An FNA pitfall: Mammary analog secretory carcinoma mistaken for acinic cell carcinoma due to cytoplasmic granules
Bibliographic record
Abstract
In the salivary gland, a key differential feature of Mammary analog secretory carcinoma (MASC) from acinic cell carcinoma (ACC) is the lack of cytoplasmic granules. We report a case of a parotid mass incorrectly diagnosed on fine needle aspirate as acinic cell carcinoma due to many cells with basophilic granules suggesting serous acinar differention. Tumor resection revealed a tumor consistent with low grade adenocarcinoma that had eosinophilic, microvacuolar cytoplasm with distinct basophilic granules staining with PASD and mucicarmine. The diagnosis of MASC was confirmed with stains for GCDF-15, mammoglobin, and S100 and FISH consistent with a t(12;15) translocation. Relying on the absence of cytoplasmic granules as a feature to distinguish ACC from MASC is a diagnostic pitfall.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".