The interactions between MRI-detected osteophytes and bone marrow lesions or effusion-synovitis on knee symptom progression: an exploratory study

Radiomics analysis using magnetic resonance imaging of bone marrow edema for diagnosing knee osteoarthritis

This study aimed to develop and validate a bone marrow edema model using a magnetic resonance imaging-based radiomics nomogram for the diagnosis of osteoarthritis. Clinical and magnetic resonance imaging (MRI) data of 302 patients with and without osteoarthritis were retrospectively collected from April 2022 to October 2023 at Longhua Hospital affiliated with the Shanghai University of Traditional Chinese Medicine. The participants were randomly divided into two groups (a training group, n = 211 and a testing group, n = 91). We used logistic regression to analyze clinical characteristics and established a clinical model. Radiomics signatures were developed by extracting radiomic features from the bone marrow edema area using MRI. A nomogram was developed based on the rad-score and clinical characteristics. The diagnostic performance of the three models was compared using the receiver operating characteristic curve and Delong's test. The accuracy and clinical application value of the nomogram were evaluated using calibration curve and decision curve analysis. Clinical characteristics such as age, radiographic grading, Western Ontario and McMaster Universities Arthritis Index score, and radiological features were significantly correlated with the diagnosis of osteoarthritis. The Rad score was constructed from 11 radiological features. A clinical model was developed to diagnose osteoarthritis (training group: area under the curve [AUC], 0.819; testing group: AUC, 0.815). Radiomics models were used to effectively diagnose osteoarthritis (training group,: AUC, 0.901; testing group: AUC, 0.841). The nomogram model composed of Rad score and clinical characteristics had better diagnostic performance than a simple clinical model (training group: AUC, 0.906; testing group: AUC, 0.845; p < 0.01). Based on DCA, the nomogram model can provide better diagnostic performance in most cases. In conclusion, the MRI-bone marrow edema-based radiomics-clinical nomogram model showed good performance in diagnosing early osteoarthritis.

Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning

OBJECTIVES

To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagittal proton density-weighted images and to distinguish between three common types of knee synovitis.

MATERIALS AND METHODS

This retrospective study included 376 consecutive patients with pathologically confirmed knee synovitis (rheumatoid arthritis, gouty arthritis, and pigmented villonodular synovitis) from two institutions. A semantic segmentation model was trained on manually annotated sagittal proton density-weighted images. The segmentation results of the regions of interest and patients' sex and age were used to classify knee synovitis after feature processing. Classification by the DL method was compared to the classification performed by radiologists.

RESULTS

Data of the 376 patients (mean age, 42 ± 15 years; 216 men) were separated into a training set (n = 233), an internal test set (n = 93), and an external test set (n = 50). The automated segmentation model showed good performance (mean accuracy: 0.99 and 0.99 in the internal and external test sets). On the internal test set, the DL model performed better than the senior radiologist (accuracy: 0.86 vs. 0.79; area under the curve [AUC]: 0.83 vs. 0.79). On the external test set, the DL diagnostic model based on automatic segmentation performed as well or better than senior and junior radiologists (accuracy: 0.79 vs. 0.79 vs. 0.73; AUC: 0.76 vs. 0.77 vs. 0.70).

CONCLUSION

DL models for segmentation of SC and IPFD can accurately classify knee synovitis and aid radiologic diagnosis.

Association of biochemical markers with bone marrow lesion changes on imaging-data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium

BACKGROUND

To assess the prognostic value of short-term change in biochemical markers as it relates to bone marrow lesions (BMLs) on MRI in knee osteoarthritis (OA) over 24 months and, furthermore, to assess the relationship between biochemical markers involved with tissue turnover and inflammation and BMLs on MRI.

METHODS

Data from the Foundation for the National Institutes of Health OA Biomarkers Consortium within the Osteoarthritis Initiative (n = 600) was analyzed. BMLs were measured according to the MRI Osteoarthritis Knee Score (MOAKS) system (0-3), in 15 knee subregions. Serum and urinary biochemical markers assessed were as follows: serum C-terminal crosslinked telopeptide of type I collagen (CTX-I), serum crosslinked N-telopeptide of type I collagen (NTX-I), urinary CTX-Iα and CTX-Iβ, urinary NTX-I, urinary C-terminal cross-linked telopeptide of type II collagen (CTX-II), serum matrix metalloproteinase (MMP)-degraded type I, II, and III collagen (C1M, C2M, C3M), serum high sensitivity propeptide of type IIb collagen (hsPRO-C2), and matrix metalloproteinase-generated neoepitope of C-reactive protein (CRPM). The association between change in biochemical markers over 12 months and BMLs over 24 months was examined using regression models adjusted for covariates. The relationship between C1M, C2M, C3M, hsPRO-C2, and CRPM and BMLs at baseline and over 24 months was examined.

RESULTS

Increases in serum CTX-I and urinary CTX-Iβ over 12 months were associated with increased odds of changes in the number of subregions affected by any BML at 24 months. Increase in hsPRO-C2 was associated with decreased odds of worsening in the number of subregions affected by any BML over 24 months. C1M and C3M were associated with BMLs affected at baseline.

CONCLUSIONS

Short-term changes in serum CTX-I, hsPRO-C2, and urinary CTX-Iβ hold the potential to be prognostic of BML progression on MRI. The association of C1M and C3M with baseline BMLs on MRI warrants further investigation.

Bone marrow lesions in osteoarthritis: From basic science to clinical implications

Osteoarthritis (OA) is the most prevalent musculoskeletal disease characterized by multiple joint structure damages, including articular cartilage, subchondral bone and synovium, resulting in disability and economic burden. Bone marrow lesions (BMLs) are common and important magnetic resonance imaging (MRI) features in OA patients. Basic and clinical research on subchondral BMLs in the pathogenesis of OA has been a hotspot. New evidence shows that subchondral bone degeneration, including BML and angiogenesis, occurs not only at or after cartilage degeneration, but even earlier than cartilage degeneration. Although BMLs are recognized as important biomarkers for OA, their exact roles in the pathogenesis of OA are still unclear, and disputes about the clinical impact and treatment of BMLs remain. This review summarizes the current basic and clinical research progress of BMLs. We particularly focus on molecular pathways, cellular abnormalities and microenvironmental changes of subchondral bone that contributed to the formation of BMLs, and emphasize the crosstalk between subchondral bone and cartilage in OA development. Finally, potential therapeutic strategies targeting BMLs in OA are discussed, which provides novel strategies for OA treatment.

Factors associated with subjective knee joint stiffness in people with knee osteoarthritis: A systematic review

INTRODUCTION

Subjective knee stiffness is a common symptom in patients with knee osteoarthritis treated conservatively. However, the influencing factors or effects of knee joint stiffness are unknown. The aim of this study was to explore the factors associated with subjective knee stiffness in patients with knee osteoarthritis.

METHODS

The MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Web of Science, and PEDro databases were searched in November 2021. Prospective or retrospective cohort studies were included. The methodological quality of the selected articles was assessed using the Scottish Intercollegiate Guidelines Network checklist.

RESULTS

Twenty out of 1943 screened articles were included in this systematic review. Eighteen and two studies were rated as having acceptable and low quality, respectively. All the included studies measured subjective knee stiffness using the Western Ontario and McMaster Universities Osteoarthritis Index. The main findings were that worse preoperative subjective knee stiffness was associated with worse pain, subjective knee stiffness, and patient satisfaction at 1 year after total knee arthroplasty. In addition, worse subjective knee stiffness was associated with future degenerative changes in the knee joint, such as joint space narrowing and osteophyte growth progression.

CONCLUSION

Subjective knee stiffness may be associated with the prognosis after total knee arthroplasty and degenerative changes in the knee joint. Early detection and treatment of knee stiffness could lead to a good prognosis after total knee arthroplasty and prevent the progression of degenerative changes in the knee joint.