Advances in Musculoskeletal Imaging in Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
Over the past decade, imaging of inflammatory arthritis in juvenile arthropathies has significantly advanced due to technological improvements in the imaging modalities and elaboration of imaging recommendations and protocols through systematic international collaboration. This review presents the latest developments in ultrasound (US) and magnetic resonance imaging (MRI) of the peripheral and axial joints in juvenile idiopathic arthritis. In the field of US, the ultra-wideband and ultra-high-frequency transducers provide outstanding spatial resolution. The more sensitive Doppler options further improve the assessment and quantification of the vascularization of inflamed tissues, and shear wave elastography enables the diagnosis of tissue stiffness. Concerning MRI, substantial progress has been achieved due to technological improvements in combination with the development of semiquantitative scoring systems for the assessment of inflammation and the introduction of new definitions addressing the pediatric population. New solutions, such as superb microflow imaging, shear wave elastography, volume-interpolated breath-hold examination, and MRI-based synthetic computed tomography open new diagnostic possibilities and, at the same time, pose new challenges in terms of clinical applications and the interpretation of findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".