Osteoarthritis and Cartilage最新文献

Objective: To generate a list of candidate items potentially useful for discriminating individuals with Early-stage Symptomatic Knee Osteoarthritis (EsSKOA) from those with other conditions and from established osteoarthritis (OA), and to reduce this list based on expert consensus.

Design: We conducted a three-round online international modified Delphi exercise with OA clinicians and researchers ("OA experts"). In Round 1, participants reviewed 84 candidate items and nominated additional item(s) potentially useful for EsSKOA classification; those nominated by ≥3 participants were added. In Round 2, participants rated perceived usefulness of 108 items (1 [not at all useful] to 9 [extremely useful]). In Round 3, participants could revise their ratings after reviewing Round 2 group median and quartiles. Following Round 3, we retained items with a median usefulness score >5 and ≥33.3% of participants categorised the item as useful (7 to 9), overall and in subgroup analysis by clinician field.

Results: There were 128 participants in Round 1 and 113 (88%) completed all rounds. We retained 77 items that spanned multiple domains (demographics, symptoms, physical exam, performance-based measures, imaging, laboratory investigations, and gross inspection/arthroscopy). Highly rated items included (median usefulness score): prior knee joint injury (8), diagnosis of OA in a different joint (7), and activity-related knee pain (7). The interquartile range was most often 3.

Conclusion: We identified 77 items that OA experts consider potentially useful for EsSKOA classification. The results highlight experts' uncertainty around item usefulness. Next, candidate items will be further assessed and reduced using data-driven and multicriteria decision analysis methods.

Objective: This study aims to establish an accurate and robust imaging biomarker for pre-clinical osteoarthritis (OA) research, focusing on early detection of cartilage surface degeneration.

Method: Using 50 male Wistar rats, this study aims to observe Collagenase-induced OA (CIOA) progression through microcomputed x-ray tomography (µCT), histopathological analysis, and gait analysis. A novel parameter, Cartilage Roughness Score (CRS), was developed for assessing cartilage structural damage from µCT data and was compared with histological OARSI Cartilage Degeneration Score (OARSI CDS). Additionally, as CRS maps the full surface, it was used to simulate the level of uncertainty in histological sampling.

Results: CRS and OARSI CDS have a linear relationship. CRS for healthy cartilage is 2.75 (95% CI: 1.14-4.36), and with every 1 unit increase in OARSI, CRS is expected to increase by 0.64 (95% CI: 0.35-0.92). Cartilage degeneration due to CIOA was evident in both histopathological scoring and CRS. However, only CRS was sensitive enough to show consistent damage progression from day 10 to day 60. Furthermore, our simulation for histological sampling suggested that up to 16 coronal slices with 200 µm spacing would be needed to accurately represent the full extent of cartilage surface degeneration in a slice-wise manner. Gait analysis showed changes solely at eight days post-collagenase injection, normalizing by day 60.

Conclusion: The CRS analysis method emerges as a robust tool for cartilage surface damage assessment. This study demonstrates the potential of automatic 3D analysis over the traditional 2D histological approach when evaluating cartilage surface damage.

People make sense of osteoarthritis (OA) by drawing on information, beliefs, and knowledge. This narrative review summarises diverse qualitative and quantitative research investigating beliefs and knowledge about OA and the impact these have on behaviour and outcomes. It synthesises evidence and highlights key actions clinicians can take to support people to make sense of OA in helpful ways. Beliefs about OA inform the behaviour of those living with OA and the behaviour of clinicians caring for people with OA. Beliefs about OA often focus on joint degradation and inevitable progression. These impairment-focused fatalistic beliefs can result in reduced offer of, or engagement in, active management strategies. Alternative views focus on health as part of a dynamic ecosystem where people are healthy when they can participate in activities they value. These beliefs are associated with increased engagement in self-management and lifestyle-based interventions. Clinician actions that support people to make sense of OA ways that align with helpful behaviours and support participation in valued activities represent key opportunities to improve health and well-being.

Objective: To evaluate the humeral head bone volume of patients with cuff tear arthropathy (CTA) and examine the therapeutic effect of zoledronate in a rat modified model of CTA (mCTA).

Design: The bone mass in patients with CTA was measured using Hounsfield units from CT images. The mCTA was induced by transecting the rotator cuff, biceps brachii tendon, and superior half of the joint capsule in adult rat shoulders. A single subcutaneous injection of zoledronate was followed by bone histomorphometry and immunohistochemistry of the humeral head, as well as the Murine Shoulder Arthritis Score (MSAS) assessment.

Results: The humeral head bone volume was decreased in patients with CTA. In the mCTA model, M1 macrophages were increased in the synovium and were decreased by zoledronate treatment. The increased expressions of TNF-α, IL-1β and IL-6 in mCTA synovium and articular cartilage were suppressed in the zoledronate-treated mCTA group. The expression of catabolic enzymes in the articular cartilage and MSAS showed similar results. The zoledronate-treated mCTA group showed a decreased subchondral bone collapse with a decreased RANKL/OPG expression ratio and a suppressed number of osteoclasts compared with the control mCTA group. The enhanced expressions of HMGB1 and S100A9 in the mCTA shoulders were eliminated in the zoledronate-treated mCTA group.

Conclusions: The humeral head subchondral bone was decreased in patients with CTA. In the mCTA model, the collapse and osteoarthritic changes were prevented by zoledronate administration. Zoledronate seemed to suppress the number of M1 macrophages in the synovium and osteoclasts in the subchondral bone.

Objective: To review recent literature evidence describing imaging of osteoarthritis (OA) and to identify the current trends in research on OA imaging.

Method: This is a narrative review of publications in English, published between April, 2023, and March, 2024. A Pubmed search was conducted using the following search terms: osteoarthritis/OA, radiography, ultrasound/US, computed tomography/CT, magnetic resonance imaging/MRI, DXA/DEXA, and artificial intelligence/AI/deep learning. Most publications focus on OA imaging in the knee and hip. Imaging of OA in other joints and OA imaging with artificial intelligence (AI) are also reviewed.

Results: Compared to the same period last year (April 2022 - March 2023), there has been no significant change in the number of publications utilizing CT, MRI, and AI. A notable reduction in the number of OA research papers using radiography and ultrasound is noted. There were several observational studies focusing on imaging of knee OA, such as the Multicenter Osteoarthritis Study, Rotterdam Study, Strontium ranelate efficacy in knee OA (SEKOIA) study, and the Osteoarthritis Initiative FNIH Biomarker study. Hip OA observational studies included, but not limited to, Cohort Hip and Cohort Knee study and UK Biobank study. Studies on emerging applications of AI in OA imaging were also covered. A small number of OA clinical trials were published with a focus on imaging-based outcomes.

Conclusion: MRI-based OA imaging research continues to play an important role compared to other modalities. Usage of various AI tools as an adjunct to human assessment is increasingly applied in OA imaging research.