Posterior Ankle Impingement Syndrome: MR Imaging Findings in Seven Patients
Bibliographic record
Abstract
PURPOSE: To report the magnetic resonance (MR) imaging findings in seven patients with posterior ankle impingement (PAI) syndrome. MATERIALS AND METHODS: Seven patients-three ballet dancers, one badminton player, one soccer player, one hockey player, and one construction worker-who presented with posterior ankle pain were assessed with MR imaging. Their clinical records and imaging studies were reviewed. The MR imaging studies were assessed for the presence of abnormal bone marrow signal intensity, osseous lesions, and soft-tissue abnormalities. RESULTS: One patient was treated surgically. In all patients, MR imaging demonstrated abnormal bone marrow signal intensity in the os trigonum and/or lateral talar tubercle, consistent with bone contusions. Two patients had a fragmented os trigonum or lateral tubercle, and two had a pseudoarthrosis of the posterolateral talus. Increased signal intensity was seen with distention of the posterior recess of the tibiotalar joint in two patients and with distention of the posterior recess of the subtalar joint in four patients. Three patients had fluid accumulation in the flexor hallucis longus tendon sheath. CONCLUSION: Bone contusions of the lateral talar tubercle and os trigonum are prevalent MR imaging findings of PAI syndrome. MR imaging clearly depicts the osseous and soft-tissue abnormalities associated with PAI syndrome and is useful in the assessment of this condition.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".