Objective: To investigate the associations between whole joint cartilage and meniscal morphology on MRI and radiographic joint space width (JSW) measures and in knee osteoarthritis (KOA), to determine whether bicompartmental measures demonstrate stronger associations than unicompartmental ones, and to evaluate their correlations with Kellgren and Lawrence grading. Design: A cross-sectional analysis of baseline radiographs and MRIs from 262 KOA participants in the prospective, multicenter IMI-APPROACH cohort was conducted. Radiographic measures included minimum joint space width (mJSW), fixed location JSW (JSW(x)), mean JSW, and joint line convergence angle (JLCA), assessed using fully automated software. JSW was evaluated both unicompartmentally and bicompartmentally. Cartilage morphology, full-thickness cartilage loss, meniscal extrusion, tears, and maceration were assessed using the semi-quantitative MRI Osteoarthritis Knee Score to summarize whole-joint cartilage and meniscal morphology. Associations of radiographic measures with MRI outcomes were assessed using multivariable linear regression; Spearman correlations with Kellgren and Lawrence (KL) were also evaluated. Results: MRI-defined meniscal maceration was associated with unicompartmental and bicompartmental JSW measures. Full-thickness cartilage loss was associated with unicompartmental (95% CI [-0.16;-0.02]) and bicompartmental mJSW (95% CI [-0.14;-0.02]), and JLCA (95% CI [0.04;0.22]). Models explained 32–39% of variance for unicompartmental and 23–45% for bicompartmental measures (R²). Bicompartmental measures showed stronger correlations with KL grading than unicompartmental measures (95% CI: –0.31 to –0.02). Conclusions: Associations between whole-joint cartilage and meniscal degeneration are similar for uni- and bicompartmental JSW, with bicompartmental JSW showing stronger correlations with KL grades. These findings support including both compartments in radiographic assessment to improve structural evaluation in KOA.

Objective: To analyze and synthesize the information available from five pivotal, large-scale, multicenter, observational studies (CHECK, OAI, FNIH Biomarkers Consortium, IMI-APPROACH, and MOST) focusing on knee osteoarthritis (OA), which can be used to elucidate disease progression, risk factors, and the effectiveness of potential interventions. Design: For this narrative review, a comprehensive literature search and data extraction from official web pages and scientific databases were conducted to compare methodologies, in- and exclusion criteria, outcomes, and cohort characteristics across the studies. Thematic, comparative, and qualitative analyses were employed to identify trends, commonalities, and disparities among the findings. Results: The studies collectively enhanced understanding of the onset and progression of knee OA, and in several of the studies, hip OA, emphasizing the importance of both systemic and local risk factors. Advanced imaging and biomarkers are important components in all the cohorts, with the goal of aiding early diagnosis and tracking disease progression. All cohorts evaluated unique markers generally not available in the other cohorts, while other factors overlap, suggesting possibilities for combining or cross-validating between cohorts. Conclusions: The collaborative efforts of major OA research significantly advance our understanding of knee OA. These studies highlight the importance of a multifaceted approach, integrating advanced imaging, biomarkers, and longitudinal data to tackle the complexities of OA. By synthesizing findings and addressing knowledge gaps such as heterogeneity of patients and used measurements, and use of novel pain measures, future research can develop more effective diagnostic tools and treatments, ultimately enhancing the quality of life for OA patients.

Magnetic resonance Imaging is the gold standard for assessment of soft tissues; however, X-ray-based techniques are required for evaluating bone-related pathologies. This study evaluated the performance of synthetic computed tomography (sCT), a novel MRI-based bone visualization technique, compared with CT, for the scoring of knee osteoarthritis. sCT images were generated from the 3T T1-weighted gradient-echo MR images using a trained machine learning algorithm. Two readers scored the severity of osteoarthritis in tibiofemoral and patellofemoral joints according to OACT, which enables the evaluation of osteoarthritis, from its characteristics of joint space narrowing, osteophytes, cysts and sclerosis in CT (and sCT) images. Cohen's κ was used to assess the interreader agreement for each modality, and intermodality agreement of CT- and sCT-based scores for each reader. We also compared the confidence level of readers for grading CT and sCT images using confidence scores collected during grading. Inter-reader agreement for tibiofemoral and patellofemoral joints were almost-perfect for both modalities (κ = 0.83–0.88). The intermodality agreement of osteoarthritis scores between CT and sCT was substantial to almost-perfect for tibiofemoral (κ = 0.63 and 0.84 for the two readers) and patellofemoral joints (κ = 0.78 and 0.81 for the two readers). The analysis of diagnosis confidence scores showed comparable visual quality of the two modalities, where both are showing acceptable confidence levels for scoring OA. In conclusion, in this single-center study, sCT and CT were comparable for the scoring of knee OA.