Osteoarthritis imaging最新文献

{"title":"Fusion of photon-counting CT and MRI improves assessment of the knee: a pilot study.","authors":"Zhaoye Zhou, Theresa Sophie Patzer, Mohamad Alzaher, Ali Guermazi, Dorra Guermazi, Karim Sariahmed, Allyson Zheng, Marco L Loggia, Mohamed Jarraya, Fang Liu","doi":"10.1016/j.ostima.2026.100470","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100470","url":null,"abstract":"<p><strong>Purpose: </strong>The complementary information gained by combining photon counting CT (PCCT) and MRI may enhance the evaluation of the osteochondral unit. Our aim is to evaluate whether fusing PCCT and MRI improves diagnostic clarity and segmentation consistency for osteochondral lesions compared with MRI alone.</p><p><strong>Materials and methods: </strong>24 participants (15 with knee OA and 9 healthy controls) underwent PCCT and 3T MRI between October 2024 and May 2025. Images were co-registered and fused using a mutual information-based algorithm. Two musculoskeletal radiologists rated diagnostic clarity on 5-point Likert scales. Inter-reader agreement was quantified with the intraclass correlation coefficient (ICC) and Cohen kappa. Another musculoskeletal radiologist and a radiology trainee performed manual segmentations of bones, cartilage, meniscus, and osteophytes on PCCT-MRI fusion or MRI alone. Inter- and intra-rater segmentation consistency was evaluated using Dice similarity coefficient and surface Dice (sDice). Paired comparisons were analyzed with the Wilcoxon signed-rank test.</p><p><strong>Results: </strong>Fusion imaging yielded significantly higher clarity scores for cartilage thickness (3.91 vs 4.95), articular surface (3.93 vs 4.63), and osteophyte boundaries (4.00 vs 4.83; all p < .05). Inter-reader agreement improved (ICC, from 0.43 to 0.88; Cohen kappa, from 0.42 to 0.89). Quantitative analysis showed greater inter- and intra-rater consistency for cartilage (Dice, 0.70 vs 0.81; sDice, 0.66 vs 0.78) and bone (Dice, 0.93 vs 0.95; sDice, 0.61 vs 0.86; all p < .01).</p><p><strong>Conclusion: </strong>PCCT-MRI fusion enhances diagnostic clarity and inter-reader agreement. Fusion also increases segmentation consistency for cartilage and bone, supporting its potential clinical value for comprehensive osteochondral evaluation.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100470"},"PeriodicalIF":0.0,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148809543","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":"Recent advances in understanding molecular and clinical heterogeneity in osteoarthritis: one disease or several?","authors":"Tonia L Vincent, Thomas A Perry","doi":"10.1016/j.ostima.2026.100467","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100467","url":null,"abstract":"<p><p>The failure to develop disease modifying drugs in osteoarthritis (OA) has been a frustration for academia and industry as well as a disappointment for patients. Many reasons have contributed to this failure, most notably an incomplete understanding of its pathogenesis and a lack of clarity on whether OA is one disease or a collection of several different diseases. The challenges in OA are compounded by the heterogeneous clinical presentation of disease and its slow insidious course in most individuals. Patient reported pain is variable, only partly correlates with structural disease, and is complicated by the development of central sensitisation leading to pain amplification in many, especially women. Happily, in recent years, a number of substantial advances have helped to define the core tenets of disease; revealing the breadth of the biology and its variance across patients with different clinical phenotypes. These advances have included large-scale agnostic approaches to unravel the biology through multi-omic analyses, improved clinical phenotyping, and phenotype-endotype comparisons. What emerges is evidence of one core biological pathway, suggesting a shared common disease process, with evidence of biology that changes as disease progresses and with clinical phenotypes such as biological sex, age and obesity. Together, these findings support the need for both shared therapeutic strategies and more personalised approaches in OA, which are likely to enhance future treatment success.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100467"},"PeriodicalIF":0.0,"publicationDate":"2026-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148815040","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":"Perspective: One and one make three - leveraging the synergy of imaging and biomechanics in osteoarthritis research and care.","authors":"Wouter Schallig, Niels B J Dur, Mariska G H Wesseling, Rianne A van der Heijden, Jaap Harlaar, Edwin H G Oei, Erin M Macri","doi":"10.1016/j.ostima.2026.100469","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100469","url":null,"abstract":"<p><p>Mechanical stress on joint tissues is a central driver of osteoarthritis (OA), yet our understanding of OA pathomechanics remains incomplete, obstructing etiology-driven personalized treatments. Current joint assessment approaches are largely monodisciplinary. In this perspective we aim to advocate for the integration of imaging and biomechanics to assess joint function in OA research, by exploring their relative strengths and limitations and their potential synergy, towards advancing our understanding of pathomechanics in OA. Traditional structural imaging is often static and non-weightbearing, limiting its ability to elucidate pathomechanical pathways of OA. Meanwhile, biomechanical measurement approaches like motion capture are able to measure human movement during dynamic, weightbearing, and functional activities like walking or squatting, but their accuracy and precision is limited by soft tissue artefacts and modeling assumptions and constraints. We argue for the deliberate integration of imaging and biomechanics modalities to overcome their respective limitations towards a comprehensive understanding of the role of pathomechanics in OA. This can done, for example, via videoradiography-based motion analysis and personalized computational models that use additional imaging outputs from radiographs, CT or MRI. Achieving this vision of integrated multimodal analysis requires coordinated, transdisciplinary collaboration and shared resources to move beyond single-modality paradigms toward an integrated framework for pathomechanical joint health assessment, which subsequently can be used to better understand the complex relationships between mechanics, structure and biology within OA. Studies adopting this integrated approach are limited, yet emerging examples showcase the potential for advancing the field of OA research and, eventually, personalized care.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100469"},"PeriodicalIF":0.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814968","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":"3-D landmarking repeatability emphasizes challenges in scan positioning during weight bearing CT of the knee.","authors":"T D Turmezei, A Boddu, T Whitmarsh, N H Degala, J A Lynch, N A Segal","doi":"10.1016/j.ostima.2026.100466","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100466","url":null,"abstract":"<p><strong>Objective: </strong>Maintaining repeatability of positioning during knee weight bearing CT (WBCT) acquisition can be challenging. We evaluated a manual bone landmarking system and automatically derived angulation metrics to advance understanding of joint positioning repeatability.</p><p><strong>Design: </strong>Bilateral knee WBCTs for 14 recruited individuals taken at a mean ± SD interval of 14.9 ± 8.1 days using a frame and laser guidance for positioning were used in this technical study. One observer manually placed 33 bony landmarks at each knee, verified by a second observer who also placed landmarks at each end of the scan range in the centre of the bone. Landmark repeatability error was the mean ± SD absolute distance (mm) between baseline and follow-up. Automated methods for knee flexion angle (KFA), valgus and vertical positioning alignment were developed from the landmarks.</p><p><strong>Results: </strong>Most repeatable landmarks were around the patella and proximal fibula with best performance at the proximal fibula tip (1.3 ± 0.5 mm). Least repeatable landmarks were along shallow curves, e.g. central tibial margins and around the trochlea, with worst performance at the tibial tuberosity (5.5 ± 4.7 mm). Mean repeatability for 85% of placed landmarks was in the 1-4 mm range. Valgus alignment absolute repeatability error ranged from 0.1-2.1° and for KFA was 0.3-15.5°, neither dependent on KL grade severity. Worst vertical scan range placement error was ∼60 mm.</p><p><strong>Conclusion: </strong>Despite guidance systems, repeatability of KFA and vertical positioning could be optimised at the time of acquisition. This would provide a robust platform for evaluation of metrics such as meniscal extrusion and 3-D joint space width from WBCT that have shown promise in the evaluation of knee OA.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100466"},"PeriodicalIF":0.0,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814853","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":"Effusion and synovial hyperplasia: Distinct constructs in early and late-stage knee OA.","authors":"Robert Dima, Trevor Birmingham, Holly Philpott, Dianne Bryant, Aaron Fenster, C Thomas Appleton","doi":"10.1016/j.ostima.2026.100468","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100468","url":null,"abstract":"<p><strong>Objective: </strong>Ultrasound (US) permits the assessment of synovial effusion and synovial thickening (hyperplasia) in knee osteoarthritis (OA). We aimed to measure the associations of these features with radiographic OA severity and patient-reported knee-specific pain using a quantitative US image analysis approach.</p><p><strong>Methods: </strong>Patients with symptomatic knee OA were included. The Knee Injury and Osteoarthritis Outcome Score (KOOS) pain subscale, Kellgren-Lawrence (KL) grade, and lateral suprapatellar recess B-mode images were acquired for Outcome Measures in Rheumatology (OMERACT) measurement and grading. US images of effusion-synovitis were manually segmented to calculate effusion and hyperplasia area. Correlation was assessed, and associations with KL grade/KOOS pain were modelled using multivariable linear and quadratic regression with and without adjustment for age, sex, and body mass index (BMI).</p><p><strong>Results: </strong>Quantitative measures of effusion and hyperplasia area correlated strongly (ρ 0.83 to 0.86) with OMERACT grades and effusion-synovitis depth. Adjusting for age, sex, and BMI, synovial effusion and hyperplasia area are non-linearly related to radiographic severity, a pattern also observed in models of OMERACT global synovitis and effusion-synovitis depth. KOOS pain was associated with effusion-synovitis depth (β=-0.53) and borderline associated with OMERACT hyperplasia (β=-5.55), but not with OMERACT global synovitis, effusion, nor any quantitative effusion-synovitis area measures.</p><p><strong>Conclusion: </strong>Minimal US effusion-synovitis among knee OA patients with late-stage disease may indicate maladaptive remodeling of the synovium instead of reduced inflammation. Discriminating between patients with and without maladaptive synovial remodeling in early and late-stage disease should be a priority, as it may improve our ability to predict joint failure.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100468"},"PeriodicalIF":0.0,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814910","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":"The association between infrapatellar fat pad volume and knee pain in non-obese postmenopausal women.","authors":"Nima Yazdankhah, Vahid Anwari, Siwen Liu, Emily Ha, Andy Kin On Wong","doi":"10.1016/j.ostima.2026.100465","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100465","url":null,"abstract":"<p><strong>Background: </strong>The infrapatellar fat pad (IPFP) is a significant source of pro-inflammatory cytokines and may be related to knee pain. The study aim was to determine the association between knee symptoms and each of IPFP size from knee MRI and density from peripheral (p) QCT knee images in non-obese postmenopausal women.</p><p><strong>Methods: </strong>Postmenopausal women 50-85 yrs old with a body mass index (BMI) < 30 kg/m² and variable knee pain completed proton-density-weighted MRI and pQCT scans of the knee (one slice at the level of each compartment), where the IPFP was contoured to yield volumes (for MRI), areas and density (for pQCT). Knee symptoms were evaluated using the Intermittent and Constant Osteoarthritis Pain (ICOAP) and Knee Osteoarthritis Outcomes Score (KOOS) questionnaires, and OARSI physical function tests. Multivariable linear regression examined how IPFP metrics relate to these outcomes, accounting for age, BMI, use of pain medications, and Kellgren Lawrence (KL) score (≥2 vs <2).</p><p><strong>Results: </strong>Among 47 women (mean age: 61.2(8.82) yrs, BMI:22.5(3.2) kg/m², KL score ≥2: 27.6%), a 1 cm² smaller IPFP area from pQCT slices of the medial femoral compartment was associated with a 2.3% lower KOOS activities of daily living (ADL) score, a 4.7% higher ICOAP constant pain score, and a 3.9% higher ICOAP total pain score. A 1 mg/cm³ higher IPFP density from the pQCT slice of the lateral tibial compartment was associated with a 4.27% lower KOOS ADL score. Meanwhile, a 1 cm³ larger overall IPFP volume from MRI was associated with a 2% higher ICOAP intermittent pain score.</p><p><strong>Conclusions: </strong>A denser and thinner IPFP cross-sectional area but with larger overall volume - suggesting a long, dense, and skinny phenotype - may be a correlate of having more knee pain in postmenopausal women.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100465"},"PeriodicalIF":0.0,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814958","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":"Longitudinal 3D quantification of joint space from CT images: Semi-automatic segmentation and feasibility of nnU-Net automation.","authors":"Jean Baptiste Deloges, Stéphanie Uk, Jordan Cohen, Marianne Bourguignon, Jean Denis Laredo, Klaus Engelke, Christine Chappard","doi":"10.1016/j.ostima.2026.100455","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100455","url":null,"abstract":"<p><strong>Objectives: </strong>The most commonly imaging techniques used in knee osteoarthritis (OA) of the are Xrays and MRI. Computed tomography (CT) however, has his own advantages, especially three-dimensional high-resolution representation of subchondral bone and epiphyseal bone structure. Addition of a method allowing 3D joint space (JS) quantification would improve the clinical value of CT in knee OA follow-up. We here propose a method for quantifying the 3D JS from CT images using a semi-automatic and automatic segmentation based on deep learning method.</p><p><strong>Design: </strong>Fifty-four subjects (6 men, 48 women; mean age: 62.8 ± 8.4 years), from a multicenter longitudinal study, with medial compartment OA (Kellgren-Lawrence grade 2 -3) who underwent high-resolution non-weightbearing CT scans performed 36 months apart (M00 and M36). A semi-automatic segmentation that could be manually corrected was used to segment the JS and to train a nnUNet algorithm. JS thickness mapping was obtained using a 3D sphere method both for the medial (MED) and lateral (LAT) compartments at times M00 and M36. Parameters measured included mean thickness (JS_mTh), standard deviation of thickness (JS-SDTh), minimum (JS_min), maximum (JS_max) and maximum/minimum ratio (JS_max/min).</p><p><strong>Results: </strong>For the MED and LAT compartments, JS_mTh presented the best root mean square coefficient of variation (RMSCV%) about 2.7% and 2.8%, standard deviation (RMSSDmm) about 0.137 mm and 0.158 mm. JS_mTh, JS_SDTh and JS_max were significantly different for the MED compartment between M00 and M36, there is no differences for the LAT compartment, with 22% of the subjects with JS_mTh reduction beyond 0.5 mm for the MED compartment and 4% for the LAT compartment. The mean biases between semi-automatic and nn-Unet JS_mTh measurements were - 0.16mm±0.38 and -0.04±0.59 for MED and LAT compartments, respectively.</p><p><strong>Conclusion: </strong>This study shows that JS_mTh measured on non-weight bearing CT scans in patients with medial compartment OA had a satisfactory reproducibility and is able to measure significant variations between two CT-scans taken 36 months apart. Automatic segmentation based on nnUnet has the potential to replace semi-automatic segmentation.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100455"},"PeriodicalIF":0.0,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814955","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":"Soft tissue degeneration 10+ years after ACLR and their association with radiographic PTOA and knee pain development: radiomic analysis using qMRI approach in MOON nested on-site cohort","authors":"Kihwan Kim ,&nbsp;William Zaylor ,&nbsp;Sameed Khan ,&nbsp;Richard Lartey ,&nbsp;Brendan L. Eck ,&nbsp;Mei Li ,&nbsp;Sibaji Gaj ,&nbsp;Jeehun Kim ,&nbsp;Carl S. Winalski ,&nbsp;Faysal Altahawi ,&nbsp;Nancy Obuchowski ,&nbsp;Morgan H. Jones ,&nbsp;Laura J. Huston ,&nbsp;Kevin D. Harkins ,&nbsp;Michael V. Knopp ,&nbsp;Christopher C. Kaeding ,&nbsp;Kurt P. Spindler ,&nbsp;Xiaojuan Li","doi":"10.1016/j.ostima.2025.100377","DOIUrl":"10.1016/j.ostima.2025.100377","url":null,"abstract":"<div><h3>Background</h3><div>Anterior cruciate ligament reconstruction (ACLR) is the standard treatment for ACL injuries; however, over 50% of patients develop post-traumatic osteoarthritis (PTOA) within 10–20 years. Quantitative MRI (qMRI) enables early detection of cartilage and soft tissue changes, and radiomics may enhance understanding of PTOA and knee pain development.</div></div><div><h3>Objective</h3><div>This study investigates structural and soft tissue changes associated with radiographic PTOA and examines their relationship to knee pain in patients 10 years post-ACLR using qMRI-based radiomics analysis.</div></div><div><h3>Methods</h3><div>We analyzed 162 patients from the MOON nested on-site cohort. qMRI acquisitions of the knee and thigh were harmonized across sites to minimize variability. A total of 17656 Radiomic features were extracted from T1ρ and T2 maps from cartilage and menisci, thigh muscle fat fraction maps, and thigh muscle morphology images. Radiomics models for radiographic PTOA (Kellgren-Lawrence ≥ 2) and knee pain (KOOS pain ≤ 85) were developed using Boruta, minimum redundancy maximum relevance, and XGBoost.</div></div><div><h3>Results</h3><div>Eight radiomic features from cartilage, menisci, and muscle regions (quadriceps/adductors) were associated with radiographic PTOA. Six radiomic features from cartilage and menisci were linked to knee pain. Radiomics models outperformed clinical models with AUROC = 0.85 (95% CI: 0.84–0.87) and 0.79 (95% CI: 0.77–0.81) for radiographic PTOA and knee pain, respectively.</div></div><div><h3>Conclusion</h3><div>qMRI-based radiomics identifies cartilage, menisci, and muscle features linked to PTOA and knee pain post-ACLR. Future studies should explore additional tissue features and contralateral knee analyses to further elucidate PTOA progression and pain mechanisms.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"6 2","pages":"Article 100377"},"PeriodicalIF":0.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208433","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":"20 Years of the International Workshop on Osteoarthritis imaging (IWOAI): From a Small Pre-Alpine Village to a Global Community","authors":"Felix Eckstein MD ,&nbsp;David J. Hunter ,&nbsp;Ali Guermazi","doi":"10.1016/j.ostima.2026.100396","DOIUrl":"10.1016/j.ostima.2026.100396","url":null,"abstract":"<div><h3>Introduction</h3><div>The International Workshop on Osteoarthritis Imaging (IWOAI) was founded in 2007 to create a focused scientific forum dedicated to imaging (biomarkers) in osteoarthritis. In contrast to large international congresses, the workshop was conceived as a small and interactive meeting encouraging open discussion and interdisciplinary exchange among researchers from academia and industry.</div></div><div><h3>Perspective</h3><div>Since its first meeting in 2007 in the remote pre-Alpine village of Ainring, IWOAI has evolved into an annual global series of workshops bringing together international experts from many different disciplines. Despite its worldwide expansion, the workshop has remained limited in size, with up to 150 participants (South Carolina in 2012) but often smaller. The retreat-like format has allowed ample time for discussion and personal interaction. It has fostered a collaborative environment in which methodological challenges, emerging imaging technologies, publicly accessible cohorts and image repositories (e.g. the Osteoarthritis Initiative), and regulatory aspects of imaging biomarkers are discussed in depth. Informal interactions during social events and post-conference excursions have strengthened professional networks, collaborations, and personal friendships across disciplines and institutions. Over time, the workshop community also contributed to strengthening the field institutionally by establishing the International Society for Osteoarthritis Imaging (ISOAI) in 2019.</div></div><div><h3>Outlook</h3><div>As imaging technologies, AI-based automated image analysis, and data science continue to advance, imaging biomarkers are expected to play an increasingly important role in osteoarthritis clinical research and therapeutic development. Continued collaboration among academic researchers, clinicians, industry scientists and regulators will remain essential for translating imaging advances into meaningful clinical applications, trials, and ultimately disease-modifying therapy.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"6 2","pages":"Article 100396"},"PeriodicalIF":0.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208393","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":"Association of baseline MRI-defined structural features with knee symptom trajectories over nine years: Data from the osteoarthritis initiative (OAI)","authors":"Shen Liu ,&nbsp;Xiaoxiao Sun ,&nbsp;Yong Ge ,&nbsp;Thang Nhat Duong ,&nbsp;C. Kent Kwoh","doi":"10.1016/j.ostima.2025.100380","DOIUrl":"10.1016/j.ostima.2025.100380","url":null,"abstract":"<div><h3>Objective</h3><div>The development of knee symptoms in OA over time can present with multiple phenotypes. This study aims to identify MRI-defined predictors of trajectories of knee symptoms.</div></div><div><h3>Design</h3><div>All knees in the Osteoarthritis Initiative (OAI) with at least one baseline score of 0 from one of four knee symptom measurements were included. These measurements included pain severity, knee pain frequency, and the Western Ontario and McMaster Universities Osteoarthritis Index knee pain and knee function scores. The latent class mixed model (LCMM) was employed to categorize knees into different trajectories and to assess their association with various MRI-defined structural features while controlling for important covariates.</div></div><div><h3>Results</h3><div>A total of 1221 knees were grouped into two classes: 596 with a minimal knee symptom trajectory and 625 with a rapidly progressive trajectory. The class-membership model revealed that the following variables were associated with being in the rapidly progressive phenotype: bone marrow lesions (BMLs) score (Odds Ratio (OR) of 1.12 [95 % Confidence Interval (CI): 1.03, 1.22]) for each unit increase in BML total size scores; females, widespread pain, CES-D, overweight, and obesity. The age group 65 to 79 vs. that of 45 to 55 and highest year of education completed were less likely to be associated with the rapidly progressive knee pain group. Other covariates were not significant.</div></div><div><h3>Conclusion</h3><div>Two distinct phenotypes/trajectories were consistently identified across all four knee symptom measurements in a multi-trajectory model. Modifiable factors such BMLs, BMI, widespread pain and depression may serve as indicators of higher risk of rapid knee symptom progression.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"6 2","pages":"Article 100380"},"PeriodicalIF":0.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148208434","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}