Magnetic Resonance Imaging and Radiographic Assessment of Carpal Depressions in Children with Juvenile Idiopathic Arthritis: Normal Variants or Erosions?
Bibliographic record
Abstract
OBJECTIVE: Magnetic resonance imaging (MRI) is playing an increasingly important role in the diagnosis and followup of juvenile idiopathic arthritis (JIA). Carpal depressions are commonly observed in healthy children and in patients with JIA. The aim of our study was to further characterize these depressions in patients with JIA. METHODS: A total of 29 MRI wrist examinations were analyzed. Depressions were classified according to morphology as either tubular or focal. Features including the presence of a vessel related to the depression, evidence of synovitis, bone marrow edema, or loss of joint space on a radiograph taken on the same day were recorded for each depression. RESULTS: A total of 173 depressions were identified in 145 carpal bones. Forty percent were capitate depressions. A third were focal depressions and two-thirds were tubular. About 10% of tubular depressions and 30% of focal depressions were associated with features suggesting true erosions, with the remainder likely to represent vascular channels and normal variants. CONCLUSION: Radiologists and clinicians should undertake caution when assessing carpal depressions on MRI because the vast majority are likely to represent normal variants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".