Osteoarthritis imaging最新文献

{"title":"THE AGING JOINT: QUANTITATIVE [18F]NAF PET-MR IMAGING OF CELLULAR & MOLECULAR CHANGES IN BONE, CARTILAGE AND MUSCLE ACROSS THE LIFESPAN","authors":"A. Goyal, Y. Vainberg, F. Belibi, A.A. Gatti, M.S. White, R. Shalit, F. Kogan","doi":"10.1016/j.ostima.2025.100334","DOIUrl":"10.1016/j.ostima.2025.100334","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Osteoarthritis (OA) is increasingly recognized as a whole-joint disease, affecting cartilage, subchondral bone and periarticular muscles. While structural changes throughout the lifespan have been investigated in prior work, few studies have explored early cellular and molecular changes, such as bone metabolism, cartilage matrix composition, and muscle quality. In this study, we simultaneously assessed bone metabolic activity, cartilage microstructure, and muscle morphometry and composition in vivo, and examined their associations with key OA risk factors including age, body mass index (BMI), and sex.</div></div><div><h3>OBJECTIVE</h3><div>To characterize cellular and molecular features of bone, cartilage, and muscle in asymptomatic adults, and determine how these metrics vary with key OA risk factors of age, BMI, and sex.</div></div><div><h3>METHODS</h3><div>Forty-five asymptomatic subjects (23-79 years old, 22 female) with no history of knee injury or symptomatic arthritis underwent bilateral knee imaging on a 3T GE PET-MRI scanner (Figure 1). Quantitative DESS MR images (TEs 6 and 30.4 ms) were used to compute mean cartilage T2 relaxation time and thickness in femoral, tibial and patellar subregions, which were segmented using a previously validated automated pipeline. Dynamic [<sup>18</sup>F]NaF PET scans were acquired before and after a stair-climbing exercise (2.5mCi dose/injection) and were used to quantify Standardized Uptake Value measures (SUVmean, SUVmax) and their exercise-induced change: ΔSUVmean, ΔSUVmax. Iterative Decomposition of water and fat with Echo Assymetry and Least squares estimation (IDEAL) scans of the bilateral thighs were also acquired. The quadriceps, hamstrings, and hip adductors were segmented using an automated pipeline (MuscleMap) and muscle volume (normalized to BMI), fat fraction, and lean muscle mass were calculated for each muscle. Statistical analysis included a linear mixed effects model for each tissue outcome (cartilage, bone, and muscle metrics), where sex (male vs. female), age (years) and BMI (kg/m²) were included as fixed-effect predictors, and random intercepts for subject and for side nested within subject (to account for the paired left/right measures) captured within‐individual correlation. Significance threshold was set at p < 0.05 for this analysis.</div></div><div><h3>RESULTS</h3><div>Table 1 shows results from the linear mixed effects model.</div><div>1) Higher BMI was associated with markedly greater baseline (SUVmean and SUVmax) and post‐exercise bone tracer uptake (ΔSUVmean and ΔSUVmax), indicating increased bone turnover in individuals with higher body mass. Age was linked specifically to higher maximum uptake measures (SUVmax and ΔSUVmax), suggesting that focal sites of remodeling intensify with aging even if the overall mean uptake remains relatively stable.</div><div>2) In cartilage, T2 relaxation times rose progressively across whole, deep, and superfic","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100334"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EXPLORING SEX-BASED HIP MORPHOLOGY DIFFERENCES IN YOUNG ADULTS USING AN AUTOMATED 3D METHOD","authors":"M.A. Kamphuis ,&nbsp;E.H.G. Oei ,&nbsp;J. Runhaar ,&nbsp;D.F. Hanff ,&nbsp;J.J. Tolk ,&nbsp;R. Agricola ,&nbsp;S.M.A. Bierma-Zeinstra ,&nbsp;S. Klein ,&nbsp;J. Hirvasniemi","doi":"10.1016/j.ostima.2025.100295","DOIUrl":"10.1016/j.ostima.2025.100295","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Although many factors contribute to the development of hip OA, structural abnormalities such as acetabular dysplasia are recognized as contributing to early degenerative changes. To identify these abnormalities, conventional two-dimensional radiographic methods are still widely used to assess hip morphology. However, they inherently oversimplify the joint’s complex three-dimensional anatomy and are subject to limitations such as patient positioning.</div></div><div><h3>OBJECTIVE</h3><div>This study aimed to develop and validate an automated method for 3D hip morphology analysis, incorporating segmentation and image feature extraction, as well as to assess morphological differences between sexes.</div></div><div><h3>METHODS</h3><div>We analyzed data from 2454 participants from Generation R Cohort (mean ± standard deviation age and BMI: 18.4±0.6 years and 22.7±3.8 kg/m²) comprising 1199 males and 1255 females. Hip structures (femoral bone, acetabular bone, femoral cartilage, and acetabular cartilage) were automatically segmented from MRI. An nnU-Net ensemble model was trained on 40 manually segmented hips and its performance evaluated using the Dice score. From the segmentations, five categories of morphological features were computed: basic geometric metrics (centers and radii), cartilage volumes, angular measurements (tilt, version, neck shaft angle and coverage angles, alpha angles), coverage metrics, and joint space width measurements. Independent samples t-tests were used to evaluate sex -based differences.</div></div><div><h3>RESULTS</h3><div>The automatic deep learning segmentation model achieved mean ± standard deviation Dice scores of 0.97±0.004, 0.90±0.01, 0.76±0.02, and 0.77±0.02 for femoral bone, acetabular bone, femoral cartilage, and acetabular cartilage, respectively, on a hold-out test set of 10 hips. All biomarkers showed statistically significant differences (p&lt;0.05), we highlight those with the largest differences between male and female group means. Compared to males, females had smaller femoral and acetabular radii, as well as reduced cartilage volumes in both the femoral and acetabular regions (Table 1). Alpha angles were lower in females, particularly in the coronal plane, but also in the axial plane, while the acetabular version angle for females was greater (Table 1).</div></div><div><h3>CONCLUSION</h3><div>This study demonstrates the feasibility of automated 3D analysis for comprehensive hip morphology assessment. Overall, the analysis reveals consistent and measurable differences in hip morphology between sexes. These morphological insights may help clarify structural risk factors for early hip OA.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100295"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OSTEOARTHRITIS IS A MULTI-JOINT DISEASE. OR IS IT?","authors":"M.A. van den Berg ,&nbsp;E. Panfilov ,&nbsp;J.H. Krijthe ,&nbsp;R. Agricola ,&nbsp;A. Tiulpin","doi":"10.1016/j.ostima.2025.100326","DOIUrl":"10.1016/j.ostima.2025.100326","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;OA frequently affects both the hip and knee joints; however, most prognostic studies evaluate these joints in isolation. Given the biomechanical and systemic connections between them, this joint-specific focus may overlook important patterns of disease progression. A better understanding of combined hip and knee OA progression could support the development of more accurate prediction models and treatment strategies.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;To determine whether combined hip and knee OA progression exhibits a distinct phenotype compared to isolated OA progression.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;This study used the OAI data, which comprises data from participants aged 45–79 years at risk of developing knee OA. The dataset features bilateral posteroanterior knee radiographs and standardized weight-bearing anteroposterior pelvic radiographs obtained at the baseline and 48-month follow-up visits. Minimal JSW (mJSW) was measured manually for knees and automatically for hips. OA progression was defined as JSN of ≥0.5 mm in either hip or ≥0.7 mm in either knee. Participants with no JSN in any of the four joints at the 48-month follow-up were excluded. The selected participants were classified as having isolated (either hip or knee) or combined (both hip and knee) progression. A logistic regression model incorporating clinical and structural baseline features was used to explore associations with combined progression compared to isolated progression. Baseline radiographic OA (ROA) status of each of the four joints was classified as no ROA (0), early ROA (1) and definite ROA (2) based on the KLG and modified Croft grades. Adjusted odds ratios (aOR) and their 95% confidence intervals, estimated using bootstrapping with 10,000 iterations, and the goodness-of-fit of the model were assessed.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;Among the 1,190 included participants with any ROA progression (mean age 61.5 ± 8.8 years; BMI 29.1 ± 4.5; 55.1% female), 281 (23.6%) showed combined ROA progression. The co-occurrence of baseline hip and knee ROA grades was reviewed descriptively (Table 1). The observed relatively small prevalence of combined progression in this population prevented including these ROA status interaction effects within our model. The logistic model showed improved fit over an intercept-only model (likelihood ratio test, p &lt; 0.0001), and acceptable goodness-of-fit (Hosmer-Lemeshow test, p = 0.40). Several baseline features were associated with higher odds of combined progression compared to isolated, including older age, female sex, varus knee alignment in the right knee, higher mJSW in the hip, and having definite ROA in the left hip (Figure 1). Interestingly, having ROA in the right hip or valgus knee alignment in the left knee would decrease the odds of combined progression.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;CONCLUSION&lt;/h3&gt;&lt;div&gt;Our findings suggest that combined hip and knee OA progression may represent a disti","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100326"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IMPROVED DCE-MRI OF OA SYNOVITIS IN THE PRESENCE OF EFFUSION","authors":"J.C. Waterton ,&nbsp;J.H. Naish ,&nbsp;M. Tibiletti ,&nbsp;L. Edwards ,&nbsp;M.J. Heaton ,&nbsp;J.D. Kaggie ,&nbsp;M.J. Graves ,&nbsp;R.J. Janiczek ,&nbsp;A. McCaskie ,&nbsp;F.J. Gilbert ,&nbsp;G.J.M. Parker ,&nbsp;J.W. MacKay","doi":"10.1016/j.ostima.2025.100329","DOIUrl":"10.1016/j.ostima.2025.100329","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Synovitis is increasingly important in OA, both for disease understanding and as a therapeutic target. Dynamic contrast-enhanced (DCE) MRI is a powerful tool providing regional pharmacodynamic biomarkers. Investigators commonly map synovitis using compartmental models, such as the Extended Tofts model (ETM) originally developed for neuroscience and oncology (1). ETM assumes the extravascular extracellular space (v_e) is a well-mixed compartment, an assumption commonly violated in the presence of effusion. Use of an unsuitable compartmental model sometimes produces physiologically implausible imaging biomarkers which lack face validity and damage confidence in the interpretation of any changes.</div></div><div><h3>OBJECTIVE</h3><div>1) to develop a 3-compartment model (3CM) suitable for DCE-MRI in OA in the presence of effusion; 2) to characterize the model by simulation; 3) to compare performance of new 3CM and conventional ETM in an OA study with between- and within-subject comparison.</div></div><div><h3>METHODS</h3><div>The model (2) (figure 1A), includes v_e in exchange with a well-mixed vascular plasma compartment v_p, and also with a third effusion-like compartment receiving contrast from, but not returning it to, v_e. It has previously been characterized in an RA setting (2). A previously-reported (3) knee OA DCE-MRI study includes 61 datasets from 21 subjects (6 healthy, 11 KL2, 4 KL3) imaged on multiple occasions, all segmented by a musculoskeletal radiologist (JWM). Data were fit voxelwise in VoxelFlow (Bioxydyn) using 3CM, ETM, and a Patlak-type uptake-only model (UOM). Akaike Information Criterion (AIC) was used to determine which model each voxel preferred. Between-subject means±SD and between-scan repeatability coefficients of variation (CoV) were determined for each biomarker, and also for the AIC-imposed parcellations.</div></div><div><h3>RESULTS</h3><div>In simulations when the generative model was 3CM, ETM performed poorly (except at low k₁), but when the generative model was ETM, 3CM performed almost as well as the generative model across the whole parameter space. In OA subjects (Figure 1B, Table 1), extreme unphysiologic values of v_e (red in Figure 1C) were seen with ETM but not 3CM, while repeatability CoV did not deteriorate for the new 3CM k₁ in comparison to conventional ETM (Table 1). Differences between healthy and OA subjects were preserved.</div></div><div><h3>CONCLUSION</h3><div>The new 3CM model provides plausible biomarker values and informative maps, avoiding unphysiologic parameter estimates. This offers drug developers greater confidence in interpreting drug-induced pharmacodynamic responses.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100329"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AUTOMATIC MENISCUS ANALYSIS DEMONSTRATES REPAIR IS NOT SUPERIOR TO MENISCECTOMY IN IMPROVING MENISCAL UTE-T2* PROPERTIES 2-YEARS POST ACLR","authors":"A.A. Gatti ,&nbsp;A.A. Williams ,&nbsp;C.R. Chu","doi":"10.1016/j.ostima.2025.100347","DOIUrl":"10.1016/j.ostima.2025.100347","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;Concomitant meniscus tear is common with ACL injury and amplifies OA risk. MRI ultrashort echo-time T2* (UTE-T2*) is sensitive to the compositional integrity of the meniscus and is histologically verified to associate with collagen fibril alignment. We implemented an automated pipeline to determine whether meniscal T2* composition 2-years after ACL reconstruction (ACLR) differs between patients with and without a meniscal tear at the time of surgery.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;To test whether menisci found to be torn at the time of ACLR exhibit, at 2-year follow-up, higher mean UTE-T2* reflecting greater compositional degeneration than intact menisci and whether meniscal repair demonstrates lower UTE-T2* than meniscectomy at 2-year follow-up.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;111 ACLR patients (53/111(48%) female; mean[SD] age: 32[10]yrs; BMI: 25[3]kg/m2) underwent 3T MRI 2 years after ACLR (2.0[0.9]years). UTE-T2* maps were generated by fitting a mono-exponential decay curve to sagittal T2*-weighted images using a Levenberg-Marquardt algorithm. Images were acquired at 8 TEs (32μs -16ms, non-uniform spacing) using a radial-out 3D Cones acquisition, TR = 22ms, in-plane resolution = 0.313 to 0.364 mm, and 3mm slice thickness. Menisci were automatically segmented using a U-Net pre-trained on &gt;300 DESS volumes and fine-tuned to segment root-sum-of-squares images combining Cones echoes 2–6. Training labels were generated by registering DESS images to Cones and propagating the segmentation. Automated segmentation was evaluated in a validation cohort using the dice similarity coefficient (DSC) and average symmetric surface distance (ASSD). The menisci were subdivided into anterior, middle, and posterior thirds using an automated polar coordinate-based system (Fig 1). Meniscal tear and treatment at the time of ACLR was assessed from operative reports. UTE-T2* differences between torn and intact menisci, and between repair versus meniscectomy were assessed with t-tests (or Mann-Whitney U tests). Statistical analyses were performed with SPSS (IBM) and Excel (Microsoft).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;Automated segmentation in the validation cohort (n=16) had median DSC = 0.71 and ASSD = 0.52 mm for the medial, and DSC = 0.68 and ASSD = 0.51 mm for the lateral meniscus. At the time of ACLR, meniscal tears were observed in 56/111(50%) patients: 24/111(22%) of medial and 45/111(41%) of lateral menisci. More tears were resected: 11/24(45%) medial, 25/45(56%) lateral than repaired: 10/24(42%) medial, 15/45(33%) lateral. Patients with any medial meniscal tear had higher mean UTE-T2* in the middle (14%, p&lt;0.001) and posterior (20%, p=0.002) regions compared to those with intact menisci, (Fig 2). Patients with any lateral meniscal tear had 20% higher mean UTE-T2* in the middle region of the lateral menisci compared to those with intact menisci (p=0.001). Two years post-ACLR, no mean UTE-T2* differences were","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100347"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WHAT IS THE DISTRIBUTION OF MRI-ASSESSED CARTILAGE DAMAGE AND OSTEOPHYTES WITHIN RADIOGRAPHIC KL GRADE?","authors":"J.E. Collins ,&nbsp;A. Guermazi ,&nbsp;C.K. Kwoh ,&nbsp;S. Demehri ,&nbsp;D.J. Hunter ,&nbsp;F.W. Roemer","doi":"10.1016/j.ostima.2025.100282","DOIUrl":"10.1016/j.ostima.2025.100282","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;Previous studies have shown that mild-to-moderate radiographic disease severity of knee osteoarthritis (OA), i.e. grades 2 and 3 on the Kellgren-Lawrence (KL) scale, reflects a wide spectrum of cartilage morphology including knees with KL2 having no cartilage damage at all, and KL 3 knees having far-advanced wide-spread full-thickness cartilage loss, raising questions on the validity of the KL grading system to classify knees. Radiographic KL grade 2 or 3 is often an inclusion criterion in disease- modifying drug (DMOAD) trials, with the assumption that these knees represent mild-to-moderate OA, i.e. definite OA but not end-stage. No data is available on whether KL0 and 1 knees, - considered pre-radiographic OA -, exhibit osteophytes (OPs) or cartilage damage to a relevant extent or whether more advanced disease, i.e. KL3 and 4, may also reflect knees without or only little relevant cartilage damage or OP presence.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;The current study aimed at investigating the distribution of MRI-based measures of OP and cartilage damage scores by radiographic KL grade.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;Centrally MOAKS MRI and radiographic KL readings were included from the following Osteoarthritis Initiative (OAI) substudies: FNIH Biomarker consortium, POMA and BEAK. In order to match the anteroposterior (a.p.) radiograph, four locations for OPs assessed in the coronal plane (central medial femur, central medial tibia, central lateral femur, central lateral tibia) were considered. Eight tibiofemoral subregions matching the a.p. radiograph were considered for cartilage damage: anterior medial tibia, central medial tibia, posterior medial tibia, central medial femur, anterior lateral tibia, central lateral tibia, posterior lateral tibia and central lateral femur (&lt;strong&gt;Figure 1&lt;/strong&gt;). Cartilage was classified as focal damage only (MOAKS 0, 1.0, 1.1), damage with no advanced full thickness wide-spread damage (MOAKS 2.0, 2.1, 3.0, 3.1), and full thickness wide-spread damage (MOAKS 2.2, 3.2, 3.3). Meniscal damage was assessed with MOAKS, which considered both meniscal morphology and extrusion scores. Descriptive statistics were used to show the frequencies of maximum MOAKS osteophyte and cartilage grades by radiographic KL grade.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;In total, the dataset includes 4924 visits from 1981 participants contributing 2276 knees for up to four timepoints. The radiographic KL distribution for the sample is KL0 n=1463 (29.7%), KL1 n=1457 (29.6%), KL2 n=1282 (26.0%), KL3 n=703 (14.3%) and KL4 n=19 (0.4%). There was a definite trend of increasing cartilage damage and osteophyte score with an increasing KL grade &lt;em&gt;(p&lt;0.001 for both).&lt;/em&gt; However, there was marked heterogeneity in both measures within KL grade. More than 20% of KL 0 knees showed wide-spread superficial cartilage damage and a minority wide-spread full-thickness damage (&lt;strong&gt;Figure 2, Panel A&lt;/str","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100282"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Welcome to the 19th IWOAI","authors":"","doi":"10.1016/S2772-6541(25)00101-1","DOIUrl":"10.1016/S2772-6541(25)00101-1","url":null,"abstract":"","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100361"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conference Timetable","authors":"","doi":"10.1016/S2772-6541(25)00104-7","DOIUrl":"10.1016/S2772-6541(25)00104-7","url":null,"abstract":"","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100364"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASSESSING TEST-RETEST RELIABILITY OF JSW MEASUREMENTS FOR THE MOST4 KNEE RADIOGRAPH POSITIONING PROTOCOL","authors":"N.A. Segal ,&nbsp;N.H. Degala ,&nbsp;T.D. Turmezei ,&nbsp;J.A. Lynch","doi":"10.1016/j.ostima.2025.100317","DOIUrl":"10.1016/j.ostima.2025.100317","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Despite challenges, joint space width (JSW) on weight-bearing radiographs has remained the most common structural outcome for Phase III trials approved by either the FDA or the EMA. The JSW is the distance between the projected femur and tibia margins on radiographic images. Superimposition of the posterior and anterior edges of the tibial plateau is required to accurately measure radiographic JSW. Knees must be positioned correctly at both baseline and follow-up to maximize reliability of measures of JSW and reliability metrics are useful to calculate sample sizes for studies that depend on JSW measurements.</div></div><div><h3>OBJECTIVE</h3><div>To establish the test-retest reliability of knee joint 2D imaging protocols used by the Multicenter Osteoarthritis Study (MOST4) at the 20-year visit.</div></div><div><h3>METHODS</h3><div>This cross-sectional, observational study compared joint space width (JSW) measurements between baseline and 2-week follow-up on PA radiographs acquired using an XFI scanner (Planmed Oy, Helsinki, Finland), using the same protocol used for the MOST4-V1 (20-year) visit. Participants were age ≥50 years, Kellgren-Lawrence grade 0-4, met MOST4 inclusion criteria, and could safely undergo WBCT (i.e. body mass&lt; 230kg, able to stand for 5 minutes with support). Participants were positioned using a customized Perspex frame which could be tilted in the sagittal plane (5°, 10° or 15°) to make the tibial plateaus coplanar with the x-ray beam for a PA radiograph of both knees. Shrout-Fleiss intraclass correlation coefficients (ICC 2.1) and limits of agreement (mm) were calculated for joint space width (JSW) measurements on radiographs acquired at baseline and 2-week follow-up. For the medial compartment, JSW was measured at 50%, 60%, 70%, 80%, and 90% of the distance from the medial tibial spine (0%) to the outer margin of the medial tibial plateau (MTP; 100%). For the lateral compartment, JSW was measured at 50%, 60%, 70%, 80%, and 90% of the distance from the lateral tibial spine (0%) to the outer margin of the lateral tibial plateau (100%). JSW could not be measured in one knee due to poor alignment of the MTP and some knees could not be measured at JSW 90% due to the relative position of the femur on the tibia.</div></div><div><h3>RESULTS</h3><div>A total of 28 knees for 14 participants (demographics in Table 1) were imaged. ICC for JSW at each position in the medial and lateral compartments at JSW 50% to 90% are presented in Table 2 and limits of agreement are presented in Table 3. ICC for JSW measurements in the medial compartment were all ≥ 0.92 and ICC for JSW measurements in the lateral compartment were all ≥ 0.76.</div></div><div><h3>CONCLUSION</h3><div>These data support that the MOST4 knee radiograph acquisition protocol using the XFI has acceptable test-retest reliability for measurement of JSW at locations within the medial and lateral compartments.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100317"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PROJECTED CARTILAGE AREA RATIO, EVALUATED USING THREE-DIMENSIONAL MRI ANALYSIS SOFTWARE, IS A USEFUL INDEX FOR ASSESSING CARTILAGE IN THE MEDIAL COMPARTMENT OF THE KNEE JOINT, COMPARABLE TO CARTILAGE THICKNESS MEASUREMENTS","authors":"N. Ozeki ,&nbsp;J. Masumoto ,&nbsp;I. Sekiya","doi":"10.1016/j.ostima.2025.100305","DOIUrl":"10.1016/j.ostima.2025.100305","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;The projected cartilage area ratio, evaluated using three-dimensional MRI, is defined as the proportion of the region of interest (ROI) occupied by sufficiently thick cartilage and serves as a quantitative index for cartilage assessment (1). However, the relationships between the projected cartilage area ratio and factors such as cartilage thickness, lower limb alignment, patient characteristics, and the medial meniscus coverage ratio have not been fully clarified.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;The aim of this retrospective study was to investigate the correlations between the projected cartilage area ratio and cartilage thickness, lower limb alignment, patient characteristics, and the medial meniscus coverage ratio.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;A total of 53 patients who underwent medial meniscus repair or high tibial osteotomy for the treatment of medial knee OA were included. MRI was performed using a 3.0-T system (Achieva 3.0TX, Philips, Netherlands). Sagittal images of the knee joint were obtained using both fat-suppressed spoiled gradient echo and proton-weighted sequences. DICOM data were processed using SYNAPSE VINCENT 3D software (FUJIFILM Corp., Tokyo, Japan). Tibial cartilage was projected vertically onto a plane aligned with the bone’s long axis, while femoral cartilage was projected radially around the intercondylar axis, defined as the line connecting the centers of the medial and lateral femoral condyles. These centers were identified by approximating each condyle to an ellipse on lateral views. The software automatically delineated the ROI using bone contours and divided the medial femoral condyle (MFC) into nine subregions based on anatomical morphology. The projected cartilage area ratio was calculated as the ratio of the projected cartilage area exceeding a defined thickness threshold to the total ROI area in each region and subregion. Average cartilage thickness and the medial meniscus coverage ratio were also automatically computed. The medial meniscus coverage ratio was defined as the ratio of the area covered by the meniscus within the medial tibial cartilage area to the total medial tibial cartilage area. Correlations between the projected cartilage area ratio or average cartilage thickness and patient demographics, lower limb alignment, Kellgren–Lawrence (KL) grade, and the medial meniscus coverage ratio were assessed using Spearman’s rank correlation coefficient.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;A strong positive correlation was observed between the projected cartilage area ratio and average cartilage thickness in both the MFC (r = 0.96, p &lt; 0.001) and the medial tibial plateau (MTP) (r = 0.96, p &lt; 0.001) (Figure 1). Body weight was not correlated with the projected cartilage area ratio or cartilage thickness; however, BMI showed significant negative correlations with the projected cartilage area ratio (MFC: r = -0.45, p &lt; 0.001; MTP: r = -0.33, p = 0.02) and c","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100305"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}