Osteoarthritis and Cartilage最新文献

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.

Osteoarthritis (OA) research is a fast-growing and extremely wide field, in which a substantial increase in knowledge has been achieved over the last year. It covers many different topics, however, a PubMed search using the terms 'osteoarthritis' and 'biology' resulted in only a limited number of studies that were published between April 2023 and April 2024. In order to identify OA-relevant studies that focus on mechanistic studies of biological processes at the tissue, cellular, and molecular level, the following keywords were included as search terms: tissue interactions, single cell sequencing, transcriptomics, extracellular matrix, signaling, ion channels, and pain. The final selection of publications presented in this 'year in review' was influenced by the personal preferences of the authors, and eventually three larger key themes emerged: 1) Joint tissue interactions covering meniscus, subchondral bone, fat tissue, synovium, and synovial fluid. 2) Degeneration of the cartilage extracellular matrix and generation of bioactive fragments. 3) Receptors, ion channels, signaling pathways, and cellular metabolism. Many of the studies summarized here identified novel potential targets for OA treatment, and promising results were already obtained addressing these targets in different animal models. It will be exciting to see which findings can be translated into future clinical studies and eventually lead to novel treatment approaches for human OA.

Objective: Dual-energy x-ray absorptiometry (DXA) images are increasingly used to study hip morphology. Whether hip morphology measurements are consistent between DXA images and radiographs is unknown. Therefore, we investigated the agreement and reliability of the measurements performed on DXA images and radiographs.

Design: We included participants from the Rotterdam study, a population-based cohort study, who received a hip DXA image and pelvic radiograph on the same day. The acetabular depth-width ratio (ADR), modified acetabular index (mAI), alpha angle (AA), Wiberg and lateral center edge angle (WCEA, LCEA), extrusion index (EI) and triangular index ratio (TIR) were automatically determined on both imaging modalities. The intraobserver and intermethod agreement were studied using Bland-Altman methods, and the reliability was assessed using intraclass correlation coefficients (ICC). Secondly, the diagnostic agreement regarding dysplasia, cam, and pincer morphology was assessed using percent agreement and Cohen's kappa.

Results: A total of 750 hips from 411 individuals, median age 67.3 years (range 52.2 - 90.6), 45.5% male, were included. The following intermethod ICCs (95% CI) were obtained: ADR 0.85 (0.74-0.91), mAI 0.75 (0.52-0.85), AA 0.72 (0.68-0.75), WCEA 0.81 (0.74-0.85), LCEA 0.93 (0.91-0.94), EI 0.88 (0.84-0.91), and TIR 0.81 (0.79-0.84). We found comparable intraobserver ICCs for each morphological measurement.

Conclusion: DXA images and pelvic radiographs could both reliably be used to study hip morphology. Due to the lower radiation burden, DXA images could be an excellent alternative to pelvic radiographs for research purposes.

Objective: To provide a comprehensive and insightful summary of studies on molecular biomarkers at the gene, protein, and metabolite levels across different sample types and joints affected by osteoarthritis (OA).

Methods: A literature search using the PubMed database for publications on OA biomarkers published between April 1, 2023 and April 30, 2024 was performed. Publications were then screened, examined at length, and summarized in a narrative review.

Results: Out of the 364 papers initially identified, 44 publications met inclusion criteria, were relevant to OA, and were further examined for data extraction and discussion. These studies included 1 genomic analysis, 22 on protein markers, 6 on metabolite markers, 9 on inflammatory mediators, and 6 integrating multiple molecular levels.

Conclusions: Significant advancements have been made in identifying molecular biomarkers for OA, encompassing various joints, sample types, and molecular levels. Despite this progress, gaps remain, particularly in the need for validation, larger sample sizes, the integration of more clinical data, and consideration of covariates. For early detection and improved treatment of OA, continued efforts in biomarker identification are needed. This effort should seek to identify effective biomarkers that advance early detection, support prevention, evaluate interventions, and improve patient outcomes.