MétaCan
Menu
Back to cohort
Record W4416624953 · doi:10.1016/j.joca.2025.11.004

Osteoarthritis year in review 2025: Imaging

2025· article· en· W4416624953 on OpenAlexaff
Matthew S. Harkey, Anthony A. Gatti, Mylène P. Jansen, McKenzie S. White, Jessica Tolzman, Arjun Parmar, Ian Frederick, Thomas M. Link, Harvi F. Hart

Bibliographic record

VenueOsteoarthritis and Cartilage · 2025
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsWestern University
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsOsteoarthritisScope (computer science)Medical imagingMEDLINE

Abstract

fetched live from OpenAlex

OBJECTIVE: To conduct a narrative review of selected imaging studies published in the past year, with a focus on how emerging methods and multi-tissue assessments are contributing to disease characterization, early detection, and intervention strategies. DESIGN: We conducted a comprehensive search strategy of PubMed, Embase, and CINAHL for original English-language human studies on imaging in osteoarthritis, published between March 2024 and March 2025. From the 262 full-text studies that met inclusion criteria, we identified a set of representative studies through independent review and group discussion. These studies are organized into five themes that emerged from this study: effusion-synovitis, infrapatellar fat pad, muscle, subchondral bone, and subcutaneous fat. Within each theme, one highlighted study and several additional studies were synthesized, followed by a summary of cross-cutting insights and future directions. RESULTS: A total of 26 studies were included. Collectively, the studies reinforce the importance of viewing osteoarthritis as a condition involving multiple joint structures, with inflammation as a recurring feature across tissues. Muscle quality and local adiposity emerged as consistent imaging biomarkers, while accessible tools such as ultrasound and AI-enhanced radiography demonstrated potential for scalable clinical application. Links between imaging findings and biomechanics, particularly gait and loading patterns, also featured prominently. Cross-cutting themes emphasized the value of considering multiple tissues, expanding the reach of imaging to clinical and community settings, and integrating imaging with functional measures. CONCLUSIONS: Imaging research in the osteoarthritis continues to broaden in scope and application. The studies highlighted in this review illustrate how advances in methods and metrics are improving opportunities for earlier detection, more precise assessment of symptoms, and the development of targeted, structure-informed interventions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0140.015
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0170.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.255
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOsteoarthritis and CartilageSame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207