Validity and responsiveness of a new measure of knee osteophytes for osteoarthritis studies: data from the osteoarthritis initiative

Koumine inhibits IL-1β-induced chondrocyte inflammation and ameliorates extracellular matrix degradation in osteoarthritic cartilage through activation of PINK1/Parkin-mediated mitochondrial autophagy

Osteoarthritis (OA) is a degenerative joint disease, Increasingly, mitochondrial autophagy has been found to play an important regulatory role in the prevention and treatment of osteoarthritis. Koumine is a bioactive alkaloid extracted from the plant Gelsemium elegans. In previous research, Koumine was found to have potential in improving the progression of OA in rats. However, the specific mechanism of its action has not been fully explained. Therefore, the aim of this study was to investigate whether Koumine can alleviate OA in rats by influencing mitochondrial autophagy. In the in vitro study, rat chondrocytes (RCCS-1) were induced with IL-1β (10 ng/mL) to induce inflammation, and Koumine (50 μg/mL) was co-treated. In the in vivo study, a rat OA model was established by intra-articular injection of 2% papain, and Koumine was administered orally (1 mg/kg, once daily for two weeks). It was found that Koumine effectively reduced cartilage erosion in rats with osteoarthritis. Additionally, it decreased the levels of inflammatory factors such as IL-1β, IL-6, and extracellular matrix (ECM) components MMP13 and ADAMTS5 in chondrocytes and articular cartilage tissue, while increasing the level of Collagen II.Koumine inhibited the production of reactive oxygen species (ROS) in cartilage tissue and increased the number of autophagosomes in chondrocytes and articular cartilage tissue. Additionally, it upregulated the expression of mitochondrial autophagy proteins LC3Ⅱ/Ⅰ, PINK1, Parkin, and Drp1. The administration of Mdivi-1 (50 μM) reversed the enhanced effect of Koumine on mitochondrial autophagy, as well as its anti-inflammatory and anti-ECM degradation effects in rats with OA. These findings suggest that Koumine can alleviate chondrocyte inflammation and improve the progression of OA in rats by activating PINK1/Parkin-mediated mitochondrial autophagy.

Magnetic resonance imaging assessments for knee segmentation and their use in combination with machine/deep learning as predictors of early osteoarthritis diagnosis and prognosis

Knee osteoarthritis (OA) is a prevalent and disabling disease that can develop over decades. This disease is heterogeneous and involves structural changes in the whole joint, encompassing multiple tissue types. Detecting OA before the onset of irreversible changes is crucial for early management, and this could be achieved by allowing knee tissue visualization and quantifying their changes over time. Although some imaging modalities are available for knee structure assessment, magnetic resonance imaging (MRI) is preferred. This narrative review looks at existing literature, first on MRI-developed approaches for evaluating knee articular tissues, and second on prediction using machine/deep-learning-based methodologies and MRI as input or outcome for early OA diagnosis and prognosis. A substantial number of MRI methodologies have been developed to assess several knee tissues in a semi-quantitative and quantitative fashion using manual, semi-automated and fully automated systems. This dynamic field has grown substantially since the advent of machine/deep learning. Another active area is predictive modelling using machine/deep-learning methodologies enabling robust early OA diagnosis/prognosis. Moreover, incorporating MRI markers as input/outcome in such predictive models is important for a more accurate OA structural diagnosis/prognosis. The main limitation of their usage is the ability to move them in rheumatology practice. In conclusion, MRI knee tissue determination and quantification provide early indicators for individuals at high risk of developing this disease or for patient prognosis. Such assessment of knee tissues, combined with the development of models/tools from machine/deep learning using, in addition to other parameters, MRI markers for early diagnosis/prognosis, will maximize opportunities for individualized risk assessment for use in clinical practice permitting precision medicine. Future efforts should be made to integrate such prediction models into open access, allowing early disease management to prevent or delay the OA outcome.

Fast quantitative bone marrow lesion measurement on knee MRI for the assessment of osteoarthritis

Objective

Knee osteoarthritis (KOA) is a prevalent disease with a high economic and social cost. Magnetic resonance imaging (MRI) can be used to visualize many KOA-related structures including bone marrow lesions (BMLs), which are associated with OA pain. Several semi-automated software methods have been developed to segment BMLs, using manual, labor-intensive methods, which can be costly for large clinical trials and other studies of KOA. The goal of our study was to develop and validate a more efficient method to quantify BML volume on knee MRI scans.

Materials and methods

We have applied a deep learning approach using a patch-based convolutional neural network (CNN) which was trained using 673 MRI data sets and the segmented BML masks obtained from a trained reader. Given the location of a BML provided by the reader, the network performed a fully automated segmentation of the BML, removing the need for tedious manual delineation. Accuracy was quantified using the Pearson's correlation coefficient, by a comparison to a second expert reader, and using the Dice Similarity Score (DSC).

Results

The Pearson's R2 value was 0.94 and we found similar agreement when comparing two readers (R2 ​= ​0.85) and each reader versus the DL model (R2 ​= ​0.95 and R2 ​= ​0.81). The average DSC was 0.70.

Conclusions

We developed and validated a deep learning-based method to segment BMLs on knee MRI data sets. This has the potential to be a valuable tool for future large studies of KOA.

Osteophyte size and location on hip DXA scans are associated with hip pain: Findings from a cross sectional study in UK Biobank

OBJECTIVE

It remains unclear how the different features of radiographic hip osteoarthritis (rHOA) contribute to hip pain. We examined the relationship between rHOA, including its individual components, and hip pain using a novel dual-energy x-ray absorptiometry (DXA)-based method.

METHODS

Hip DXAs were obtained from UK Biobank. A novel automated method obtained minimum joint space width (mJSW) from points placed around the femoral head and acetabulum. Osteophyte areas at the lateral acetabulum, superior and inferior femoral head were derived manually. Semi-quantitative measures of osteophytes and joint space narrowing (JSN) were combined to define rHOA. Logistic regression was used to examine the relationships between these variables and hip pain, obtained via questionnaires.

RESULTS

6807 hip DXAs were examined. rHOA was present in 353 (5.2%) individuals and was associated with hip pain [OR 2.42 (1.78-3.29)] and hospital diagnosed OA [6.01 (2.98-12.16)]. Total osteophyte area but not mJSW was associated with hip pain in mutually adjusted models [1.31 (1.23-1.39), 0.95 (0.87-1.04) respectively]. On the other hand, JSN as a categorical variable showed weak associations between grade ≥ 1 and grade ≥ 2 JSN with hip pain [1.30 (1.06-1.60), 1.80 (1.34-2.42) respectively]. Acetabular, superior and inferior femoral osteophyte areas were all independently associated with hip pain [1.13 (1.06-1.20), 1.13 (1.05-1.24), 1.10 (1.03-1.17) respectively].

CONCLUSION

In this cohort, the relationship between rHOA and prevalent hip pain was explained by 2-dimensional osteophyte area, but not by the apparent mJSW. Osteophytes at different locations showed important, potentially independent, associations with hip pain, possibly reflecting the contribution of distinct biomechanical pathways.

Proximal tibial osteophyte volumes are correlated spatially and with knee alignment: a quantitative analysis suggesting the influence of biochemical and mechanical factors in the development of osteophytes

OBJECTIVE

To characterize the differences and correlations in osteophyte volumes between and within proximal tibial compartments, and to assess the correlations between osteophyte volumes and the femorotibial angle.

DESIGN

CT scans of 73 knees with predominantly medial femorotibial osteoarthritis (21 K/L2, 28 K/L3, 24 K/L4) were retrospectively analyzed using a new, reproducible method measuring total and subregional osteophyte volumes in the medial and lateral compartments. Non-parametric statistics was used for comparison and correlation analyses.

RESULTS

Total osteophyte volumes were larger in the medial than in the lateral compartment for all severity groups (p < 0.05). Additionally, statistically significant differences were observed among subregions of the lateral compartment in K/L3 and K/L4 knees. Statistically significant positive correlations were found between the medial and lateral total osteophyte volumes in K/L3 and K/L4 knees (ρ ≥ 0.44, p = 0.03), and among most subregional osteophyte volumes within each compartment in K/L3 knees. Markedly fewer statistically significant correlations were present in K/L2 and K/L4 knees. In K/L3 knees, the femorotibial angle was statistically significantly positively correlated with the total osteophyte volume in the medial compartment (ρ = 0.50, p = 0.01), with osteophyte volumes in most medial subregions, and with the osteophyte volume in the lateral posterior subregion (ρ = 0.40, p = 0.05).

CONCLUSIONS

Quantitative assessment of osteophytes may bring insight on factors influencing their development. Positive correlations of osteophyte volumes found between and within compartments suggest the influence of biochemical mediators acting on the entire joint, while positive correlations between the femorotibial angle and osteophyte volumes suggest a role of mechanical factors. These hypotheses are to be further confirmed.

West Lake staging: A new staging system orchestrated by X-ray and MRI on knee osteoarthritis

Purpose: To investigate the differences on X-ray and MRI among each stage of knee osteoarthritis (KOA) and further propose a new staging system called West Lake (WL) staging. Methods: A cross-sectional study was conducted on patients with KOA. Stage I, II, III, and IV were divided based on stepwise treatment strategy of Knee osteoarthritis (KOA). Joint space widths (JSW) were measured on X-rays, whereas cartilage injuries (CI) and bone marrow lesions (BML) were evaluated on MRI. The differences of them across the groups were calculated by T-test. Receiver operating characteristic (ROC) curves were rendered to obtain the areas under the curves (AUC), Youden index and corresponding cut-off points. Results: Eventually, there were significant differences on JSW, CI, and BML between stage II/III and III/IV, while no significant differences between stage I/II. In stage II/III, the AUC of JSW, CI, BML was 0.99, 0.76, 0.71 and the Youden index was 0.94, 0.38, 0.45, meanwhile the cut-off points were ≤5.1 mm, >1, >2. In stage III/IV, the AUC of JSW, CI, BML was 0.96, 0.79, 0.74 and the Youden index was 0.84, 0.58, 0.38, meanwhile the cut-off points were ≤3.2 mm, >3, >4. Conclusion: The WL staging was described as follows: Stage I, X-ray shows no joint space narrow, normal MRI or MRI shows cartilage degeneration and only 1 or 2 sections are involved in BML. Stage II, X-ray shows joint space narrow, MRI shows cartilage defect but no full-thickness cartilage defect, meanwhile 3 or 4 sections are involved in BML. Stage III, X-ray shows serious joint space narrow even JSW disappeared, MRI shows full-thickness cartilage defect, more than 4 sections are involved in BML.

MRI-detected osteophytes of the knee: natural history and structural correlates of change

Backgroud

The natural history of semi-quantitative magnetic resonance imaging (MRI)-detected osteophytes (MRI-detected OPs) has not been described and it is unknown whether knee structural abnormalities can predict MRI-detected OP change over time. Thus, the aim of current study is to describe the natural history of knee MRI-detected OP, and to determine if knee structural abnormalities are associated with change of MRI-detected OP in a longitudinal study of older adults.

Methods

Randomly selected older adults (n = 837, mean age 63 years) had MRI at baseline and 413 of them had MRI 2.6 years later to measure MRI-detected OP, cartilage defects, cartilage volume, bone marrow lesions (BMLs), meniscal extrusion, infrapatellar fat pad (IPFP) quality score/maximum area and effusion-synovitis.

Results

Over 2.6 years, average MRI-detected OP score increased significantly in all compartments. The total MRI-detected OP score remained stable in 53% of participants, worsened (≥ 1-point increase) in 46% and decreased in 1%. Baseline cartilage defects (RR, 1.25–1.35), BMLs (RR, 1.16–1.17), meniscal extrusion (RR, 1.22–1.33) and IPFP quality score (RR, 1.08–1.20) site-specifically and independently predicted an increase in MRI-detected OP (p values all ≤ 0.05), after adjustment for covariates. Presence of IPFP abnormality was significantly associated with increased MRI-detected OPs but became non-significant after adjustment for other structural abnormalities. Total (RR, 1.27) and suprapatellar pouch effusion-synovitis (RR, 1.22) were both associated with increased MRI-detected OPs in the lateral compartment only (both p < 0.04).

Conclusion

Knee MRI-detected OPs are common in older adults and are likely to progress. The association between baseline structural abnormalities and worsening MRI-detected OPs suggest MRI-detected OP could be a consequence of multiple knee structural abnormalities.

Integration of accelerated MRI and post-processing software: a promising method for studies of knee osteoarthritis

OBJECTIVE

Magnetic resonance imaging (MRI) is a widely used imaging modality for studies of knee osteoarthritis (OA). Compared to radiography, MRI offers exceptional soft tissue imaging and true three-dimensional (3D) visualization. However, MRI is expensive both due to the cost of acquisition and evaluation of the images. The goal of our study is to develop a new method to address the cost of MRI by combining innovative acquisition methods and automated post-processing software.

METHODS

Ten healthy volunteers were scanned with three different MRI protocols: A standard 3D dual-echo steady state (DESS) pulse sequence, an accelerated DESS (DESS_Acc), acquired at approximately half the time compared to DESS, and a multi-echo time DESS (DESS_MTE), which is capable of producing measurements of T2 relaxation time. A software tool was used to measure cartilage volume. Accuracy was quantified by comparing DESS to DESS_Acc and DESS_MTE and precision was measured using repeat readings and acquisitions. T2 precision was determined using duplicate DESS_MTE acquisitions. Intra-class correlation coefficients (ICCs), root-mean square standard deviation (RMSSD), and the coefficient of variation (CoV) were used to quantify accuracy and precision.

RESULTS

The accuracies of DESS_Acc and DESS_MTE were CoV = 3.7% and CoV = 6.6% respectively, while precision was 3.8%, 3.0%, and 3.1% for DESS, DESS_Acc and DESS_MTE. T2 repositioning precision was 5.8%.

CONCLUSION

The results demonstrate that accurate and precise quantification of cartilage volume is possible using a combination of substantially faster MRI acquisition and post-processing software. Precise measurements of cartilage T2 and volume can be made using the same acquisition.