Juvenile idiopathic inflammatory myopathies assessment by magnetic resonance imaging: a scoping review of protocols, scoring systems, and applications
Bibliographic record
Abstract
BACKGROUND: Our review assessed whole body (WB) and dedicated body-part magnetic resonance imaging (DedMRI) techniques, protocols, and inflammatory scoring systems, focusing on their clinimetric properties (reliability, validity, responsiveness) in clinical and research settings of patients with juvenile idiopathic inflammatory myopathies (JIIM). METHODS: A comprehensive search of MEDLINE, EMBASE, and Cochrane databases from 2000 to 2024 identified relevant studies. RESULTS: Sixteen studies enrolling JIIM patients with MRI were reviewed, which showed heterogeneity in objectives, methodologies, and scoring systems. Four (25%) studies used quantitative assessments, while 12 (75%) employed semi-quantitative or qualitative methods in scoring MRI. WB-MRI was performed in 3 (18.7%) studies, and DedMRI in 13 (81.2%). Muscle evaluation included assessments of edema [14 (87.5%) studies], fatty infiltration [4 (25%) studies], and atrophy [6 (37.5%) studies]. T1 images were used in 9 (56.2%) studies for measuring chronic changes, with coronal views reported in 6 (37.5%). Fluid-sensitive sequences (T2 with fat saturation, STIR) were employed in all studies and were obtained in the coronal plane in 9 (56.2%). These sequences were crucial for detecting soft tissue edema related to acute/subacute inflammation. One (6%) study included diffusion and T1 post-contrast sequences. CONCLUSION: There is significant heterogeneity in MRI protocols for evaluating JIIM. Standardized WB-MRI protocols are needed to ensure consistency and comparability across studies and institutions, optimize assessments of disease activity, treatment response, and follow-up in JIIM patients. Standardization should enhance the reliability of MRI for diagnosing and monitoring JIIM in clinical and research settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".