Fine‐needle aspiration cytology with histological correlation of chordoma metastatic to the lung: A diagnostic dilemma
Bibliographic record
Abstract
Chordoma is an uncommon tumor initially believed to be benign due to the rarity of its metastasis. Cytological, morphological, and immunohistochemical features of chordoma, relating to its origin from notochordal remnants, allows for its accurate diagnosis. A 75-year-old man with a known history of tuberculosis (TB) presented with shortness of breath and a dry cough. A chest X-ray demonstrated a diffuse, infiltrative miliary pattern in both lungs. Bronchial washings submitted for culture and cytological examination did not identify any tuberculous bacilli. Fine needle aspiration cytology (FNAC) showed focal areas of myxoid regions with small, round, uniform mononuclear cells. There was a documented past history of chordoma arising from the L2 vertebrae. Because of the rarity of this lesion in the lung and the limited diagnostic material available with a clinical history of TB and lumbar chordoma, the pathological report rendered on the FNAC was "atypical cells suspicious for metastatic chordoma." A wedge biopsy of the lung confirmed the presence of metastatic pulmonary chordoma. Despite palliative treatment, he died within a year. Although the metastatic potential of chordomas has been recognized and documented, to the best of our knowledge, metastasis of chordoma to the lung diagnosed by FNAC with cytohistological correlation has not been previously reported in the English literature.
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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 | 0.002 | 0.011 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".