Development and Reliability of a Preliminary Foot Osteoarthritis Magnetic Resonance Imaging Score
Bibliographic record
Abstract
OBJECTIVE: Foot osteoarthritis (OA) is very common but underinvestigated musculoskeletal condition and there is little consensus as to common magnetic resonance imaging (MRI) features. The aim of this study was to develop a preliminary foot OA MRI score (FOAMRIS) and evaluate its reliability. METHODS: This preliminary semiquantitative score included the hindfoot, midfoot, and metatarsophalangeal joints. Joints were scored for joint space narrowing (JSN; 0-3), osteophytes (0-3), joint effusion/synovitis, and bone cysts (present/absent). Erosions and bone marrow lesions (BML) were scored (0-3) and BML were evaluated adjacent to entheses and at sub-tendon sites (present/absent). Additionally, tenosynovitis (0-3) and midfoot ligament pathology (present/absent) were scored. Reliability was evaluated in 15 people with foot pain and MRI-detected OA using 3.0T MRI multi-sequence protocols, and assessed using ICC as an overall score and per anatomical site. RESULTS: Intrareader agreement (ICC) was generally good to excellent across the foot in joint features (JSN 0.90, osteophytes 0.90, effusion/synovitis 0.46, cysts 0.87), bone features (BML 0.83, erosion 0.66, BML entheses 0.66, BML sub-tendon 0.60) and soft tissue features (tenosynovitis 0.83, ligaments 0.77). Interreader agreement was lower for joint features (JSN 0.43, osteophytes 0.27, effusion/synovitis 0.02, cysts 0.48), bone features (BML 0.68, erosion 0.00, BML entheses 0.34, BML sub-tendon 0.13), and soft tissue features (tenosynovitis 0.35, ligaments 0.33). CONCLUSION: This preliminary FOAMRIS demonstrated good intrareader reliability and fair interreader reliability when assessing the total feature scores. Further development is required in cohorts with a range of pathologies and to assess the psychometric measurement properties.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".