Whole-body Magnetic Resonance Imaging in Psoriatic Arthritis, Rheumatoid Arthritis, and Healthy Controls: Interscan, Intrareader, and Interreader Agreement and Distribution of Lesions
Bibliographic record
Abstract
OBJECTIVE: Whole-body MRI (WBMRI) is a promising technique for monitoring patients' global disease activity in inflammatory joint diseases. The validation of WBMRI is limited; no studies have evaluated the test-retest agreement (interscan agreement) and only a few have assessed the intra- and interreader agreement. Therefore, we first examined the interscan agreement of WBMRI in patients with psoriatic arthritis (PsA), rheumatoid arthritis (RA), and healthy controls (HC); and second, we evaluated the intra- and interreader agreement and agreement with conventional hand MRI and determined the distribution of lesions. METHODS: WBMRI was performed twice at a 1-week interval in 14 patients with PsA, 10 with RA, and 16 HC. Images were anonymized and read in pairs with unknown chronological order by experienced readers according to the Outcome Measures in Rheumatology (OMERACT) WBMRI, Canada-Denmark MRI, and the RA MRI scoring system (RAMRIS) and the PsA MRI scoring system (PsAMRIS). Ten image sets were reanonymized for assessment of intra- and interreader agreement. Agreement was calculated on lesion level by percentage exact agreement (PEA) and Cohen κ, and for sum scores by absolute agreement, single-measure intraclass correlation coefficient (ICC). RESULTS: WBMRI of the spine and peripheral joints and entheses generally showed moderate to almost perfect interscan agreement with PEA ranging from 95% to 100%, κ 0.71-1.00, and ICC 0.95 to 1.00. Intra- and interreader data generally showed moderate to almost perfect agreement. Agreement with conventional MRI varied. More lesions were found in patients than in HC. CONCLUSION: WBMRI showed good interscan agreement, implying that repositioning of the patient between examinations does not markedly affect scoring of lesions. Intra- and interreader agreement were moderate to almost perfect.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".