To present an overview of the current role of imaging in clinical trials of knee osteoarthritis (OA), focusing on radiography and magnetic resonance imaging (MRI) in the context of their role as both inclusion criteria and structural outcome measures. A non-systematic literature search (PubMed) was performed, starting with a list of terms including the title of the current manuscript, followed by multiple search terms. The identified methodologies, findings, concepts, and recommendations were organized into a systematic framework, providing an overview of the current and future role of imaging in OA clinical trials. Conventional radiography is the most commonly used modality for the evaluation of OA in clinical trials of disease-modifying OA drugs (DMOADs). Radiography is used to define the severity of structural disease and to measure joint space width as an inclusionary criterion, and has also been employed as an outcome measure. Limitations include a lack of reproducibility, a lack of sensitivity, specificity, and responsiveness regarding structural progression, and an insufficient ability to depict diagnoses of exclusion. MRI is more sensitive and specific in assessing tissue damage and its progression. Using abbreviated imaging protocols and rapid image assessment, MRI may be applied at screening. Quantitative and semiquantitative approaches have been commonly used as outcome measures, and both have advantages and disadvantages. Reasons for the failure of past DMOAD trials are multifold and include patient selection based on imaging and application of imaging outcome measures that are either not sufficiently sensitive to change or are difficult to reliably reproduce longitudinally.

Objective To evaluate whether a composite outcome measure could better detect the effects of adverse patellofemoral morphology on knee structure over two-years than single outcome measures. Methods We used data from the Multicenter Osteoarthritis Study (MOST) to analyze the association between measures of patellofemoral morphology and composite outcomes that combined data on cartilage damage and bone marrow lesion enlargement in two subregions of the patellofemoral joint using proportional odds regression to account for ordinality. We used Z scores to assess sensitivity to change. Results In the cohort of 240 MOST participants with a mean age of 51 years, BMI of 29 kg/m2 we found that for tibial tubercle to trochlear groove distance (TTTG), entry point to trochlear groove angle (EPTG), and entry point to transition point angle (EPTP) cartilage worsening as a single measurement outperformed composite outcomes with higher Z scores. Alternatively, we found that patella tilt angle (PTA) performed best when predicting bone marrow lesion worsening as a single measurement than compared to the composite outcomes. Conclusion For patellofemoral morphological measures, composite outcomes that combined data on cartilage damage and bone marrow lesion enlargement failed to increase sensitivity to change over outcomes for single structures alone. Other composite outcomes may be more successful in increasing the sensivitiy to change, and this warrants further investigation.

Primary aim was to evaluate whether presence of osteoarthritis (OA), as assessed by ordinal grading on whole-body computed tomography (CT), is associated with 68 Ga fibroblast activation protein inhibitor (FAPI) positron emission tomography (PET) tracer uptake as a measure of fibroblastic activation. Secondary aim was to evaluate whether OA disease severity is positively correlated with increased tracer uptake and to evaluate reliability. In a retrospective study design, patients who had undergone 68 Ga-FAPI PET-CT for a spectrum of clinical reasons were included. Whole-body CT was assessed for OA using the OsteoArthritis Computed Tomography‐Score in multiple joints and the spine. Maximum standard uptake value (SUVmax) was determined correspondingly. Logistic regression and correlation analyses were used to describe associations between structural OA and 68 Ga-FAPI PET activity. Fifty-four patients were included. Presence of OA in the acromioclavicular joints (ACJ) was associated with odds of SUVmax being in the highest tertile. Increased odds were seen for one location of the cervical spine (OR 5.7, 95

Articular cartilage is crucial for joint function; however, it has limited regenerative capacity when damaged, a hallmark of many rheumatic diseases. Non-invasive imaging is essential for early diagnosis, therapeutic monitoring and prognostication. MRI remains the reference standard, offering detailed assessment of both morphological and compositional cartilage changes. Technological advances, including high-resolution and compositional MRI techniques such as T2 mapping, T1ρ, delayed gadolinium-enhanced MRI of cartilage, sodium imaging, diffusion imaging and ultra-short echo-time imaging, enable early detection of matrix alterations that precede structural breakdown. CT arthrography, although it involves radiation, serves as a valuable alternative when MRI is contra-indicated, offering high performance in the detection and evaluation of cartilage surface lesions. Emerging modalities, such as ultrasonography and PET, offer additional functional insights but are currently limited in scope. Artificial intelligence is poised to transform cartilage imaging through accelerated acquisition, automated segmentation, improved interpretation and enhanced efficiency, with growing clinical adoption. Advanced cartilage imaging will probably have an increasingly important role in clinical rheumatology, particularly for the optimization of individualized management of cartilage pathology. Non-invasive imaging of articular cartilage has evolved markedly and can be used to monitor response to treatment and predict disease outcomes. This Review provides rheumatologists with a comprehensive update on current and emerging imaging and analysis techniques for the assessment of cartilage.

OBJECTIVE:Gait affects knee loading. Modifying gait could reduce load and protect against cartilage loss. Our objective is to look for modifiable gait parameters and determine their relation to worsening cartilage damage. METHODS:We studied participants from the Multicenter Osteoarthritis Study (MOST) ages 45 to 90 years with, or at risk for, knee osteoarthritis (OA). Gait assessment used inertial measurement units (APDM, Inc) on the pelvis and ankles during a 20-m walk. Knee magnetic resonance imaging (MRI) was acquired at baseline and two years later. Cartilage damage worsening was assessed using MRI Osteoarthritis Knee Scores in 14 knee subregions. We examined change (yes/no) in each subregion. We used ensemble machine learning to discriminate subregions with and without cartilage damage. Predictors tested included gait variables, radiographic OA, baseline cartilage damage, age, sex, height, weight, depressive symptoms, and race/clinic site. Data were split 70% training and 30% test sets. We identified the 10 variables that, across 100 repetitions, most frequently contributed to risk of damage. We used G-computation to evaluate causal risk differences of worsening cartilage damage for each variable. RESULTS:We studied 1,703 participants (mean [±SD] age 61.4 [±9.4] years, 56% female). At two years, 46% had worse cartilage damage in at least one knee subregion. Of gait variables, longer step length was associated with increased risk of damage, especially in knees with more baseline damage. CONCLUSION:Longer step length was associated with worse cartilage damage over two years. Interventions to shorten step length might reduce risk of worsening cartilage damage.

BACKGROUND:MRI is increasingly recognized not only for visualization of knee joint structures in knee osteoarthritis (KOA), but also for its potential to predict KOA incidence and progression. OBJECTIVE:We aim to provide a comprehensive overview of how different types of MRI-detected joint tissue pathology perform in predicting radiographic progression and longitudinal evolution of clinical outcomes and functional decline. METHODS:The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration number CRD420251132451). A systematic literature search was performed in PubMed, Scopus, and Web of Science. After removal of duplicates, 4810 studies underwent a multi-step screening process, of which 99 were included in the qualitative synthesis. The quality of included studies was evaluated using the Newcastle-Ottawa Scale and the Downs and Black checklist. RESULTS:Most of the included studies were of good quality. Strong predictors of KOA incidence included baseline bone marrow lesions (BMLs), specific bone shape patterns (ORs up to 12.5 (95% CI, 4.0-39.3)), meniscal tears, and synovitis. Predictors of KOA progression, characterized by increasing cartilage damage, were meniscal extrusion, synovitis, and BMLs. Notably, baseline cartilage T2 signal abnormalities were a powerful predictor of the future development of new structural cartilage defects (OR = 21.3 (95% CI, 11.1, 40.6)), highlighting a pathway from compositional to structural deterioration in knees with and without pre-existing disease. CONCLUSION:Several MRI-detected joint tissue pathologies longitudinally associated with structural progression and clinically relevant outcomes, such as total knee arthroplasty, allowing patient stratification for disease-modifying osteoarthritis drug (DMOAD) trials. These associations may be further strengthened using compositional and multi-featured MRI models as well as AI-based feature extraction.

Introduction In medical imaging, the bone-cartilage interface refers to the anatomical and radiological boundary between the subchondral bone and overlying hyaline cartilage. Direct visualization of this interface is challenging for multiple reasons, but advances have been made. This perspective focuses on the visualization and clinical relevance of the cartilage-bone interface as visualized by magnetic resonance imaging (MRI), discusses the concept of the meniscal-osteo-chondral unit, introduces cartilage classification systems in the context of this interface and briefly addresses the role of computed tomography (CT) arthrography.Main Part:Recent developments in MRI technology including optimization of ultrashort echo time (TE) sequences allow for direct visualization of the osteo-chondral junction. Despite these advances, the clinical relevance of these imaging findings remains incompletely understood to date. The concept of the osteo-chondral-meniscal unit reflects the close anatomical and functional interrelation between different joint tissues at a local level and has implications for disease progression. Cumulative tissue damage on a subregional joint level substantially increases risk for cartilage damage progression. Cartilage delaminations are typically a result of shear forces and are clinically relevant as these may not be fully appreciated during arthroscopy but may require surgical treatment. The International Cartilage Regeneration & Joint Preservation Society (ICRS) cartilage classification system includes damage of the osteochondral interface while most other systems do not include subchondral bone changes. CT arthrography remains the imaging reference standard for assessing surface morphology and detecting subtle surface defects. Despite its strengths, it is likely underutilized in both clinical trials and routine clinical practice. Conclusions The cartilage-bone interface is best comprehensively evaluated using advanced MRI techniques. The close interrelation between different joint tissues on a subregional joint level must be considered when considering individualized treatment strategies.

Exercise is recommended by all major treatment guidelines of knee osteoarthritis (OA). However, most patients do not maintain the exercise program after cessation of the supervised training period. This study evaluated the sustainability of the positive treatment effects of a 7-month whole-body electromyostimulation (WB-EMS) intervention in overweight individuals with symptomatic knee OA. Seventy-two participants were randomly assigned to a WB-EMS group (n = 36) or a usual care control group (CG, n = 36). After 7 months, supervised WB-EMS training was discontinued, and participants were free to continue WB-EMS independently or engage in alternative exercise modalities. Analyses included only participants who did not continue or newly initiate WB-EMS or resistance training during the subsequent 6-month sustainability period (WB-EMS: n = 21 vs. CG: n = 33). Post-intervention, a significant effect in the primary outcome “pain”, assessed by the Knee Injury and Osteoarthritis Outcome Score (KOOS), was observed in favour of the WB-EMS group. However, this difference was no longer significant at the 6-month sustainability follow-up. Likewise, WB-EMS–induced effects were not maintained for most secondary outcomes, including the remaining KOOS subscales, the 7-day pain diary and hip/leg extensor strength. The only exception was the 30-s sit-to-stand test (p < 0.001). Overall, benefits in knee pain and function largely diminished after training cessation, underscoring the importance of long-term exercise adherence.

Synovitis remains an important marker of osteoarthritis (OA) disease incidence and progression, and is best assessed using imaging. In general, MRI with intravenous contrast is considered the gold standard method for assessing synovitis because it can effectively differentiate inflamed synovium and adjacent joint effusion and other surrounding structures. However, administration of intravenous gadolinium is not always desirable. Several emerging methods are being explored for the visualization of synovitis using non-contrast-enhanced MRI (NCE-MRI) but currently underestimate the amount of inflammation. Ultrasound is another approach that is able to measure and quantify synovitis; however, as with other applications of ultrasound, it is observer-dependent, which may affect reproducibility. Radiography does not play a role in synovitis assessment due to its inability to differentiate intraarticular soft tissues. CT, when contrast enhanced, has been shown to effectively detect synovitis and may be a viable alternative to MRI when MRI is contraindicated or not available. Nuclear medicine techniques such as PET-CT, PET-MRI, and SPECT-CT are not routinely used due to high cost, radiation exposure, and image acquisition times. However, novel radiotracers/biomarkers are being investigated. AI approaches have been investigated for their ability to predict clinical and structural outcomes and for automated detection and quantification including features such as effusion-synovitis.

OBJECTIVE:The Foundation for the National Institutes of Health (FNIH) OA Biomarkers Consortium aims to identify, develop, and qualify biomarkers to support drug development in knee osteoarthritis (OA). The project's second phase, the PROGRESS OA study, aims to externally validate prognostic and response biomarkers identified in the earlier phase (phase 1). Here we present results assessing external validation of prognostic imaging biomarkers. DESIGN:PROGRESS OA included data from the control arms of several completed randomized controlled trials (RCTs) for symptomatic knee OA. Radiographic progression was defined as joint space width loss (JSWL) ≥0.7 mm. Symptomatic progression was defined as increase of nine or more points in Western Ontario and McMaster Universities Arthritis Index pain (0-100 scale). Imaging biomarkers included quantitative measures of cartilage thickness and semiquantitative (SQ) assessments. Associations between baseline biomarkers and outcomes over 12 to 36 months were examined using logistic regression. RESULTS:A total of 320 participants from four RCTs were included. Forty-one participants (13%) had JSWL ≥0.7 mm and 64 (20%) had worsening symptoms. In univariable logistic regression, measures of quantitative and SQ cartilage, SQ Hoffa-synovitis, effusion-synovitis, and meniscal extrusion were consistently selected to predict JSWL ≥0.7 mm, similar to phase 1. SQ Hoffa-synovitis and lateral meniscal damage were consistently selected to predict symptomatic progression. Cross-validated areas under the curve were 0.69 (95% confidence interval [CI]: 0.53-0.85) for JSWL ≥0.7 mm and 0.77 (95% CI: 0.65-0.87) for symptomatic progression. CONCLUSION:The selected prognostic imaging biomarkers are candidates for enriching OA trials for structural and/or symptomatic progressors. Ongoing work includes pursuit of formal biomarker qualification by regulatory agencies, and the use of these biomarkers to capture structural progression with high sensitivity to change.

Objective:Magnetic resonance imaging (MRI) enables detection of early, multi-tissue changes in knee osteoarthritis (OA). A Delphi-derived MRI definition integrates findings across multiple joint tissues to classify tibiofemoral OA (TFOA), though it may identify OA in the absence of cartilage damage. We examined how often MRI-defined TFOA occurs without cartilage involvement in two large US cohorts. Methods:We analyzed baseline data from participants without definite radiographic TFOA [Kellgren-Lawrence (KL) grade <2 in both knees] in the Osteoarthritis Initiative (OAI) and Multicenter Osteoarthritis Study (MOST) cohorts. OAI knees were scored using the MRI Osteoarthritis Knee Score (MOAKS) and MOST knees using the Whole-Organ MRI Score (WORMS). MRI-defined TFOA was determined per Delphi criteria, and these knees were assessed for absence of cartilage lesions, with a secondary analysis for osteophyte absence. Results:Among participants with KL <2 in both knees, MRI-defined TFOA was observed in 283 of 1621 (17.5 %) in OAI and 206 of 641 (32.1 %) in MOST. Nearly all cases showed partial- or full-thickness cartilage lesions. Knees without cartilage involvement were rare: 1/283 (0.4 %) in OAI and 3/206 (1.5 %) in MOST. By contrast, knees without osteophytes were more common (13.4 % OAI, 5.8 % MOST). Conclusions:In two large cohorts at elevated risk for knee OA, MRI-detected cartilage damage was almost always present when knees met multi-tissue MRI-based TFOA criteria, suggesting cartilage involvement may be a consistent feature of disease characterization. These findings indicate that the Delphi definition rarely identifies OA in the absence of cartilage involvement.

BACKGROUND:The relationship between patellofemoral (PF) morphology and PF cartilage damage in the general population remains unclear. PURPOSE:This study aimed to determine whether 3-dimensional-based metrics of PF morphology are associated with progressive lateral PF cartilage damage. STUDY DESIGN:Cross-sectional study; Level of evidence, 2. METHODS:We analyzed nonweightbearing computed tomography scans of knees from a subset of participants enrolled in the community-based Multicenter Osteoarthritis Study. Baseline and 2-year magnetic resonance imaging scans of the knee were evaluated for progressive PF cartilage damage using the Magnetic Resonance Imaging Osteoarthritis Knee Score. Tibial tubercle-trochlear groove (TT-TG) distance, patellar tilt, external tibiofemoral rotation (eTFR), patellar height, entry point-trochlear groove angle, and entry point-transition point (EP-TP) angle were measured for each knee. To assess the association of each morphology measure with progressive cartilage damage, logistic regression models with generalized estimating equations were fit using continuous and natural cubic spline models. RESULTS:We analyzed lateral PF cartilage damage in 389 knees (mean age, 53.79 ± 5.51 years; mean body mass index, 28.48 ± 5.13 kg/m2). TT-TG distance (β = 0.23; odds ratio, 1.26; P = .036), eTFR (β = 0.24; odds ratio, 1.27; P = .048), and EP-TP angle (Z = 2.09; P = .036) all demonstrated significant positive associations with worsening lateral PF cartilage damage. CONCLUSION:The results demonstrated significant associations between 3-dimensional anatomic metrics and progressive lateral PF cartilage damage. Elevated TT-TG distance, eTFR, and EP-TP angle may be keys to understanding the mechanical cause of lateral PF osteoarthritis.

OBJECTIVE:To use patient-reported outcomes (PROs) and performance measures to develop a multi-component outcome (virtual knee replacement [vKR]) that predicts knee replacement (KR). METHODS:Osteoarthritis Initiative (OAI) participants with baseline radiographs, clinical assessments and health insurance were followed for 60 months. Of 8205 knees (4143 participants), 206 knees (187 participants) had KR. Eighteen clinical measures available at annual visits were considered, (e.g., Knee injury and Osteoarthritis Outcome Score knee pain (KOOS KP), frequency, severity, and Quality of Life (QoL), frequent knee pain, knee pain severity, SF12 Mental Health and Physical Health subscales, physical activity, depression, 20-meter walk and chair stands). Combinations of these were evaluated utilizing logistic regression to predict KRs in the next year. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were assessed. RESULTS:The most accurate models for predicting KR incorporated KOOS KP and KOOS QoL at a specific annual visit, and KOOS KP worsening over the previous year combined as weighted sums. Per 10 points of these assessments the odds of vKR increased by 30 % to 65 %. AUCs ranged from 0.87 to 0.92 (vKR1). Constraining KOOS KP and KOOS QoL to be worse at follow-up than at baseline, AUCs exceeded 0.85 (vKR2). When KOOS KP and KOOS QoL remained unchanged or worsened over one year, AUCs were >0.80 (vKR3). CONCLUSION:The three vKR criteria represent potential clinical multi-component outcomes for clinical trials of knee OA. After further validation, any of them may serve as a standalone clinical outcome or in combination with actual knee replacement.

Cartilage surface mapping is a technique that can visualize 3D cartilage thickness variation throughout a joint without a need for arbitrary regional definitions. The objective of this cross-sectional study was to utilize this technique to evaluate the cartilage thickness distribution in knee osteoarthritis patients and to analyze to what extent it depends on demographic, radiographic, and MRI structural pathology strata. Patients of the IMI-APPROACH cohort were included, with MRIs obtained at 1.5 T or 3 T. Tibial and femoral cartilage segmentation and registration with a canonical surface were performed semi-automatically. Kellgren-Lawrence and OARSI grading were performed on knee radiographs; MOAKS scoring was performed on MRI scans. The association of demographics and radiographic and MRI scorings with cartilage thickness distribution was analyzed with general linear models using statistical parametric mapping. Two hundred eighty-seven patients were included. Male sex and height were positively associated with cartilage thickness particularly in the trochlea and medial femur, respectively, with differences up to 0.5 mm (male vs female), while radiographic joint space narrowing and bone marrow lesions showed region-specific negative associations (up to 0.14–0.5 mm per grade). Kellgren-Lawrence grade, MOAKS meniscal extrusion, and osteophytes showed patterns of positive and negative associations, with increasing grades showing reduced local tibiofemoral cartilage thickness, but greater thickness in the trochlea (both up to 0.2–0.3 mm per grade). Decreased height, female sex, and increasing tibiofemoral pathology were associated with thinner tibiofemoral cartilage. Unexpected results such as consistently thicker cartilage in the anterior femur with increasing disease or osteophytosis states provide opportunities for future research.