Diagnostic pitfalls in fine needle aspiration of solitary pulmonary nodules: two cases with radio-cyto-histological correlation
Bibliographic record
Abstract
BACKGROUND: Fine needle aspiration is an important tool for diagnosis and preoperative evaluation of solitary nodules of the lung. It provides a definitive diagnosis in most patients at low cost with minimal trauma. However, because of the nature of the study and the presentation of the cells in a more distorted and incomplete tissue structure than a histological slide, false positive results can occur. Prior detailed clinical knowledge about the patient, procedures and methods of radiology in obtaining the aspirate specimen is extremely useful in the accurate interpretation of fine needle cytological specimens. CASE PRESENTATION: We report two cases of solitary pulmonary nodules in two elderly females, which were initially diagnosed as malignant by fine needle aspiration biopsy. Both cases subsequently underwent pulmonary lobectomy in which, one turned out to be a pulmonary hamartoma and the other appeared to be a middle lobe syndrome of the right lung with liver tissue contamination at the time of fine needle aspiration of the lung. CONCLUSIONS: We are now strong believers that much care must be taken in the interpretation of fine needle aspiration of solitary nodules of the lung. Complete study of the entire specimen, including the cell block, is warranted, since what one interprets as malignant, could have different features in another part of the sample. Last but not the least, prior knowledge of the complete clinical history of the patient together with the salient radiological findings would greatly facilitate the cytopathologist to reach an accurate diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".