Primary pulmonary meningioma or large meningothelial-like nodule? A clinicopathological dilemma
Bibliographic record
Abstract
Introduction: Primary pulmonary meningiomas (PPMs) are rare ectopic tumors that potentially arise from displaced embryonic arachnoid cells that are isolated outside the dura mater. Its presence outside of the central nervous system poses inherent challenges. We report a case of a primary pulmonary meningioma discovered after a 12-year follow-up for a presumed benign lung lesion. Case Report: A 47-year-old male with a 17-year history of severe, undiagnosed right-sided subxiphoid and periumbilical pain was monitored for a right middle lobe lung mass that grew from 2.2 cm to 3.4 cm over 12 years. Initially, the transthoracic needle biopsy suggested a solitary fibrous tumor. Video-assisted thoracoscopic wedge resection with concomitant biopsy displayed the characteristic histomorphology, including whorling and psammomatous calcification. Positive immunohistochemical staining for epithelial membrane antigen (EMA) and progesterone receptor (PR) supported the diagnosis of clinically confirmed PPM. Conclusion: This interesting case illustrates that primary pulmonary meningiomas can mimic other tumors and may be associated with atypical symptoms like chronic pain. In this 12-year monitored case, surgery relieved the patient’s debilitating 17-year-long chronic pain. Additionally, a novel nomenclature system was developed to help distinguish between PPMs and large meningothelial-like nodules.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| 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".