Osteoarthritis imaging最新文献

{"title":"Regional depth-specific subchondral bone density in osteoarthritic and normal distal femora: In vivo precision and exploratory comparisons.","authors":"J D Johnston, A E Sacher, C E McLennan, J A Lynch, T Neogi, D J Hunter, D R Wilson, S A Kontulainen","doi":"10.1016/j.ostima.2026.100478","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100478","url":null,"abstract":"<p><strong>Objective: </strong>To test the in vivo precision of regional and focal bone mineral density (BMD) measures in normal and osteoarthritic (OA) distal femora.</p><p><strong>Design: </strong>Fourteen participants (3:11 male:female; mean age: 49.9 (standard deviation: 11.9) years) were recruited and classified as normal (n = 7) or OA (n = 7). Each participant was scanned three times over two days using clinical quantitative computed tomography. Two BMD assessments were evaluated at the distal femur: mean regional and peak focal densities. BMD measures were assessed across three depths (0-2.5, 2.5-5, 5-7.5 mm) and six sub-regions of the distal femur (medial/lateral, anterior/central/posterior). We assessed precision using root mean square coefficients of variation (CV%_RMS). To explore potential differences between OA and normal distal femora, we performed parametric t-tests and non-parametric Mann-Whitney statistical analyses and also determined Cohen's d effect sizes.</p><p><strong>Results: </strong>CV%_RMS ranged from 1.6% to 3.6% (average: 2.2%) for measures of regional BMD while CV%_RMS ranged from 1.6% to 6.9% (average: 2.7%) for measures of focal BMD. Statistical comparisons indicated lower BMD in OA distal femoral in the medial-anterior region at depths of 2.5-5 mm (regional:18%; focal:19%) and 5-7.5 mm (regional:23%; focal:25%). All other BMD measures were similar between normal and OA distal femora (p > 0.05). Cohen's d effect sizes ranged from -1.8 to 0.76.</p><p><strong>Conclusions: </strong>This technique offers precise measures of subchondral BMD at the distal femur. This approach has the potential to quantify and distinguish OA-related alterations in subchondral BMD at the distal femur.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100478"},"PeriodicalIF":0.0,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149208273","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":"Photon-counting CT in musculoskeletal imaging: New horizon for understanding bone health in osteoarthritis.","authors":"Edwin H G Oei, Camilla Toft Nielsen, Thom van der Laan, Marcel Van Straten, Felix Christoph Müller, Mikael Ploug Boesen","doi":"10.1016/j.ostima.2026.100477","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100477","url":null,"abstract":"<p><p>Osteoarthritis is a heterogeneous disease affecting many joint tissues. The significant role of bone, and in particular abnormalities in the subchondral bone, in OA is increasingly understood. Bone marrow lesions are believed to play an important role in OA symptom perception and progression of OA. Consequently, there is an increasing interest in the characterization of subchondral bone and bone marrow lesions by means of imaging. Computed tomography (CT) has shown to be a suitable imaging method to visualize various bony abnormalities in OA, however, the spatial resolution of conventional CT scanners is limited for assessing trabecular bone architecture. Photon-counting CT (PCCT) is a new CT technology that has the potential to overcome the resolution limitations of conventional CT by using a completely different detector design. In this perspective paper, we discuss the technical principles of PCCT and the advantages for imaging of musculoskeletal diseases and OA bone health in particular. We highlight initial studies applying PCCT for imaging different tissues involved in OA, including subchondral bone, and discuss the potential of PCCT in advancing clinical OA research.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100477"},"PeriodicalIF":0.0,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149751","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: Mesenchymal stromal cells and PRP in osteoarthritis: Hope, hype and the hard evidence.","authors":"David Hunter, DingYuan Fan","doi":"10.1016/j.ostima.2026.100475","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100475","url":null,"abstract":"<p><p>In the absence of approved disease-modifying therapies for osteoarthritis (OA), regenerative therapies have emerged as promising interventions that have attracted considerable enthusiasm among patients, clinicians, and researchers. This interest has been particularly prominent in knee OA, where intra-articular orthobiologic interventions are most commonly studied and clinically adopted. However, the broad concept of \"regeneration\" encompasses a diverse range of interventions, including mesenchymal stromal cells (MSCs), platelet-rich plasma (PRP), and other orthobiologic products, which differ substantially in their biological rationale and supporting evidence. Despite increasing clinical adoption, the evidence underpinning these therapies has not kept pace with expectations. In this perspective, we examine regenerative therapies for osteoarthritis through the lens of hope, hard evidence, and hype. By critically evaluating the current clinical evidence and exploring how commercialisation and media narratives have shaped expectations and accelerated clinical adoption, we argue that a more balanced view of regenerative therapies is warranted until robust evidence from well-designed phase 3 trials becomes available.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100475"},"PeriodicalIF":0.0,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119780","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":"Diagnostic AI tools in musculoskeletal imaging-Present and future.","authors":"Sven Nebelung, Daniel Truhn","doi":"10.1016/j.ostima.2026.100476","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100476","url":null,"abstract":"<p><p>Artificial intelligence (AI) is widely promoted as the next step in musculoskeletal (MSK) imaging, yet its translation into routine clinical care, including osteoarthritis (OA), has been selective and challenging. This Perspective summarizes where diagnostic MSK AI tools stand today and argues that the central question is not whether models perform well in benchmarks, but whether they create measurable clinical value. Based on a keynote presentation at IWOAI 2026, we relate diagnostic AI tools in MSK imaging to the theme \"Linking OA Tissues\" by asking whether current AI tools can connect tissue-level imaging findings with whole-joint disease, longitudinal change, and clinical context. Drawing on the regulatory landscape and peer-reviewed evidence, we show that AI tools have been selectively translated into clinical routine: radiographic morphometry and fracture detection dominate among commercially available products because they are narrow, standardized tasks with transparent, easily verifiable outputs and an obvious clinical need. By contrast, MRI, the modality on which advanced OA assessment largely depends, remains a bottleneck. OA is a particularly challenging target because it is a multi-tissue, whole-joint, longitudinal, and context-dependent disease for which binary, single-task outputs are too crude. Furthermore, we propose a deliberately non-quantitative framework in which useful AI is the product of model performance, relevant endpoints, workflow fit, and human-AI interaction; failures of translation typically reflect deficits in the latter three rather than in model performance alone. Realizing clinical value in MSK and OA imaging will require validation against patient-relevant endpoints, attention to how readers interact with AI, and reference standards that go beyond curated benchmarks.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100476"},"PeriodicalIF":0.0,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119770","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":"Weight-bearing CT imaging of the lower limb: lessons learned and future opportunities from the multicenter osteoarthritis study (MOST).","authors":"Neil A Segal, Nasim Nosrati Nia, John A Lynch","doi":"10.1016/j.ostima.2026.100474","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100474","url":null,"abstract":"<p><strong>Objective: </strong>To summarize findings from weight-bearing computed tomography (WBCT) studies within the Multicenter Osteoarthritis Study (MOST) and discuss lessons learned and highlight their potential for improving understanding osteoarthritis (OA) structural progression.</p><p><strong>Design: </strong>Narrative review of WBCT studies within MOST, a multicenter longitudinal prospective cohort study. WBCT of bilateral knees was acquired for 824 participants during the third cycle (MOST3; 2015-2020), and bilateral hips, knees, and feet/ankles in 1647 participants during the fourth cycle (MOST4; 2023-2028).</p><p><strong>Results: </strong>MOST3 established that WBCT-derived tibiofemoral 3D joint space width (JSW) is highly reproducible (ICC=0.90-0.97) and strongly correlated with radiographic JSW (r = 0.91-0.97), although radiographs overestimated JSW by ∼2 mm. Medial tibiofemoral JSW on WBCT correlated more strongly with cartilage/meniscal morphology on MRI than radiographic JSW, and 3D JSW was more responsive to 2-year structural change than radiographic JSW. WBCT more sensitively detected patellofemoral cartilage abnormalities, osteophytes, subchondral cysts, and meniscal extrusion than radiographs and non-weight-bearing MRI. CT OA of the Knee Score (COAKS) demonstrated substantial reliability (weighted κ=0.66-0.87; ICC >0.81), and a bone-shape C-score predicted two-year worsening of knee pain in women and structural worsening in men. Narrower 3D JSW was associated with worse physical function.</p><p><strong>Conclusions: </strong>WBCT provides a reliable, physiologically-loaded 3D joint assessment that is more sensitive and responsive than radiographs, with practical advantages over MRI and MDCT in acquisition time, radiation dose, and infrastructure. These properties support its clinical potential for earlier OA detection in lower limb OA phenotyping and structural progression monitoring. MOST4 offers opportunities to validate WBCT imaging biomarkers across the lower limb kinetic chain.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100474"},"PeriodicalIF":0.0,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149042817","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":"Integrating deep learning-based radiographic features with demographic variables for hip osteoarthritis prediction: development and validation using individual participant data from the World COACH Consortium.","authors":"Myrthe A van den Berg, Gijs van Tulder, Harbeer Ahedi, Nigel K Arden, Sita M A Bierma-Zeinstra, Fleur Boel, Cindy G Boer, Michiel M A van Buuren, Flavia M Cicuttini, Timothy F Cootes, David T Felson, Willem Paul Gielis, Joshua Heerey, Joanne Kemp, Graeme Jones, Stefan Kluzek, Nancy E Lane, Claudia Lindner, Joyce B J van Meurs, Andrea B Mosler, Amanda E Nelson, Michael C Nevitt, Edwin H Oei, Jos Runhaar, Harrie Weinans, Jesse H Krijthe, Rintje Agricola","doi":"10.1016/j.ostima.2026.100472","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100472","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate whether hybrid models integrating deep learning (DL) features from baseline radiographs and demographic information can predict incident radiographic hip osteoarthritis (RHOA) and to compare their performance to models using radiographic or demographic information in isolation.</p><p><strong>Design: </strong>Data were pooled from seven prospective cohorts within the Worldwide Collaboration on OsteoArthritis prediction for the Hip (World COACH) consortium. Incident RHOA was defined as hips without RHOA at baseline that developed RHOA within four to eight years. From baseline radiographs, radiographic features were extracted with a DL-based feature extractor that was either unoptimized, optimized with baseline RHOA grades, or optimized with follow-up RHOA grades. The baseline RHOA grade acted as conventional reference. Baseline age, body mass index, and birth-assigned sex were considered as demographic predictors. Using internal and leave-one-cohort-out cross-validation, we assessed the predictive performance of models using only demographic predictors, only radiographic predictors, or both modalities combined (hybrid).</p><p><strong>Results: </strong>In the pooled dataset of 25,090 hips, 5.1% developed incident RHOA in four to eight years. Both the radiographic-only and hybrid models including follow-up-optimized radiographic features showed the best discriminative performance (AUC: 0.81 ± 0.01), whereas the demographic-only model showed an AUC of 0.71 (0.01) during internal cross-validation. The performance of the hybrid model including follow-up-optimized features dropped to an average AUC of 0.64 ± 0.09 during leave-one-cohort-out cross-validation.</p><p><strong>Conclusions: </strong>Hybrid models combining DL-based features from baseline radiographs with demographic predictors show promise for RHOA risk identification, though demographics provided limited complementary information and performance declined in leave-one-cohort-out cross-validation.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100472"},"PeriodicalIF":0.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149042765","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":"Mechanobiology of the osteochondral unit using advanced imaging in preclinical osteoarthritis models.","authors":"Pholpat Durongbhan, Lucinda Ae Evans, Aikta Sharma, Andrew A Pitsillides, Kathryn S Stok","doi":"10.1016/j.ostima.2026.100473","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100473","url":null,"abstract":"<p><p>Traditional preclinical studies of osteoarthritis (OA) frequently rely on static, cross-sectional assessments that obscure the dynamic sequence of tissue compensation and failure. To capture the dynamic trajectory of OA and allow for the ready unravelling of any mechanoadaptive changes, an interpretive shift is required toward image-guided approaches that quantify temporal, spatial, and functional alterations. This review highlights how advanced 3D X-ray micro-computed tomography (microCT) has become a critical asset for exploring mechanisms driving joint pathology and pathomechanics in preclinical animal models. Temporally, longitudinal in vivo imaging allows direct tracking of joint malalignment and subchondral bone remodelling over time. The use of contrast agents permits imaging of articular cartilage, enabling the spatial evaluation of coordinated multi-tissue degeneration. Moreover, investigating the relationship between structural changes and functional alterations can be interrogated within the intact joint by combining synchrotron radiation-based microCT with digital volume correlation (DVC) to resolve the loaded osteochondral unit and quantify deformation at the lacuna scale. This highlights the role of articular calcified cartilage in OA-induced load transfer and microdamage. Crucially, translating these high-dimensional tomographic datasets into reliable biomarkers of disease trajectory relies on adopting reproducible, automated quantitative image analysis tools and standardised reporting conventions. Ultimately, advanced tomographic techniques reposition OA imaging from being an endpoint assay to providing temporal, spatial, and functional markers that highlight mechanistic targets for future investigation.</p>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100473"},"PeriodicalIF":0.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009132","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":"Editorial: Tissues - linking them all together.","authors":"Felix Eckstein, Simo Saarakkala","doi":"10.1016/j.ostima.2026.100471","DOIUrl":"https://doi.org/10.1016/j.ostima.2026.100471","url":null,"abstract":"","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":" ","pages":"100471"},"PeriodicalIF":0.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009048","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,&nbsp;Thomas A. Perry","doi":"10.1016/j.ostima.2026.100467","DOIUrl":"10.1016/j.ostima.2026.100467","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"6 3","pages":"Article 100467"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","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":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sex differences in cartilage anatomy, imaging & treatment response","authors":"Felix Eckstein","doi":"10.1016/j.ostima.2026.100395","DOIUrl":"10.1016/j.ostima.2026.100395","url":null,"abstract":"<div><h3>Objective</h3><div>To review findings on sex differences in cartilage anatomy, cartilage imaging, and treatment in osteoarthritis, based on an invited presentation held at the International Workshop of Osteoarthritis Imaging (IWOAI) 2025.</div></div><div><h3>Design</h3><div>A non-systematic literature search (Pubmed) and consultations with experts. Additionally, comparative radiographic joint space width (JSW) and femorotibial cartilage thickness data were obtained from 2396 knees (from 2004 male and female Osteoarthritis Initiative participants), covering radiographic joint space narrowing (JSN) grades 0–3. Sex differences in JSW and cartilage morphology were related to those of other articular and periarticular tissues in qualitative form.</div></div><div><h3>Results</h3><div>Men displayed greater JSW and femorotibial cartilage thickness than women. For JSW, but not for cartilage thickness, sex differences disappeared with greater joint space narrowing (JSN) grade. The sex difference in cartilage thickness was maintained after adjusting for relevant covariates, e.g. body height. These morphological findings differ from those in cartilage transverse relaxation time (T2) and from other (peri‑) articular tissues. Preliminary findings suggest that men may respond more strongly to surgical and anabolic pharmacological cartilage therapy.</div></div><div><h3>Conclusions</h3><div>Between and within species, large differences exist in the heterogeneity of morphological traits. Sexual dimorphism can be male- or female biased in different species; within humans some musculoskeletal characteristics are greater in men and others in women. Men display “genuinely” greater JSW, cartilage thickness, and joint surface areas than women, the latter potentially contributing to a lower joint pressure and lower incidence in knee osteoarthritis than in women. Sex-differences in cartilage treatment response deserve deeper exploration.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"6 3","pages":"Article 100395"},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148964960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}