Iterative Development and Reliability of the OMERACT Hand Osteoarthritis MRI Scoring System
Bibliographic record
Abstract
OBJECTIVE: To develop and test the interreader reliability of the OMERACT Hand Osteoarthritis Magnetic Resonance Scoring System (HOAMRIS) for assessment of structural and inflammatory hand OA features in the interphalangeal joints. METHODS: The HOAMRIS was developed through an iterative process. Selection of features and their scaling was agreed upon through consensus by members of the OMERACT Magnetic Resonance Imaging (MRI) Task Force, using the Oslo Hand Osteoarthritis (OA) MRI Score system as a template. Two reliability exercises were performed, in which 6 and 4 readers participated, respectively. After the first exercise, an atlas was developed and used in the second exercise to facilitate reading. In each exercise, readers independently scored 8 MRI scans from the Oslo Hand OA cohort (coronal/axial short-tau inversion recovery and coronal/axial/sagittal T1-weighted fat-suppressed pre-/post-Gadolinium images). Interreader reliability was assessed by intraclass correlation coefficients (ICC), percentage exact and close agreement (PEA/PCA). RESULTS: The preliminary OMERACT HOAMRIS included assessment of synovitis, erosive damage, cysts, osteophytes, cartilage space loss, malalignment, and bone marrow lesions (BML), of which all were scored on a 0-3 scale for normal, mild, moderate, and severe (increments of 0.5 for synovitis, erosive damage, and BML). In the first exercise, most features showed good to very good ICC values (0.64-0.94), except synovitis (0.34). In the second exercise using the atlas, the ICC values were > 0.74 for all MRI features, and the PEA/PCA values were higher than in the first exercise. CONCLUSION: A preliminary HOAMRIS with good to very good interreader reliability was developed. Longitudinal studies are needed to assess its sensitivity to change.
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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 | 0.085 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".