Paraganglioma with highly malignant potential involving the rib - Case report and review of the literature
Bibliographic record
Abstract
Paragangliomas are rare neuroendocrine tumors arising from paraganglion cells in sympathetic or parasympathetic chains, which may develop in the abdomen, chest, skull base, and neck. As paragangliomas have a wide range of imaging features, the diagnosis often requires tissue sampling. We present a unique case of a paraganglioma which originally presented as a rib tumor. A 64-year-old male with right flank pain for 2 months’ was referred for a noncontrast renal colic CT. He was found to have a 3.7 × 3.5 cm soft tissue mass invading the left posterior 9th rib and paraspinal muscle. This was fluorodeoxyglucose F 18, (18F-FDG) avid, with no other distant metabolic activity. He underwent ultrasound-guided core biopsy which revealed a diagnosis of paraganglioma. A right thoracotomy with chest wall resection of 8, 9, and 10 ribs were subsequently performed. The tumor was removed along with a small portion of adherent lung. The tumor was positive for CD56, synaptophysin and chromogranin. S-100 highlighted occasional sustentacular cells, consistent with a pathologic diagnosis of a paraganglioma. The patient remains symptom free for 6 months’ after the operation. Our case highlights that, when paragangliomas occur within the chest wall, they may present as a rib tumor and can mimic metastasis, myeloma or other primary neoplastic etiologies originating from ribs. Both imaging and pathologic diagnosis can be challenging.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".