Spotty Bone Marrow: A Frequent MRI Finding in the Feet of Ballet Dancers
Bibliographic record
Abstract
INTRODUCTION: Bone marrow signal abnormalities on magnetic resonance imaging (MRI) are common in athletes. However, few studies evaluate the MRI appearance of bone marrow in the feet of ballet dancers. Our study aims to describe the "spotty bone marrow" (SBM) pattern in the tarsal bones of a cohort of ballet dancers, establishing its prevalence, distribution, potential associations, and evolution. Methods: Eighty-six MRIs of 68 ankles in 56 ballet dancers were retrospectively reviewed for mar- row signal alterations, which were classified as focal or SBM (defined as patchy fluid-sensitive signal hyperintensity spanning more than one location or tarsal bone). When SBM involved the talus, its anatomic distribution in the bone and morphologic pattern were recorded. Additional osseous and soft tissue findings were documented. For subjects with more than one MRI of the same ankle, the SBM's evolution was monitored. Results: Spotty bone marrow was identified in 44 ankles (65%). Spotty bone marrow was isolated to the talus (44%), present in all tarsal bones (25%), or distributed between the talus and one to three other tarsal bones (31%). In the talus, The SBM involved the entire bone (65%), the neck and body (31%), or the head and neck (4%). The SBM most commonly showed a random morphologic pattern (87%) but occasionally showed a peripheral predominance (13%). There was no statistically significant difference in the prevalence of other pathologies in ankles with and without SBM. In eight ankles with a follow-up MRI, the SBM worsened in one, remained stable in two, and improved in five ankles. None progressed to a stress fracture. Conclusion: Spotty bone marrow is an MRI finding frequently encountered in ballet dancers. It is usually self-limiting and should not be misinterpreted as a more aggressive pathology.
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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 | 0.001 |
| 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 | 0.000 |
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".