The role of radiography and MRI for eligibility assessment in DMOAD trials of knee OA

Contralateral knee osteoarthritis severity relates to magnetic resonance imaging findings in knees with and without osteoarthritis: Data from the osteoarthritis initiative

Objective

We explored whether a magnetic resonance imaging (MRI)-based composite score of bone marrow lesion and effusion-synovitis volumes related to contralateral knee osteoarthritis disease severity.

Design

Using data from the Osteoarthritis Initiative, we conducted cross-sectional knee-based analyses among participants with bilateral knee MRIs and at least one knee with Kellgren-Lawrence (KL) grade ≥1 and a WOMAC pain score ≥10/100 (n ​= ​693). Bone marrow lesion and effusion-synovitis volumes on MRIs were used to calculate a composite score ("disease activity"). We divided the disease activity score into tertiles. We used multinomial logistic models to explore the association between disease activity in knees with and without radiographic osteoarthritis (outcome) and the contralateral disease severity (KL grade or disease activity; exposure).

Results

We included 1386 knees from participants with an average age of 62 (standard deviation ​= ​9) years. Most participants were overweight and had mild-to-moderate radiographic osteoarthritis. Disease activity among knees without radiographic osteoarthritis had statistically significant relationships with contralateral disease activity (range of odds ratios: 4.86-23.22) but not contralateral KL grade (range of odds ratios: 0.86-1.01). Disease activity among knees with radiographic osteoarthritis had statistically significant relationships with contralateral disease activity and KL grade; however, the association was stronger for contralateral disease activity than KL grade (range of odds ratios: 3.67-21.29 versus 1.96-2.20).

Conclusion

Structural findings in one knee may relate to structural findings in the other knee. This highlights the need for future studies to explore how the contralateral knee could impact clinical trial screening, monitoring, and intervention strategies, especially when testing localized therapies.

Phenotypic variations in knee osteoarthritis: insights from MRI and radiographic comparisons

OBJECTIVE

To investigate the correlation between MRI-based phenotypes (cartilage-meniscus, subchondral bone, and inflammatory) and radiography-based atrophic and hypertrophic phenotypes, aiming to demonstrate MRI's diagnostic capability in identifying complex osteoarthritis phenotypes that radiography cannot fully capture.

MATERIALS AND METHODS

This single-center retrospective study examined knee radiographs and MRIs of patients from November 2021 to April 2023 to identify osteoarthritis phenotypes. Radiographs were staged by the Kellgren-Lawrence system, and both modalities were classified into atrophic or hypertrophic phenotypes. MRIs were further classified into three phenotypes: cartilage-meniscus, subchondral bone, and inflammatory. Associations between phenotypes, Kellgren-Lawrence stage, age, and gender were analyzed with Pearson chi-square test and student T-test. Reliability measurements were evaluated using kappa statistic.

RESULTS

A total of 214 knees from 187 individuals (73.3% women, 26.7% men; mean age 57.1 ± 9.1 years) were included. The hypertrophic MRI phenotype was significantly associated with cartilage-meniscus and subchondral bone phenotypes (p < 0.001). Cartilage-meniscus and subchondral bone phenotypes were less prevalent in Kellgren-Lawrence stage 2 than in stages 3 and 4 (p < 0.001 and p = 0.004, respectively). The subchondral bone phenotype was more common in men (p = 0.022), and the cartilage-meniscus phenotype in the elderly (p < 0.001). Radiography and MRI had substantial agreement (Kappa = 0.637, p < 0.001) in diagnosing hypertrophic and atrophic phenotypes.

CONCLUSION

The hypertrophic phenotype was associated with cartilage-meniscus and subchondral bone phenotypes, with lower prevalences in Kellgren-Lawrence stage 2 knees. MRI offers enhanced phenotypic characterization, which facilitates more precise and individualized management in osteoarthritis care. Despite limitations compared to MRI, radiography remains valuable for the evaluation of hypertrophic and atrophic phenotypes.

Arthroscopy has a higher discriminative capacity than MRI in detecting mild cartilage lesions

OBJECTIVES

To determine whether current MRI could detect superficial cartilage lesions that are observed in patients with knee pain for whom arthroscopy was indicated for therapeutic reasons or when the cause of pain was unclear.

METHODS

Adult patients with knee pain lasting more than 3 months, scheduled for a therapeutic/diagnostic arthroscopy, were recruited. Demographic and clinical data, pain assessment, MRI imaging and observations of cartilage damage in the medial femoral condyle during arthroscopic procedure were documented. Patients were categorized based on the presence of cartilage damage assessed via MRI and/or direct visualization. Concordance between these assessments and its variation with age and patient-reported pain were examined.

RESULTS

Out of the 95 patients recruited, 48 exhibited lesions in the medial femoral condyle (MFC) during arthroscopic examination, while only 24 of them showed lesions on the MRI scans. The thickness of the cartilage in the MFC was significantly lower in patients with cartilage damage detected by MRI compared with those without. Among patients with cartilage lesions identified during arthroscopy, those also showing lesions on the MRI had lower cartilage thickness and higher Outerbridge score than those without lesions on the MRI. Patients with detectable cartilage damage on the MRI were significantly older and reported higher levels of pain than those with damage detected only by arthroscopic examination.

CONCLUSION

Despite significant technological advancements in MRI, arthroscopy still proves superior in identifying mild structural cartilage lesions that are not identifiable by this technique.

Cathepsin K Inhibitors as Potential Drugs for the Treatment of Osteoarthritis

Links between cathepsin K and the pathophysiology of osteoarthritis (OA) can be established, not least because of the overabundance of cathepsin K in the serum of OA patients and the upregulation of cathepsin K in degraded cartilage in animal models of OA. Chondrocytes, chondroclasts, or osteoclasts contribute to the accumulated cathepsin K at the diseased osteochondral junction. After a general presentation of OA and cartilage physiology, as well as its degradation processes, we describe the function of cathepsin K and its effect on cartilage degradation via type II collagen cleavage. An overview of the most promising cathepsin K inhibitors is then presented, together with their in vitro effects. Although intensive research on cathepsin K inhibitors initially focused on bone resorption, there is growing interest in the potential of these drugs to prevent cartilage degradation. In this review, we summarize the pre-clinical and clinical trials that support the use of cathepsin K inhibitors in the treatment of OA. To date, no molecules of this type are commercially available, although a few have undergone clinical trials, but we believe that the development of cathepsin K inhibitors could broaden the therapeutic arsenal for the treatment of OA.

Frontal plane mechanical leg alignment estimation from knee x-rays using deep learning

Objective

Lower limb malalignment can complicate symptoms and accelerate knee osteoarthritis (OA), necessitating consideration in study population selection. In this study, we develop and validate a deep learning model that classifies leg alignment as "normal" or "malaligned" from knee antero-posterior (AP)/postero-anterior (PA) radiographs alone, using an adjustable hip-knee-ankle (HKA) angle threshold.

Material and methods

We utilized 8878 digital radiographs, including 6181 AP/PA full-leg x-rays (LLRs) and 2697 AP/PA knee x-rays (2292 with positioning frame, 405 without). The model's evaluation involved two steps: In step 1, the model's predictions on knee images cropped from LLRs were compared against the ground truth from the original LLRs. In step 2, the model was tested on knee AP radiographs, using corresponding same-day LLRs as a proxy for ground truth.

Results

The model effectively classified alignment, with step one achieving sensitivity and specificity of 0.92 for a threshold of 7.5°, and 0.90 and 0.85 for 5°. For positioning frame images, step two showed a sensitivity of 0.85 and specificity of 0.81 for 7.5°, and 0.79 and 0.74 for 5°. For non-positioning frame images, sensitivity and specificity were 0.91 and 0.83 for 7.5°, and 0.9 and 0.86 for 5°.

Conclusion

The model developed in this study accurately classifies lower limb malalignment from AP/PA knee radiographs using adjustable thresholds, offering a practical alternative to LLRs. This can enhance the precision of study population selection and patient management.

Integration of longitudinal load-bearing tissue MRI radiomics and neural network to predict knee osteoarthritis incidence

Background

Load-bearing structural degradation is crucial in knee osteoarthritis (KOA) progression, yet limited prediction models use load-bearing tissue radiomics for radiographic (structural) KOA incident.

Purpose

We aim to develop and test a Load-Bearing Tissue plus Clinical variable Radiomic Model (LBTC-RM) to predict radiographic KOA incidents.

Study design

Risk prediction study.

Methods

The 700 knees without radiographic KOA at baseline were included from Osteoarthritis Initiative cohort. We selected 2164 knee MRIs during 4-year follow-up. LBTC-RM, which integrated MRI features of meniscus, femur, tibia, femorotibial cartilage, and clinical variables, was developed in total development cohort (n = 1082, 542 cases vs. 540 controls) using neural network algorithm. Final predictive model was tested in total test cohort (n = 1082, 534 cases vs. 548 controls), which integrated data from five visits: baseline (n = 353, 191 cases vs. 162 controls), 3 years prior KOA (n = 46, 19 cases vs. 27 controls), 2 years prior KOA (n = 143, 77 cases vs. 66 controls), 1 year prior KOA (n = 220, 105 cases vs. 115 controls), and at KOA incident (n = 320, 156 cases vs. 164 controls).

Results

In total test cohort, LBTC-RM predicted KOA incident with AUC (95 % CI) of 0.85 (0.82-0.87); with LBTC-RM aid, performance of resident physicians for KOA prediction were improved, with specificity, sensitivity, and accuracy increasing from 50 %, 60 %, and 55 %-72 %, 73 %, and 72 %, respectively. The LBTC-RM output indicated an increased KOA risk (OR: 20.6, 95 % CI: 13.8-30.6, p < .001). Radiomic scores of load-bearing tissue raised KOA risk (ORs: 1.02-1.9) from 4-year prior KOA whereas 3-dimensional feature score of medial meniscus decreased the OR (0.99) of KOA incident at KOA confirmed. The 2-dimensional feature score of medial meniscus increased the ORs (1.1-1.2) of KOA symptom score from 2-year prior KOA.

Conclusions

We provided radiomic features of load-bearing tissue to improved KOA risk level assessment and incident prediction. The model has potential clinical applicability in predicting KOA incidents early, enabling physicians to identify high-risk patients before significant radiographic evidence appears. This can facilitate timely interventions and personalized management strategies, improving patient outcomes.

The Translational Potential of this Article

This study presents a novel approach integrating longitudinal MRI-based radiomics and clinical variables to predict knee osteoarthritis (KOA) incidence using machine learning. By leveraging deep learning for auto-segmentation and machine learning for predictive modeling, this research provides a more interpretable and clinically applicable method for early KOA detection. The introduction of a Radiomics Score System enhances the potential for radiomics as a virtual image-based biopsy tool, facilitating non-invasive, personalized risk assessment for KOA patients. The findings support the translation of advanced imaging and AI-driven predictive models into clinical practice, aiding early diagnosis, personalized treatment planning, and risk stratification for KOA progression. This model has the potential to be integrated into routine musculoskeletal imaging workflows, optimizing early intervention strategies and resource allocation for high-risk populations. Future validation across diverse cohorts will further enhance its clinical utility and generalizability.

A multi-model approach identifies ALW-II-41-27 as a promising therapy for osteoarthritis-associated inflammation and endochondral ossification

Low-grade inflammation and pathological endochondral ossification are key processes underlying the progression of osteoarthritis, the most prevalent joint disease worldwide. In this study, we employed a multi-faceted approach, integrating publicly available datasets, in silico analyses, in vitro experiments and in vivo models to identify new therapeutic candidates targeting these processes. Data mining of transcriptomic datasets identified EPHA2, a receptor tyrosine kinase associated with cancer, as being linked to both inflammation and endochondral ossification in osteoarthritis. A computational model of cellular signaling networks in chondrocytes predicted that in silico activation of EPHA2 in healthy chondrocytes increases inflammatory mediators and induces hypertrophic differentiation, a hallmark of endochondral ossification. We then evaluated the effect of EPHA2 inhibition using the tyrosine kinase inhibitor ALW-II-41-27 in cultured human chondrocytes from individuals with osteoarthritis, demonstrating significant reductions in both inflammation and hypertrophy. Additionally, systemic subcutaneous administration of ALW-II-41-27 in a mouse osteoarthritic model attenuated joint degeneration by reducing local inflammation and pathological endochondral ossification. Collectively, this study demonstrates a novel drug discovery pipeline that integrates computational, experimental, and animal models, paving the way for the development of disease-modifying treatments for osteoarthritis.

Association of MRI-based knee osteoarthritis structural phenotypes with short-term structural progression and subsequent total knee replacement

BACKGROUND

The failure of disease-modifying osteoarthritis drugs (DMOADs) trials lies mainly in the heterogeneity of the disease, which calls for a more precise population with specific progression and outcomes. This study aimed to determine whether and which MRI-based structural phenotype of knee osteoarthritis (KOA) is associated with short-term structural progression and subsequent total knee replacement (TKR).

METHODS

A longitudinal study was conducted among participants with baseline Kellgren-Lawrence grade (KLG) ≥ 2 from the Osteoarthritis Initiative (OAI). The structural phenotypes at baseline were defined as subchondral bone, meniscus/cartilage and inflammatory phenotypes according to the MRI Osteoarthritis Knee Score (MOAKS). The primary outcome was the progression of structural abnormalities within 24 months and multivariable logistic regressions were applied to evaluate the associations. The secondary outcome was the incidence of TKR during 108 months. Cox regressions and Kaplan-Meier survival curves were used for the analysis.

RESULTS

A total of 733 participants with KOA were finally included in our study, with 493 (67.3%) having the three main structural phenotypes. For the primary outcome, the subchondral bone phenotype (OR [95% CI]:1.71 [1.02, 2.83], 1.52 [1.06, 2.18], 1.65 [1.11, 2.42], respectively) and the inflammatory phenotype (OR [95% CI]: 1.69 [1.05, 2.74], 1.82 [1.31, 2.52], 2.15 [1.48, 3.14], respectively) were both associated with the short-term progression of joint space narrowing, osteophytes and sclerosis in 24 months, whereas the meniscus/cartilage phenotype was only associated with the progression of osteophytes and sclerosis. For the secondary outcome, the subchondral bone phenotype (HR [95% CI]: 1.71 [1.06-2.78]) and inflammatory phenotype (HR [95%CI]: 2.00 [1.02-2.67]) were associated with shorter time to subsequent TKR, but not the meniscus/cartilage phenotype. Besides, the cumulative effect when the structural phenotype overlapped was confirmed in both outcomes.

CONCLUSIONS

The subchondral bone phenotype and inflammatory phenotype were associated with the progression of joint space narrowing, osteophytes and sclerosis in 24 months, along with subsequent TKR in 108 months. Besides, additive effects of overlapped phenotypes were further determined. These phenotypes could serve as valuable screening tools for future clinical trials and provide guidance for risk evaluation.

Relationship between Feline Knee Joint Osteoarthritis and Bone Mineral Density Quantified Using Computed Tomography and Computed Digital Absorptiometry

Osteoarthritis (OA), including knee joint OA, is a common chronic condition in cats. In both cats and humans, knee joint OA is characterized radiographically by the presence of osteophytes, enthesiophytes, subchondral sclerosis, and joint space narrowing. However, only in humans have these radiographic signs been reported to increase bone mineral density (BMD). Therefore, this study aims to quantify the volumetric (vBMD) and relative (rBMD) BMD measures of the feline knee joint and compare BMD measures between various severities of OA to test the hypothesized OA-BMD relationship in the knee joint in cats. The 46 feline knee joints were imaged using computed tomography (CT) and conventional radiography supported by the computed digital absorptiometry (CDA) method to obtain vBMD and rBMD, respectively. Both BMD measures were assessed in three regions of interest (ROIs): the distal femur (ROI 1), patella (ROI 2), and proximal tibia (ROI 3). In all locations, vBMD and rBMD showed moderate (ROI 2: r = 0.67, p < 0.0001) to strong (ROI 1: ρ = 0.96, p < 0.0001; ROI 3: r = 0.89, p < 0.0001) positive correlations. Due to differences (p < 0.0001) in the width of the distal femur (17.9 ± 1.21 mm), patella (8.2 ± 0.82 mm), and proximal tibia (19.3 ± 1.16 mm), the rBMD was corrected (corr rBMD) using the thickness coefficient of 0.46 ± 0.04 for ROI 2 and 1.08 ± 0.03 for ROI 3. Regardless of the quantification method used, BMD measures increased linearly from a normal knee joint to severe OA, with differences in BMD between normal and mild to severe knee joint OA. The OA-BMD relationship in the feline knee joint can be preliminarily confirmed.

Investigating the relationship between radiographic joint space width loss and deep learning-derived magnetic resonance imaging-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint

Objective

To investigate the relationship between measures of radiographic joint space width (JSW) loss and magnetic resonance imaging (MRI)-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint over 12-24 months. To stratify this relationship by clinically meaningful subgroups (sex and pain status).

Design

We analyzed a subset of knees (n ​= ​256) from the Osteoarthritis Initiative (OAI) likely in early stage OA based on joint space narrowing (JSN) measurements. Natural logarithm transformation was used to approximate near normal distributions for JSW loss. Pearson Correlation coefficients described the relationship between ln-transformed JSW loss and several versions of deep learning-derived MRI-based cartilage thickness loss parameters (minimum, maximum, and mean) in subregions of the femoral condyle, tibial plateau, and combined femoral and tibial regions. Linear mixed-effects models evaluated the associations between the ln-transformed radiographic and MRI-derived measures including potential confounders.

Results

We found weak correlations between ln-transformed JSW loss and MRI-based cartilage thickness ranging from R ​= ​-0.13 (p ​= ​0.20) to R ​= ​0.26 (p ​< ​0.01). Correlations were higher (still poor) among females compared to males and painful compared to non-painful knees. Model results showed weak associations for nearly all MRI-based measures, ranging from no association to β (95% CI) ​= ​0.25 (0.11, 0.39). Associations were higher among females compared to males and minimal differences between painful and non-painful knees.

Conclusions

Despite its recommended use in disease-modifying OA drug clinical trials, results suggest that JSW loss is an ineffective proxy measure of cartilage thickness loss over 12-24 months and within a localized region of the tibiofemoral joint.

Integrating Radiomics and Neural Networks for Knee Osteoarthritis Incidence Prediction

OBJECTIVE

Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test a magnetic resonance imaging (MRI)-based joint space (JS) radiomic model (RM) to predict radiographic KOA incidence through neural networks by integrating meniscus and femorotibial cartilage radiomic features.

METHODS

In the Osteoarthritis Initiative cohort, participants with knees without radiographic KOA at baseline but at high risk for radiographic KOA were included. Patients' knees developed radiographic KOA, whereas control knees did not over four years. We randomly split the participants into development and test cohorts (8:2) and extracted features from baseline three-dimensional double-echo steady-state sequence MRI. Model performance was evaluated using an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity in both cohorts. Nine resident surgeons performed the reader experiment without/with the JS-RM aid.

RESULTS

Our study included 549 knees in the development cohort (275 knees of patients with KOA vs 274 knees of controls) and 137 knees in the test cohort (68 knees of patients with KOA vs 69 knees of controls). In the test cohort, JS-RM had a favorable accuracy for predicting the radiographic KOA incidence with an AUC of 0.931 (95% confidence interval [CI] 0.876-0.963), a sensitivity of 84.4% (95% CI 83.9%-84.9%), and a specificity of 85.6% (95% CI 85.2%-86.0%). The mean specificity and sensitivity of resident surgeons through MRI reading in predicting radiographic KOA incidence were increased from 0.474 (95% CI 0.333-0.614) and 0.586 (95% CI 0.429-0.743) without the assistance of JS-RM to 0.874 (95% CI 0.847-0.901) and 0.812 (95% CI 0.742-0.881) with JS-RM assistance, respectively (P < 0.001).

CONCLUSION

JS-RM integrating the features of the meniscus and cartilage showed improved predictive values in radiographic KOA incidence.

Ultrasound Imaging in Knee Osteoarthritis: Current Role, Recent Advancements, and Future Perspectives

While conventional radiography and MRI have a well-established role in the assessment of patients with knee osteoarthritis, ultrasound is considered a complementary and additional tool. Moreover, the actual usefulness of ultrasound is still a matter of debate in knee osteoarthritis assessment. Despite that, ultrasound offers several advantages and interesting aspects for both current clinical practice and future perspectives. Ultrasound is potentially a helpful tool in the detection of anomalies such as cartilage degradation, osteophytes, and synovitis in cases of knee osteoarthritis. Furthermore, local diagnostic and minimally invasive therapeutic operations pertaining to knee osteoarthritis can be safely guided by real-time ultrasound imaging. We are constantly observing a growing knowledge and awareness among radiologists and other physicians, concerning ultrasound imaging. Ultrasound studies can be extremely useful to track the response to various therapies. For this specific aim, tele-ultrasonography may constitute an easy tool aiding precise and repeated follow-up controls. Moreover, raw radio-frequency data from US backscattering signals contain more information than B-mode imaging. This paves the way for quantitative in-depth analyses of cartilage, bone, and other articular structures. Overall, ultrasound technologies and their rapid evolution have the potential to make a difference at both the research and clinical levels. This narrative review article describes the potential of such technologies and their possible future implications.

Prospects of Disease-Modifying Osteoarthritis Drugs

Osteoarthritis (OA) causes a massive disease burden with a global prevalence of nearly 23% in 2020 and an unmet need for adequate treatment, given a lack of disease-modifying drugs (DMOADs). The author reviews the prospects of active DMOAD candidates in the phase 2/3 clinical trials of drug development pipeline based on key OA pathogenetic mechanisms directed to inflammation-driven, bone-driven, and cartilage-driven endotypes. The challenges and possible research opportunities are stated in terms of the formulation of a research question known as the PICO approach: (1) population, (2) interventions, (3) comparison or placebo, and (4) outcomes.

Identifying significant structural factors associated with knee pain severity in patients with osteoarthritis using machine learning

Our main objective was to use machine learning methods to identify significant structural factors associated with pain severity in knee osteoarthritis patients. Additionally, we assessed the potential of various classes of imaging data using machine learning techniques to gauge knee pain severity. The data of semi-quantitative assessments of knee radiographs, semi-quantitative assessments of knee magnetic resonance imaging (MRI), and MRI images from 567 individuals in the Osteoarthritis Initiative (OAI) were utilized to train a series of machine learning models. Models were constructed using five machine learning methods: random forests (RF), support vector machines (SVM), logistic regression (LR), decision tree (DT), and Bayesian (Bayes). Employing tenfold cross-validation, we selected the best-performing models based on the area under the curve (AUC). The study results indicate no significant difference in performance among models using different imaging data. Subsequently, we employed a convolutional neural network (CNN) to extract features from magnetic resonance imaging (MRI), and class activation mapping (CAM) was utilized to generate saliency maps, highlighting regions associated with knee pain severity. A radiologist reviewed the images, identifying specific lesions colocalized with the CAM. The review of 421 knees revealed that effusion/synovitis (30.9%) and cartilage loss (30.6%) were the most frequent abnormalities associated with pain severity. Our study suggests cartilage loss and synovitis/effusion lesions as significant structural factors affecting pain severity in patients with knee osteoarthritis. Furthermore, our study highlights the potential of machine learning for assessing knee pain severity using radiographs.

Approaches to optimize analyses of multidimensional ordinal MRI data in osteoarthritis research: A perspective

Objective

Knee osteoarthritis (OA) is a disease of the whole joint involving multiple tissue types. MRI-based semi-quantitative (SQ) scoring of knee OA is a method to perform multi-tissue joint assessment and has been shown to be a valid and reliable way to measure structural multi-tissue involvement and progression of the disease. While recent work has described how SQ scoring may be used for clinical trial enrichment and disease phenotyping in OA, less guidance is available for how these parameters may be used to assess study outcomes.

Design

Here we present recommendations for summarizing disease progression within specific tissue types. We illustrate how various methods may be used to quantify longitudinal change using SQ scoring and review examples from the literature.

Results

Approaches to quantify longitudinal change across subregions include the count of number of subregions, delta-subregion, delta-sum, and maximum grade changes. Careful attention should be paid to features that may fluctuate, such as bone marrow lesions, or with certain interventions, for example pharmacologic interventions with anticipated cartilage anabolic effects. The statistical approach must align with the nature of the outcome.

Conclusions

SQ scoring presents a way to understand disease progression across the whole joint. As OA is increasingly recognized as a heterogeneous disease with different phenotypes a better understanding of longitudinal progression across tissue types may present an opportunity to match study outcome to patient phenotype or to treatment mechanism of action.

Extracellular vesicles derived from mesenchymal stem cells mediate extracellular matrix remodeling in osteoarthritis through the transport of microRNA-29a

BACKGROUND

Knee osteoarthritis (KOA) is a common orthopedic condition with an uncertain etiology, possibly involving genetics and biomechanics. Factors like changes in chondrocyte microenvironment, oxidative stress, inflammation, and immune responses affect KOA development. Early-stage treatment options primarily target symptom relief. Mesenchymal stem cells (MSCs) show promise for treatment, despite challenges. Recent research highlights microRNAs (miRNAs) within MSC-released extracellular vesicles that can potentially promote cartilage regeneration and hinder KOA progression. This suggests exosomes (Exos) as a promising avenue for future treatment. While these findings emphasize the need for effective KOA progression management, further safety and efficacy validation for Exos is essential.

AIM

To explore miR-29a's role in KOA, we'll create miR-29a-loaded vesicles, testing for early treatment in rat models.

METHODS

Extraction of bone marrow MSC-derived extracellular vesicles, preparation of engineered vesicles loaded with miR-29a using ultrasonication, and identification using quantitative reverse transcription polymerase chain reaction; after establishing a rat model of KOA, rats were randomly divided into three groups: Blank control group injected with saline, normal extracellular vesicle group injected with normal extracellular vesicle suspension, and engineered extracellular vesicle group injected with engineered extracellular vesicle suspension. The three groups were subjected to general behavioral observation analysis, imaging evaluation, gross histological observation evaluation, histological detection, and immunohistochemical detection to compare and evaluate the progress of various forms of arthritis.

RESULTS

General behavioral observation results showed that the extracellular vesicle group and engineered extracellular vesicle group had better performance in all four indicators of pain, gait, joint mobility, and swelling compared to the blank control group. Additionally, the engineered extracellular vesicle group had better pain relief at 4 wk and better knee joint mobility at 8 wk compared to the normal extracellular vesicle group. Imaging examination results showed that the blank control group had the fastest progression of arthritis, the normal extracellular vesicle group had a relatively slower progression, and the engineered extracellular vesicle group had the slowest progression. Gross histological observation results showed that the blank control group had the most obvious signs of arthritis, the normal extracellular vesicle group showed signs of arthritis, and the engineered extracellular vesicle group showed no significant signs of arthritis. Using the Pelletier gross score evaluation, the engineered extracellular vesicle group had the slowest progression of arthritis. Results from two types of staining showed that the articular cartilage of rats in the normal extracellular vesicle and engineered extracellular vesicle groups was significantly better than that of the blank control group, and the engineered extracellular vesicle group had the best cartilage cell and joint surface condition. Immunohistochemical detection of type II collagen and proteoglycan showed that the extracellular matrix of cartilage cells in the normal extracellular vesicle and engineered extracellular vesicle groups was better than that of the blank control group. Compared to the normal extracellular vesicle group, the engineered extracellular vesicle group had a better regulatory effect on the extracellular matrix of cartilage cells.

CONCLUSION

Engineered Exos loaded with miR-29a can exert anti-inflammatory effects and maintain extracellular matrix stability, thereby protecting articular cartilage, and slowing the progression of KOA.

5-aminosalicylic acid suppresses osteoarthritis through the OSCAR-PPARγ axis

Osteoarthritis (OA) is a progressive and irreversible degenerative joint disease that is characterized by cartilage destruction, osteophyte formation, subchondral bone remodeling, and synovitis. Despite affecting millions of patients, effective and safe disease-modifying osteoarthritis drugs are lacking. Here we reveal an unexpected role for the small molecule 5-aminosalicylic acid (5-ASA), which is used as an anti-inflammatory drug in ulcerative colitis. We show that 5-ASA competes with extracellular-matrix collagen-II to bind to osteoclast-associated receptor (OSCAR) on chondrocytes. Intra-articular 5-ASA injections ameliorate OA generated by surgery-induced medial-meniscus destabilization in male mice. Significantly, this effect is also observed when 5-ASA was administered well after OA onset. Moreover, mice with DMM-induced OA that are treated with 5-ASA at weeks 8-11 and sacrificed at week 12 have thicker cartilage than untreated mice that were sacrificed at week 8. Mechanistically, 5-ASA reverses OSCAR-mediated transcriptional repression of PPARγ in articular chondrocytes, thereby suppressing COX-2-related inflammation. It also improves chondrogenesis, strongly downregulates ECM catabolism, and promotes ECM anabolism. Our results suggest that 5-ASA could serve as a DMOAD.

Synthetic Knee MRI T1p Maps as an Avenue for Clinical Translation of Quantitative Osteoarthritis Biomarkers

A 2D U-Net was trained to generate synthetic T1p maps from T2 maps for knee MRI to explore the feasibility of domain adaptation for enriching existing datasets and enabling rapid, reliable image reconstruction. The network was developed using 509 healthy contralateral and injured ipsilateral knee images from patients with ACL injuries and reconstruction surgeries acquired across three institutions. Network generalizability was evaluated on 343 knees acquired in a clinical setting and 46 knees from simultaneous bilateral acquisition in a research setting. The deep neural network synthesized high-fidelity reconstructions of T1p maps, preserving textures and local T1p elevation patterns in cartilage with a normalized mean square error of 2.4% and Pearson's correlation coefficient of 0.93. Analysis of reconstructed T1p maps within cartilage compartments revealed minimal bias (-0.10 ms), tight limits of agreement, and quantification error (5.7%) below the threshold for clinically significant change (6.42%) associated with osteoarthritis. In an out-of-distribution external test set, synthetic maps preserved T1p textures, but exhibited increased bias and wider limits of agreement. This study demonstrates the capability of image synthesis to reduce acquisition time, derive meaningful information from existing datasets, and suggest a pathway for standardizing T1p as a quantitative biomarker for osteoarthritis.

Unsupervised domain adaptation for automated knee osteoarthritis phenotype classification

Background

Osteoarthritis (OA) is a global healthcare problem. The increasing population of OA patients demands a greater bandwidth of imaging and diagnostics. It is important to provide automatic and objective diagnostic techniques to address this challenge. This study demonstrates the utility of unsupervised domain adaptation (UDA) for automated OA phenotype classification.

Methods

We collected 318 and 960 three-dimensional double-echo steady-state magnetic resonance images from the Osteoarthritis Initiative (OAI) dataset as the source dataset for phenotype cartilage/meniscus and subchondral bone, respectively. Fifty three-dimensional turbo spin echo (TSE)/fast spin echo (FSE) MR images from our institute were collected as the target datasets. For each patient, the degree of knee OA was initially graded according to the MRI Knee Osteoarthritis Knee Score before being converted to binary OA phenotype labels. The proposed four-step UDA pipeline included (I) pre-processing, which involved automatic segmentation and region-of-interest cropping; (II) source classifier training, which involved pre-training a convolutional neural network (CNN) encoder for phenotype classification using the source dataset; (III) target encoder adaptation, which involved unsupervised adjustment of the source encoder to the target encoder using both the source and target datasets; and (IV) target classifier validation, which involved statistical analysis of the classification performance evaluated by the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity and accuracy. We compared our model on the target data with the source pre-trained model and the model trained with the target data from scratch.

Results

For phenotype cartilage/meniscus, our model has the best performance out of the three models, giving 0.90 [95% confidence interval (CI): 0.79-1.02] of the AUROC score, while the other two model show 0.52 (95% CI: 0.13-0.90) and 0.76 (95% CI: 0.53-0.98). For phenotype subchondral bone, our model gave 0.75 (95% CI: 0.56-0.94) at AUROC, which has a close performance of the source pre-trained model (0.76, 95% CI: 0.55-0.98), and better than the model trained from scratch on the target dataset only (0.53, 95% CI: 0.33-0.73).

Conclusions

By utilising a large, high-quality source dataset for training, the proposed UDA approach enhances the performance of automated OA phenotype classification for small target datasets. As a result, our technique enables improved downstream analysis of locally collected datasets with a small sample size.

Structural phenotypes of knee osteoarthritis: potential clinical and research relevance

A joint contains many different tissues that can exhibit pathological changes, providing many potential targets for treatment. Researchers are increasingly suggesting that osteoarthritis (OA) comprises several phenotypes or subpopulations. Consequently, a treatment for OA that targets only one pathophysiologic abnormality is unlikely to be similarly efficacious in preventing or delaying the progression of all the different phenotypes of structural OA. Five structural phenotypes have been proposed, namely the inflammatory, meniscus-cartilage, subchondral bone, and atrophic and hypertrophic phenotypes. The inflammatory phenotype is characterized by marked synovitis and/or joint effusion, while the meniscus-cartilage phenotype exhibits severe meniscal and cartilage damage. Large bone marrow lesions characterize the subchondral bone phenotype. The hypertrophic and atrophic OA phenotype are defined based on the presence large osteophytes or absence of any osteophytes, respectively, in the presence of concomitant cartilage damage. Limitations of the concept of structural phenotyping are that they are not mutually exclusive and that more than one phenotype may be present. It must be acknowledged that a wide range of views exist on how best to operationalize the concept of structural OA phenotypes and that the concept of structural phenotypic characterization is still in its infancy. Structural phenotypic stratification, however, may result in more targeted trial populations with successful outcomes and practitioners need to be aware of the heterogeneity of the disease to personalize their treatment recommendations for an individual patient. Radiologists should be able to define a joint at risk for progression based on the predominant phenotype present at different disease stages.

MR-Imaging in Osteoarthritis: Current Standard of Practice and Future Outlook

Osteoarthritis (OA) is a common degenerative joint disease that affects millions of people worldwide. Magnetic resonance imaging (MRI) has emerged as a powerful tool for the evaluation and monitoring of OA due to its ability to visualize soft tissues and bone with high resolution. This review aims to provide an overview of the current state of MRI in OA, with a special focus on the knee, including protocol recommendations for clinical and research settings. Furthermore, new developments in the field of musculoskeletal MRI are highlighted in this review. These include compositional MRI techniques, such as T2 mapping and T1rho imaging, which can provide additional important information about the biochemical composition of cartilage and other joint tissues. In addition, this review discusses semiquantitative joint assessment based on MRI findings, which is a widely used method for evaluating OA severity and progression in the knee. We analyze the most common scoring methods and discuss potential benefits. Techniques to reduce acquisition times and the potential impact of deep learning in MR imaging for OA are also discussed, as these technological advances may impact clinical routine in the future.

Latest insights in disease-modifying osteoarthritis drugs development

Osteoarthritis (OA) is a prevalent and severely debilitating disease with an unmet medical need. In order to alleviate OA symptoms or prevent structural progression of OA, new drugs, particularly disease-modifying osteoarthritis drugs (DMOADs), are required. Several drugs have been reported to attenuate cartilage loss or reduce subchondral bone lesions in OA and thus potentially be DMOADs. Most biologics (including interleukin-1 (IL-1) and tumor necrosis factor (TNF) inhibitors), sprifermin, and bisphosphonates failed to yield satisfactory results when treating OA. OA clinical heterogeneity is one of the primary reasons for the failure of these clinical trials, which can require different therapeutic approaches based on different phenotypes. This review describes the latest insights into the development of DMOADs. We summarize in this review the efficacy and safety profiles of various DMOADs targeting cartilage, synovitis, and subchondral bone endotypes in phase 2 and 3 clinical trials. To conclude, we summarize the reasons for clinical trial failures in OA and suggest possible solutions.

Нетрадиційні методи лікування остеоартрозу колінного суглоба

Сьогодні лікування остеоартрозу (ОА), як і раніше, є серйозною проблемою для медицини. Незважаючи на те, що багато широко використовуваних консервативних методів лікування ОА колінного суглоба визнані ефективними, триває пошук нових методів. Оскільки суглобовий хрящ має обмежений потенціал відновлення, ефективні методи лікування залишаються складними актуальними завданнями. Інноваційна терапія спрямована на пошук найкращого способу лікування для уповільнення прогресування ОА. Актуальними є епідеміологічні та клінічні дослідження ОА, оскільки епідеміологічні дослідження виявляють фактори ризику виникнення і прогресування цього захворювання, а клінічні дослідження відіграють важливу роль для нових методів лікування ОА, включно з пероральною, ін’єкційною та внутрішньосуглобовою терапією. Сьогодні провідні фахівці з лікування ОА продовжують дискутувати щодо корисності внутрішньосуглобових ін’єкцій (ВСІ) та доходять різних висновків. Мета дослідження: провести огляд літератури про лікування ОА колінного суглоба з аналізом інноваційних методів лікування щодо використання внутрішньосуглобових ін’єкцій (як-от: збагачена тромбоцитами плазма, терапія стовбуровими клітинами, пролотерапія, блокада генікулярного (колінного) нерва) та їх переваг і недоліків задля визначення можливих напрямків лікування, які є більш безпечними й економічно ефективними для пацієнта. Матеріали та методи. Пошук наукової інформації проведений в електронних базах PubMed, Google Scholar. Результати. У цьому огляді наведені методи лікування ОА із застосуванням внутрішньосуглобових ін’єкцій біологічно-фармакологічних засобів, як-от: збагачена тромбоцитами плазма, терапія стовбуровими клітинами та пролотерапія, блокада генікулярного нерва. Висновки. Зважаючи на мультидисциплінарний підхід, що включає біофармакологічні та немедикаментозні методи лікування ОА, внутрішньосуглобові ін’єкції можна розглядати як ефективну місцеву терапію ОА.

Strategic application of imaging in DMOAD clinical trials: focus on eligibility, drug delivery, and semiquantitative assessment of structural progression

Despite decades of research efforts and multiple clinical trials aimed at discovering efficacious disease-modifying osteoarthritis (OA) drugs (DMOAD), we still do not have a drug that shows convincing scientific evidence to be approved as an effective DMOAD. It has been suggested these DMOAD clinical trials were in part unsuccessful since eligibility criteria and imaging-based outcome evaluation were solely based on conventional radiography. The OA research community has been aware of the limitations of conventional radiography being used as a primary imaging modality for eligibility and efficacy assessment in DMOAD trials. An imaging modality for DMOAD trials should be able to depict soft tissue and osseous pathologies that are relevant to OA disease progression and clinical manifestations of OA. Magnetic resonance imaging (MRI) fulfills these criteria and advances in technology and increasing knowledge regarding imaging outcomes likely should play a more prominent role in DMOAD clinical trials. In this perspective article, we will describe MRI-based tools and analytic methods that can be applied to DMOAD clinical trials with a particular emphasis on knee OA. MRI should be the modality of choice for eligibility screening and outcome assessment. Optimal MRI pulse sequences must be chosen to visualize specific features of OA.

Achyranthoside D attenuates chondrocyte loss and inflammation in osteoarthritis via targeted regulation of Wnt3a

BACKGROUND

Achyranthes bidentata Blume (A. bidentata) is a common Chinese herb used to treat osteoarthritis (OA). Achyranthoside D (Ach-D) is a glucuronide saponin isolated from A. bidentata.

PURPOSE

To assess the mechanisms of action of Ach-D and its effects on OA.

METHODS

The effects of Ach-D were evaluated in rats underwent anterior cruciate ligament transection (ACLT) with medial meniscectomy (MMx) and in interleukin (IL)-1β-induced chondrocytes. Histological changes in rat cartilage tissues were detected using Safranin O-Fast green and haematoxylin-eosin staining. Immunohistochemical staining, qRT-PCR, ELISA, immunoblotting, and immunofluorescence were conducted to examine cartilage degeneration-related and inflammation-related factor expression. CCK-8, LDH assay, and EdU staining were performed to detect chondrocyte death.

RESULTS

Ach-D dose-dependently reduced the Osteoarthritis Research Society International (OARSI) scores, alleviated cartilage injury, and decreased the serum concentrations of CTX-II and COMP in ACLT-MMx models. Ach-D increased the expression levels of collagen II and aggrecan and decreased the levels of cartilage degeneration-related proteins, ADAMTS-5, MMP13, and MMP3, in rat cartilage tissues. Additionally, nod-like receptor protein 3 (NLRP3)-related inflammation was reduced by Ach-D, as shown by the significantly inhibited expression levels of NLRP3, ASC, GSDMD, IL-6, TNF-α, IL-1β, and IL-18 in rat cartilage tissues. In primary rat chondrocytes, Ach-D protected against IL-1β-induced viability loss and LDH release. Wnt3a is the target protein of Ach-D. Mechanistically, Ach-D alleviated OA by inhibiting Wnt signalling.

CONCLUSION

ACH-D may reduce inflammation and cartilage degeneration by inhibiting the Wnt signalling pathway, thereby reducing OA.

Ultrashort echo time magnetization transfer imaging of knee cartilage and meniscus after long-distance running

OBJECTIVE

To assess the detection of changes in knee cartilage and meniscus of amateur marathon runners before and after long-distance running using a 3D ultrashort echo time MRI sequence with magnetization transfer preparation (UTE-MT).

METHODS

We recruited 23 amateur marathon runners (46 knees) in this prospective cohort study. MRI scans using UTE-MT and UTE-T2* sequences were performed pre-race, 2 days post-race, and 4 weeks post-race. UTE-MT ratio (UTE-MTR) and UTE-T2* were measured for knee cartilage (eight subregions) and meniscus (four subregions). The sequence reproducibility and inter-rater reliability were also investigated.

RESULTS

Both the UTE-MTR and UTE-T2* measurements showed good reproducibility and inter-rater reliability. For most subregions of cartilage and meniscus, the UTE-MTR values decreased 2 days post-race and increased after 4 weeks of rest. Conversely, the UTE-T2* values increased 2 days post-race and decreased after 4 weeks. The UTE-MTR values in lateral tibial plateau, central medial femoral condyle, and medial tibial plateau showed a significant decrease at 2 days post-race compared to the other two time points (p < 0.05). By comparison, no significant UTE-T2* changes were found for any cartilage subregions. For meniscus, the UTE-MTR values in medial posterior horn and lateral posterior horn regions at 2 days post-race were significantly lower than those at pre-race and 4 weeks post-race (p < 0.05). By comparison, only the UTE-T2* values in medial posterior horn showed a significant difference.

CONCLUSIONS

UTE-MTR is a promising method for the detection of dynamic changes in knee cartilage and meniscus after long-distance running.

KEY POINTS

• Long-distance running causes changes in the knee cartilage and meniscus. • UTE-MT monitors dynamic changes of knee cartilage and meniscal non-invasively. • UTE-MT is superior to UTE-T2* in monitoring dynamic changes in knee cartilage and meniscus.

MRI underestimates presence and size of knee osteophytes using CT as a reference standard

OBJECTIVE

To explore the diagnostic performance of routine magnetic resonance imaging (MRI) for the cross-sectional assessment of osteophytes (OPs) in all three knee compartments using computed tomography (CT) as a reference standard.

METHODS

The Strontium Ranelate Efficacy in Knee Osteoarthritis (SEKOIA) trial explored the effect of 3 years of treatment with strontium ranelate in patients with primary knee OA. OPs were scored for the baseline visit only using a modified MRI Osteoarthritis Knee Score (MOAKS) scoring system in the patellofemoral (PFJ), the medial tibiofemoral (TFJ) and the lateral TFJ. Size was assessed from 0 to 3 in 18 locations. Descriptive statistics were used to describe differences in ordinal grading between CT and MRI. In addition, weighted-kappa statistics were employed to assess agreement between scoring using the two methods. Sensitivity, specificity, positive predictive value and negative predictive value as well as area under the curve (AUC) measures of diagnostic performance were employed using CT as the reference standard.

RESULTS

Included were 74 patients with available MRI and CT data. Mean age was 62.9 ± 7.5 years. Altogether 1,332 locations were evaluated. For the PFJ, MRI detected 141 (72%) of 197 CT-defined OPs with a w-kappa of 0.58 (95% CI [0.52-0.65]). In the medial TFJ, MRI detected 178 (81%) of 219 CT-OPs with a w-kappa of 0.58 (95% CI [0.51-0.64]). For the lateral compartment these numbers were 84 (70%) of 120 CT-OPs with a w-kappa of 0.58 (95% CI [0.50-0.66]).

CONCLUSION

MRI underestimates presence of osteophytes in all three knee compartments. CT may be helpful particularly regarding assessment of small osteophytes particularly in early disease.

Advances in osteoarthritis imaging

PURPOSE OF REVIEW

Imaging plays a pivotal role for diagnosis, follow-up and stratification of osteoarthritis patients in clinical trials and research. We aim to present an overview of currently available and emerging imaging techniques for osteoarthritis assessment and provide insight into relevant benefits and pitfalls of the different modalities.

RECENT FINDINGS

Although radiography is considered sufficient for a structural diagnosis of osteoarthritis and is commonly used to define eligibility of patients for participation in clinical trials, it has inherent limitations based on the projectional nature of the technique and inherent challenges regarding reproducibility in longitudinal assessment. MRI has changed our understanding of the disease from 'wear and tear' of cartilage to a whole organ disorder. MRI assessment of structural changes of osteoarthritis includes semi-quantitative, quantitative and compositional evaluation. Ultrasound is helpful in evaluating the degree of synovitis and has value in the assessment particularly of the patella-femoral joint. Recent development of computed tomography technology including weight-bearing systems has led to broader application of this technology in a research context.

SUMMARY

Advances in MRI technology have resulted in a significant improvement in understanding osteoarthritis as a multitissue disease.

The natural product salicin alleviates osteoarthritis progression by binding to IRE1α and inhibiting endoplasmic reticulum stress through the IRE1α-IκBα-p65 signaling pathway

Despite the high prevalence of osteoarthritis (OA) in older populations, disease-modifying OA drugs (DMOADs) are still lacking. This study was performed to investigate the effects and mechanisms of the small molecular drug salicin (SA) on OA progression. Primary rat chondrocytes were stimulated with TNF-α and treated with or without SA. Inflammatory factors, cartilage matrix degeneration markers, and cell proliferation and apoptosis markers were detected at the mRNA and protein levels. Cell proliferation and apoptosis were evaluated by EdU assays or flow cytometric analysis. RNA sequencing, molecular docking and drug affinity-responsive target stability analyses were used to clarify the mechanisms. The rat OA model was used to evaluate the effect of intra-articular injection of SA on OA progression. We found that SA rescued TNF-α-induced degeneration of the cartilage matrix, inhibition of chondrocyte proliferation, and promotion of chondrocyte apoptosis. Mechanistically, SA directly binds to IRE1α and occupies the IRE1α phosphorylation site, preventing IRE1α phosphorylation and regulating IRE1α-mediated endoplasmic reticulum (ER) stress by IRE1α-IκBα-p65 signaling. Finally, intra-articular injection of SA-loaded lactic-co-glycolic acid (PLGA) ameliorated OA progression by inhibiting IRE1α-mediated ER stress in the OA model. In conclusion, SA alleviates OA by directly binding to the ER stress regulator IRE1α and inhibits IRE1α-mediated ER stress via IRE1α-IκBα-p65 signaling. Topical use of the small molecular drug SA shows potential to modify OA progression.

Therapeutic applications of adipose-derived stromal vascular fractions in osteoarthritis

Osteoarthritis (OA) is considered to be a highly heterogeneous disease with progressive cartilage loss, subchondral bone remodeling, and low-grade inflammation. It is one of the world's leading causes of disability. Most conventional clinical treatments for OA are palliative drugs, which cannot fundamentally cure this disease. The stromal vascular fraction (SVF) from adipose tissues is a heterogeneous cell population. According to previous studies, it contains a large number of mesenchymal stem cells, which have been used to treat OA with good therapeutic results. This safe, simple, and effective therapy is expected to be applied and promoted in the future. In this paper, the detailed pathogenesis, diagnosis, and current clinical treatments for OA are introduced. Then, clinical studies and the therapeutic mechanism of SVF for the treatment of OA are summarized.

Imaging in Osteoarthritis

Osteoarthritis (OA) is the most frequent form of arthritis with major implications on both individual and public health care levels. The field of joint imaging, and particularly magnetic resonance imaging (MRI), has evolved rapidly due to the application of technical advances to the field of clinical research. This narrative review will provide an introduction to the different aspects of OA imaging aimed at an audience of scientists, clinicians, students, industry employees, and others who are interested in OA but who do not necessarily focus on OA. The current role of radiography and recent advances in measuring joint space width will be discussed. The status of cartilage morphology assessment and evaluation of cartilage biochemical composition will be presented. Advances in quantitative three-dimensional morphologic cartilage assessment and semi-quantitative whole-organ assessment of OA will be reviewed. Although MRI has evolved as the most important imaging method used in OA research, other modalities such as ultrasound, computed tomography, and metabolic imaging play a complementary role and will also be discussed.

99mTc-NTP 15-5 is a companion radiotracer for assessing joint functional response to sprifermin (rhFGF-18) in a murine osteoarthritis model

With the emergence of disease modifying osteoarthritis drugs (DMOAD), imaging methods to quantitatively demonstrate their efficacy and to monitor osteoarthritis progression at the functional level are urgently needed. Our group showed that articular cartilage can be quantitatively assessed in nuclear medicine imaging by our radiotracer ^99mTc-NTP 15-5 targeting cartilage proteoglycans. In this work, surgically induced DMM mice were treated with sprifermin or saline. We investigated cartilage remodelling in the mice knees by ^99mTc-NTP 15-5 SPECT-CT imaging over 24 weeks after surgery, as wells as proteoglycan biochemical assays. OA alterations were scored by histology according to OARSI guidelines. A specific accumulation of ^99mTc-NTP 15-5 in cartilage joints was evidenced in vivo by SPECT-CT imaging as early as 30 min post-iv injection. In DMM, ^99mTc-NTP 15-5 accumulation in cartilage within the operated joints, relative to contralateral ones, was observed to initially increase then decrease as pathology progressed. Under sprifermin, ^99mTc-NTP 15-5 uptake in pathological knees was significantly increased compared to controls, at 7-, 12- and 24-weeks, and consistent with proteoglycan increase measured 5 weeks post-surgery, as a sign of cartilage matrix remodelling. Our work highlights the potential of ^99mTc-NTP 15-5 as an imaging-based companion to monitor cartilage remodelling in OA and DMOAD response.

Heterogeneity of cartilage damage in Kellgren and Lawrence grade 2 and 3 knees: the MOST study

OBJECTIVE

Eligibility for clinical trials in osteoarthritis (OA) is usually limited to Kellgren-Lawrence (KL) grades 2 and 3 knees. Our aim was to describe the prevalence and severity of cartilage damage in KL 2 and 3 knees by compartment and articular subregion.

DESIGN

The Multicenter Osteoarthritis (MOST) study is a cohort study of individuals with or at risk for knee OA. All baseline MRIs with radiographic disease severity KL2 and 3 were included. Knee MRIs were read for cartilage damage in 14 subregions. We determined the frequencies of no, any and widespread full-thickness cartilage damage by knee compartment, and the prevalence of any cartilage damage in 14 articular subregions.

RESULTS

665 knees from 665 participants were included (mean age 63.8 ± 7.9 years, 66.5% women). 372 knees were KL2 and 293 knees were KL3. There was no cartilage damage in 78 (21.0%) medial tibio-femoral joint (TFJ), 157 (42.2%) lateral TFJ and 62 (16.7%) patello-femoral joint (PFJ) compartments of KL2 knees, and 17 (5.8%), 115 (39.3%) and 35 (12.0%) compartments, respectively, of KL3 knees. There was widespread full-thickness damage in 94 (25.3%) medial TFJ, 36 (9.7%) lateral TFJ and 176 (47.3%) PFJ compartments of KL2 knees, and 217 (74.1%), 70 (23.9%) and 104 (35.5%) compartments, respectively, of KL3 knees. The subregions most likely to have any damage were central medial femur (80.5%), medial patella (69.8%) and central medial tibia (69.9).

CONCLUSIONS

KL2 and KL3 knees vary greatly in cartilage morphology. Heterogeneity in the prevalence, severity and location of cartilage damage in in KL2 and 3 knees should be considered when planning disease modifying trials for knee OA.

Change in knee cartilage components in stroke patients with genu recurvatum analysed by zero TE MR imaging

Genu recurvatum in stroke patients with hemiplegia causes readily cumulative damage and degenerative changes in the knee cartilage. It is important to detect early cartilage lesions for appropriate treatment and rehabilitation. The purpose of this cross-sectional study was to provide a theoretical basis for the early rehabilitation of hemiplegia patients. We used a zero TE double-echo imaging sequence to analyse the water content in knee joint cartilage at 12 different sites of 39 stroke patients with genu recurvatum and 9 healthy volunteers using a metric similar to the porosity index. When comparing the hemiplegic limb vs. the nonhemiplegic limb in patients, the ratios of the deep/shallow free water content of the femur cartilages at the anterior horn (1.16 vs. 1.06) and posterior horn (1.13 vs. 1.25) of the lateral meniscus were significantly different. Genu recurvatum in stroke patients with hemiplegia can cause changes in the moisture content of knee cartilage, and the changes in knee cartilage are more obvious as the genu recurvatum increases. The "healthy limb" can no longer be considered truly healthy and should be considered simultaneously with the affected limb in the development of a rehabilitation treatment plan.

Intra-articular ozone slows down the process of degeneration of articular cartilage in the knees of rats with osteoarthritis

BACKGROUND

Osteoarthritis (OA) is a joint disease of multifactorial etiology, affecting mainly the knees. We aimed to evaluate the effects of two different doses of gaseous ozone intra-articularly on the knee cartilage morphology of rats with osteoarthritis (OA).

METHODS

The articular lesion was induced by sodium monoiodoacetate (MIA). 40 Wistar rats were divided into 4 groups: G1 control (without lesion and without treatment), G2 articular lesion (AL) (only lesion MIA-induced), G3 AL + treatment with 5 μg/mL of ozone intra-articular, and G4 AL + treatment with 10 μg/mL of ozone intra-articular. The experiment was carried out for 60 days.

RESULTS

Both doses of ozone intra-articular demonstrated less reduction in joint space (G3 and G4) compared to the G2, formation of osteophytes, but without subchondral sclerosis. Ozone decreased the volumetric density of the articular lesion (VV(AL)) of tibial. The treatments recovered VV(AL) of the femur similar to G1. Ozone lower dose (G3) showed lower tibia and femur macroscopic scores.

CONCLUSION

Intra-articular gaseous ozone can delay the degeneration of articular cartilage and can represents an integrative therapy in the OA treatment of knee after 60 days of treatment. For the first time the role of ozone in articular cartilage degeneration was evaluated helping to understand this therapy.

3D MRI in Osteoarthritis

Osteoarthritis (OA) is among the top 10 burdensome diseases, with the knee the most affected joint. Magnetic resonance imaging (MRI) allows whole-knee assessment, making it ideally suited for imaging OA, considered a multitissue disease. Three-dimensional (3D) MRI enables the comprehensive assessment of OA, including quantitative morphometry of various joint tissues. Manual tissue segmentation on 3D MRI is challenging but may be overcome by advanced automated image analysis methods including artificial intelligence (AI). This review presents examples of the utility of 3D MRI for knee OA, focusing on the articular cartilage, bone, meniscus, synovium, and infrapatellar fat pad, and it highlights several applications of AI that facilitate segmentation, lesion detection, and disease classification.

Molecular Classification of Knee Osteoarthritis

Knee osteoarthritis (KOA) is the most common form of joint degeneration with increasing prevalence and incidence in recent decades. KOA is a molecular disorder characterized by the interplay of numerous molecules, a considerable number of which can be detected in body fluids, including synovial fluid, urine, and blood. However, the current diagnosis and treatment of KOA mainly rely on clinical and imaging manifestations, neglecting its molecular pathophysiology. The mismatch between participants' molecular characteristics and drug therapeutic mechanisms might explain the failure of some disease-modifying drugs in clinical trials. Hence, according to the temporal alteration of representative molecules, we propose a novel molecular classification of KOA divided into pre-KOA, early KOA, progressive KOA, and end-stage KOA. Then, progressive KOA is furtherly divided into four subtypes as cartilage degradation-driven, bone remodeling-driven, inflammation-driven, and pain-driven subtype, based on the major pathophysiology in patient clusters. Multiple clinical findings of representatively investigated molecules in recent years will be reviewed and categorized. This molecular classification allows for the prediction of high-risk KOA individuals, the diagnosis of early KOA patients, the assessment of therapeutic efficacy, and in particular, the selection of homogenous patients who may benefit most from the appropriate therapeutic agents.

Early-stage symptomatic osteoarthritis of the knee - time for action

Osteoarthritis (OA) remains the most challenging arthritic disorder, with a high burden of disease and no available disease-modifying treatments. Symptomatic early-stage OA of the knee (the focus of this Review) urgently needs to be identified and defined, as efficient early-stage case finding and diagnosis in primary care would enable health-care providers to proactively and substantially reduce the burden of disease through proper management including structured education, exercise and weight management (when needed) and addressing lifestyle-related risk factors for disease progression. Efforts to define patient populations with symptomatic early-stage knee OA on the basis of validated classification criteria are ongoing. Such criteria, as well as the identification of molecular and imaging biomarkers of disease risk and/or progression, would enable well-designed clinical studies, facilitate interventional trials, and aid the discovery and validation of cellular and molecular targets for novel therapies. Treatment strategies, relevant outcomes and ethical issues also need to be considered in the context of the cost-effective management of symptomatic early-stage knee OA. To move forwards, a multidisciplinary and sustained international effort involving all major stakeholders is required.

The Development of Disease-Modifying Therapies for Osteoarthritis (DMOADs): The Evidence to Date

Osteoarthritis (OA) is a complex heterogeneous articular disease with multiple joint tissue involvement of varying severity and no regulatory-agency-approved disease-modifying drugs (DMOADs). In this review, we discuss the reasons necessitating the development of DMOADs for OA management, the classifications of clinical phenotypes or molecular/mechanistic endotypes from the viewpoint of targeted drug discovery, and then summarize the efficacy and safety profile of a range of targeted drugs in Phase 2 and 3 clinical trials directed to cartilage-driven, bone-driven, and inflammation-driven endotypes. Finally, we briefly put forward the reasons for failures in OA clinical trials and possible steps to overcome these barriers.

lncRNA FER1L4 is dysregulated in osteoarthritis and regulates IL-6 expression in human chondrocyte cells

Osteoarthritis (OA) is the most prevalent joint disease and is one of the major causes of disability in the world. There has been an increase in the incidence of OA, which is associated with an aging population, sedentary lifestyle, and reduced physical activity. Due to the complex OA pathogenesis, there are limited diagnostic tools. OA is a degenerative joint disorder with a recognized inflammatory component, usually described as abnormal expression of inflammatory factors. For instance, interleukin 6 (IL‐6) has been shown to be upregulated in serum and synovial fluid among patients with OA. Most of the inflammatory factors have been associated with the expression of long noncoding RNAs (lncRNAs). However, the role of the novel lncRNA Fer-1-like protein 4 (FER1L4) in OA is yet to be determined. Here, we interrogated the expression profile of FER1L4 in patients with OA to define its potential application as a diagnostic marker. We collected synovial fluid and blood samples from both OA cases and normal controls. Using qRT-PCR, we evaluated the expression of FER1L4 in plasma and synovial fluid. On the other hand, the expression of IL-6 in plasma and synovial fluid was assessed using ELISA. Besides, the effect of age, gender or disease stage in the expression of the FER1L4 in plasma was also estimated. Moreover, the receiver operating characteristic (ROC) curves were used to determine the impact of FER1L4 in OA cases compared with the normal controls. In addition, we analyzed the correlation between FER1L4 and IL-6 through Pearson correlation analysis. Also, IL-6 expression in overexpressed FER1L4 samples was detected in chondrocytes through western blot analysis, while FER1L4 expression following endogenous IL-6 exposure was detected by qRT-PCR. Our data showed that whereas lncRNA FER1L4 is downregulated in OA patients, IL‐6 is upregulated. The plasma FER1L4 levels among the OA cases were suppressed with disease progression and old age, and the down-regulation could efficiently discriminate OA patients from normal subjects. In addition, upregulation of FER1L4 inhibited IL‐6 expression in human chondrocyte cells, and treatment with different concentrations of exogenous IL‐6 did not affect the expression of FER1L4. Taken together, our data demonstrates that FER1L4 could efficiently identify OA cases from normal subjects, and can also modulate the expression of IL‐6 in human chondrocytes.

Immunofluorescence Analysis of NF-kB and iNOS Expression in Different Cell Populations during Early and Advanced Knee Osteoarthritis

Synovitis of the knee synovium is proven to be a precursor of knee osteoarthritis (OA), leading to a radiologically advanced stage of the disease. This study was conducted to elucidate the expression pattern of different inflammatory factors—NF-kB, iNOS, and MMP-9 in a subpopulation of synovial cells. Thirty synovial membrane intra-operative biopsies of patients (ten controls, ten with early OA, and ten with advanced OA, according to the Kellgren–Lawrence radiological score) were immunohistochemically stained for NF-kB, iNOS, and MMP9, and for different cell markers for macrophages, fibroblasts, leukocytes, lymphocytes, blood vessel endothelial cells, and blood vessel smooth muscle cells. The total number of CD68+/NF-kB+ cells/mm² in the intima of early OA patients (median = 2359) was significantly higher compared to the total number of vimentin+/Nf-kB+ cells/mm² (median = 1321) and LCA+/NF-kB+ cells/mm² (median = 64) (p < 0.001 and p < 0.0001, respectively). The total number of LCA+/NF-kB+ cells/mm² in the subintima of advanced OA patients (median = 2123) was significantly higher compared to the total number of vimentin+/NF-kB+ cells/mm² (median = 14) and CD68+/NF-kB+ cells/mm² (median = 29) (p < 0.0001). The total number of CD68+/iNOS+ cells/mm² in the intima of both early and advanced OA patients was significantly higher compared to the total number of vimentin+/iNOS+ cells/mm² and LCA+/iNOS+ cells/mm² (p < 0.0001 and p < 0.001, respectively). The total number of CD68+/MMP-9+ cells/mm² in the intima of both early and advanced OA patients was significantly higher compared to the total number of vimentin+/MMP-9+ cells/mm² and CD5+/MMP-9+ cells/mm² (p < 0.0001). Macrophages may have a leading role in OA progression through the NF-kB production of inflammatory factors (iNOS and MMP-9) in the intima, except in advanced OA, where leukocytes could have a dominant role through NF-kB production in subintima. The blocking of macrophageal and leukocyte NF-kB expression is a possible therapeutic target as a disease modifying drug.

How to effectively utilize imaging in disease-modifying treatments for osteoarthritis clinical trials: the radiologist's perspective

Introduction: One of the reasons for failures of disease-modifying osteoarthritis drug clinical trials has been the radiography-based definition of structural eligibility criteria. Imaging, particularly MRI, has a critical role in planning and conducting clinical trials of osteoarthritis.Areas covered: A literature search was performed using keywords including 'osteoarthritis,' 'knee,' 'MRI,' 'intra-articular injection,' 'semiquantitative scoring,' 'clinical trial,' and other specific terms where relevant. The core concepts of using MRI in osteoarthritis clinical trials are explained focusing on knee osteoarthritis, including its role in determining patient eligibility and inclusion/exclusion criteria as well as outcome measures from the expert musculoskeletal radiologist's perspective. A brief overview of statistical analyses that should be deployed in clinical trials utilizing semiquantitative MRI analyses is discussed.Expert opinion: In order to increase chances to detect measurable efficacy effects, investigators should consider utilizing MRI from screening to outcome assessment. Recognition of several phenotypes of osteoarthritis helps in participant stratification and will lead to more targeted clinical trials. Inclusion and exclusion criteria need to be defined using not only radiography but also MRI. Correct intra-articular injection of investigational compounds is critically important if intra-articular drug delivery is required, and such procedure should be performed and documented using appropriate imaging guidance.

Machine-learning, MRI bone shape and important clinical outcomes in osteoarthritis: data from the Osteoarthritis Initiative

OBJECTIVES

Osteoarthritis (OA) structural status is imperfectly classified using radiographic assessment. Statistical shape modelling (SSM), a form of machine-learning, provides precise quantification of a characteristic 3D OA bone shape. We aimed to determine the benefits of this novel measure of OA status for assessing risks of clinically important outcomes.

METHODS

The study used 4796 individuals from the Osteoarthritis Initiative cohort. SSM-derived femur bone shape (B-score) was measured from all 9433 baseline knee MRIs. We examined the relationship between B-score, radiographic Kellgren-Lawrence grade (KLG) and current and future pain and function as well as total knee replacement (TKR) up to 8 years.

RESULTS

B-score repeatability supported 40 discrete grades. KLG and B-score were both associated with risk of current and future pain, functional limitation and TKR; logistic regression curves were similar. However, each KLG included a wide range of B-scores. For example, for KLG3, risk of pain was 34.4 (95% CI 31.7 to 37.0)%, but B-scores within KLG3 knees ranged from 0 to 6; for B-score 0, risk was 17.0 (16.1 to 17.9)% while for B-score 6, it was 52.1 (48.8 to 55.4)%. For TKR, KLG3 risk was 15.3 (13.3 to 17.3)%; while B-score 0 had negligible risk, B-score 6 risk was 35.6 (31.8 to 39.6)%. Age, sex and body mass index had negligible effects on association between B-score and symptoms.

CONCLUSIONS

B-score provides reader-independent quantification using a single time-point, providing unambiguous OA status with defined clinical risks across the whole range of disease including pre-radiographic OA. B-score heralds a step-change in OA stratification for interventions and improved personalised assessment, analogous to the T-score in osteoporosis.

Decreased miR-214-3p activates NF-κB pathway and aggravates osteoarthritis progression

Background

Osteoarthritis (OA), a disease with whole-joint damage and dysfunction, is the leading cause of disability worldwide. The progressive loss of hyaline cartilage extracellular matrix (ECM) is considered as its hallmark, but its exact pathogenesis needs to be further clarified. MicroRNA(miRNA) contributes to OA pathology and may help to identify novel biomarkers and therapies against OA. Here we identified miR-214–3p as an important regulator of OA.

Methods

qRT-PCR and in situ hybridization were used to detect the expression level of miR-214–3p. The function of miR-214–3p in OA, as well as the interaction between miR-214–3p and its downstream mRNA target (IKBKB), was evaluated by western blotting, immunofluorescence, qRT-PCR and luciferase assay. Mice models were introduced to examine the function and mechanism of miR-214–3p in OA in vivo.

Findings

In our study, we found that miR-214–3p, while being down-regulated in inflamed chondrocytes and OA cartilage, regulated ECM metabolism and cell apoptosis in the cartilage. Mechanically, the protective effect of miR-214–3p downregulated the IKK-β expression and led to the dysfunction of NF-κB signaling pathway. Furthermore, intra-articular injection of miR-214–3p antagomir in mice joints triggered spontaneous cartilage loss while miRNA-214–3p agomir alleviated OA in the experimental mouse models.

Interpretation

Decreased miR-214–3p activates the NF-κB signaling pathway and aggravates OA development through targeting IKKβ, suggesting miR-214–3p may be a novel therapeutic target for OA.

Funding

This study was financially supported by grants from the National Natural Science Foundation of China (81,773,532, 81,974,342).