An atypical lipomatous tumor mimicking a giant fibrovascular polyp of the hypopharynx
Bibliographic record
Abstract
RATIONALE: Giant fibrovascular polyps (GFVPs) found in the hypopharynx are exceedingly rare. These are benign tumors which are identified by CT or MRI and usually treated based on symptoms. Even more rarely, pathology may identify one of these masses as an atypical lipomatous tumor (ALT). This paper will present a case of an ALT of the hypopharynx that was originally classified as a GFVP, highlighting the difficulty in distinguishing between them and the importance of making the correct diagnosis. PATIENT CONCERNS: An 84-year-old man presented to the emergency department with a 6-month history of a pedunculated hypopharyngeal growth, dysphagia, and intermittent dyspnea. DIAGNOSES: The mass was characterized as a GFVP by barium swallow and MRI. INTERVENTIONS: The hypopharyngeal mass was resected for obstructive symptoms and to confirm the diagnosis. Final pathology found the mass to be more consistent with an atypical lipomatous tumor (ALT). OUTCOMES: The patient's dysphagia and dyspnea resolved. He was free of recurrence at 22 months postoperative. LESSONS: Both GFVPs and ALTs are very rarely found in the hypopharynx but can be easily misclassified as one another. Imaging is useful to initially characterize the mass, but to definitively differentiate between them, pathological analysis is necessary. Although they are rare, it is important to consider both possibilities on the differential for hypopharyngeal masses. Further, accurate analysis is essential to distinguish between them because their definitive management and follow-up is different.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".