Sonography of Intramuscular Myxomas
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to retrospectively review sonographic images of pathologically proven soft tissue myxomas to determine whether a sonographic correlate to the bright rim and bright cap signs described in the magnetic resonance imaging literature is present. METHODS: The study group consisted of 6 patients with pathologically proven soft tissue myxomas (1 man and 5 women; age range, 41-72 years; mean, 56.5 years). The available sonographic images for each subject were retrospectively reviewed by 2 authors (L.F. and K.F.), with agreement reached by consensus. Among other findings, images were also reviewed for a peripheral rim of increased echogenicity (termed the "bright rim sign") and for the presence of a triangular hyperechoic area adjacent to at least one of the poles of the mass (termed the "bright cap sign"). RESULTS: The bright rim and bright cap signs were seen in 5 (83%) of the 6 myxomas. The single case without the bright cap sign was not the same case as the one lacking the bright rim sign. CONCLUSIONS: The sonographic bright rim and bright cap signs were associated with 5 (83%) of the 6 intramuscular myxomas. These findings correlate with their magnetic resonance imaging equivalents, which are well documented in the literature, due to muscle atrophy and adjacent fatty infiltration. Recognition of these features may assist in a more accurate sonographic diagnosis before biopsy.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".