint space narrowing was observed between the N and S groups. Multiple linear regression analysis revealed that the number of fusion levels (p < 0.05) and follow-up period (p < 0.001) were independent risk factors for joint space narrowing. Spinal parameters at the final follow-up were not independent risk factors. CONCLUSIONS: Long spinal fusion (more than four levels) led to significantly greater joint space narrowing of the hip than short (up to three levels) or no fusion. Spinal alignment did not affect joint space narrowing of the hip. Surgeons should be aware that more than four interbody fusions may result in worse joint space narrowing of the hip. LEVEL OF EVIDENCE: IV, retrospective study.

Anserine bursa palpation tenderness is a risk factor for knee osteoarthritis progression and arthroplasty: data from the Osteoarthritis Initiative.

OBJECTIVE: Anserine bursa pain (ABP) is defined as the presence of palpation tenderness medially below the joint line, which is 2 cm from the tibial tuberosity. This study aimed to determine a link between ABP and three knee outcomes: frequent pain, joint space narrowing (JSN) progression, and total knee arthroplasty (TKA). METHODS: Participants from the Osteoarthritis Initiative cohort were included in this study. Frequent ABP was defined as presenting thrice at four-time points. The Chi-square test and binary logistic regression analyses examined the associations between ABP and the three knee outcomes. Furthermore, Cox Proportional Hazards Model explored the association between ABP and TKA. RESULTS: Baseline ABP was linked to a higher risk of frequent pain (odds ratio (OR): 2.28, 95% confidence interval (CI): 1.76-2.97, P < 0 .001) and TKA (OR: 1.54, 95% CI 1.01-2.36, P = 0 .044) after adjusting for gender, baseline age, body mass index (BMI), and Kellgren-Lawrence (KL) grade. In the frequent ABP group from baseline to the 4-year follow-up (≥ 3 of four-time points), frequent pain (OR: 3.14, 95% CI: 2.34-4.22, P < 0 .001) and TKA (OR: 1.79, 95% CI: 1.11-2.90, P = 0 .017) had a high association with ABP after adjusting for gender, baseline age, BMI, and KL grade. CONCLUSION: This study highlights the association between ABP and knee outcomes; therefore, clinicians should pay closer attention during the physical examination, especially in middle-aged and older female patients. Moreover, understanding ABP cause aids in better diagnosis and treatment. Key Points • This is the first study to identify an association between anserine bursa palpation tenderness and symptomatic knee osteoarthritis. • As opposed to most studies, which focus on intra-articular symptoms and signs, this study focused on extra-articular symptoms and signs. • Clinically, anserine bursa palpation tenderness can be utilized to determine patients at risk for the progression of knee osteoarthritis, thereby aiding in providing early therapeutic intervention.

Quantification of pre-existing radiographic damage and its relationship with joint activity and long-term clinical outcomes with secukinumab therapy in patients with psoriatic arthritis.

BACKGROUND: Psoriatic arthritis (PsA) patient data from two phase 3 secukinumab trials (FUTURE 1, 5) were analysed to quantify the prevalence and extent of pre-existing radiographic damage (RD) at baseline; investigate the association of RD with swollen/tender joint counts (SJC/TJC) at baseline; and investigate the extent to which RD at baseline correlated with response to secukinumab. METHODS: Pooled data (N = 1554) provided baseline radiographic bone erosion and joint space narrowing (JSN) scores at pre-specified locations per the van der Heijde-modified total Sharp score (vdH-mTSS) for PsA and swollen and tender joint scores in the same joints at multiple visits. Overall patient RD and individual joints RD bone erosion and JSN scores were assessed. The association between joint activity (tenderness, swelling) and vdH-mTSS was assessed at the overall patient-level and individual joint tender, swollen scores (yes/no) and RD joint JSN and bone erosion scores at the individual joint-level. Treatment response was assessed using SJC/TJC at weeks 16 and 52 and the proportion of patients achieving minimal disease activity (MDA) over all assessments within 1 year from FUTURE 5 alone. RESULTS: A substantial prevalence of pre-existing RD with higher prevalence of erosion than JSN was observed (86% and 60% of patients had positive erosion and JSN scores, respectively); higher RD prevalence was associated with longer time since PsA diagnosis. Joint activity was weakly associated with RD at baseline at the patient-level (Pearson's coefficients: range 0.12-0.18), but strongly associated at the individual joint-level, with a higher probability of tender/swollen joints to associate with higher JSN/erosion scores: all 42 analysed joints showed statistical significance at the 0.05 level (unadjusted) for the relationship between joint tenderness (yes/no) and its JSN score, all but one for tenderness and bone erosion scores, and all but 2 for swollen and JSN scores and for swollen and bone erosion score. Secukinumab (150/300 mg), reduced TJC and SJC across all values of baseline erosion and JSN scores at weeks 16 and 52. Patients with higher levels of RD were less likely to achieve zero tender/zero swollen joint status and had lower chance of achieving MDA. CONCLUSIONS: PsA patients showed substantial prevalence of RD at baseline that correlated with time since diagnosis, but patient's individual joint activity was strongly associated with pre-existing RD at those joints. Patients with the highest RD at baseline had a reduced likelihood of achieving zero joint count status.

Bisphosphonate use is associated with a decreased joint narrowing rate in the non-arthritic hip.

AIMS: The preventive effects of bisphosphonates on articular cartilage in non-arthritic joints are unclear. This study aimed to investigate the effects of oral bisphosphonates on the rate of joint space narrowing in the non-arthritic hip. METHODS: We retrospectively reviewed standing whole-leg radiographs from patients who underwent knee arthroplasties from 2012 to 2020 at our institute. Patients with previous hip surgery, Kellgren-Lawrence grade ≥ II hip osteoarthritis, hip dysplasia, or rheumatoid arthritis were excluded. The rate of hip joint space narrowing was measured in 398 patients (796 hips), and the effects of the use of bisphosphonates were examined using the multivariate regression model and the propensity score matching (1:2) model. RESULTS: A total of 45 of 398 (11.3%) eligible patients were taking an oral bisphosphonate at the time of knee surgery, with a mean age of 75.8 years (SD 6.2) in bisphosphonate users and 75.7 years (SD 6.8) in non-users. The mean joint space narrowing rate was 0.04 mm/year (SD 0.11) in bisphosphonate users and 0.12 mm/year (SD 0.25) in non-users (p < 0.001). In the multivariate model, age (standardized coefficient = 0.0867, p = 0.016) and the use of a bisphosphonate (standardized coefficient = -0.182, p < 0.001) were associated with the joint space narrowing rate. After successfully matching 43 bisphosphonate users and 86 non-users, the joint narrowing rate was smaller in bisphosphonate users (p < 0.001). CONCLUSION: The use of bisphosphonates is associated with decreased joint degeneration in non-arthritic hips after knee arthroplasty. Bisphosphonates slow joint degeneration, thus maintaining the thickness of joint cartilage in the normal joint or during the early phase of osteoarthritis.Cite this article: Bone Joint Res 2022;11(11):826-834.

Deep Learning-Based Computer-Aided Diagnosis of Rheumatoid Arthritis with Hand X-ray Images Conforming to Modified Total Sharp/van der Heijde Score.

INTRODUCTION: Rheumatoid arthritis (RA) is a systemic autoimmune disease; early diagnosis and treatment are crucial for its management. Currently, the modified total Sharp score (mTSS) is widely used as a scoring system for RA. The standard screening process for assessing mTSS is tedious and time-consuming. Therefore, developing an efficient mTSS automatic localization and classification system is of urgent need for RA diagnosis. Current research mostly focuses on the classification of finger joints. Due to the insufficient detection ability of the carpal part, these methods cannot cover all the diagnostic needs of mTSS. METHOD: We propose not only an automatic label system leveraging the You Only Look Once (YOLO) model to detect the regions of joints of the two hands in hand X-ray images for preprocessing of joint space narrowing in mTSS, but also a joint classification model depending on the severity of the mTSS-based disease. In the image processing of the data, the window level is used to simulate the processing method of the clinician, the training data of the different carpal and finger bones of human vision are separated and integrated, and the resolution is increased or decreased to observe the changes in the accuracy of the model. RESULTS: Integrated data proved to be beneficial. The mean average precision of the proposed model in joint detection of joint space narrowing reached 0.92, and the precision, recall, and F1 score all reached 0.94 to 0.95. For the joint classification, the average accuracy was 0.88, and the accuracy of severe, mild, and healthy reached 0.91, 0.79, and 0.9, respectively. CONCLUSIONS: The proposed model is feasible and efficient. It could be helpful for subsequent research on computer-aided diagnosis in RA. We suggest that applying the one-hand X-ray imaging protocol can improve the accuracy of mTSS classification model in determining mild disease if it is used in clinical practice.