Fine‐needle aspiration biopsy of breast adenomyoepithelioma: A potential false positive pitfall and presence of intranuclear cytoplasmic inclusions
Bibliographic record
Abstract
Cytologic diagnosis of adenomyoepithelioma can be very challenging. We report fine needle aspiration cytology (FNAC) findings of a benign adenomyoepithelioma. The cytologic features are characterized by hypercellularity and the presence of numerous atypical dispersed cells with epithelioid morphology and intact cytoplasm. The nuclei showed stippled chromatin, irregular nuclear membrane, and prominent eosinophilic nucleoli. No necrosis or mitoses were seen. The presence of naked nuclei, and extensive intranuclear cytoplasmic inclusions were identified and raised the possibility of adenomyoepithelioma. Immunohistochemically, the atypical cells showed strong positivity for myosin heavy chain, p63, and CK5/6, while the epithelial cells reacted with estrogen receptors. This immunophenotypic pattern supports the myoepithelial origin of the atypical cell proliferation and favors the diagnosis of benign adenomyoepithelioma. However, biopsy was recommended to exclude malignancy. Histologically, the tumor showed prominent myoepithelial cells with significant atypia, intranuclear cytoplasmic inclusions, and dense cytoplasm. No evidence of malignancy was identified. In conclusion, we report a case of adenomyoepithelioma with a significant cytological atypia that may result in confusion with malignant breast tumors. The presence of intranuclear cytoplasmic inclusions, naked nuclei, and expression of myoepithelial markers should provide clues to the right diagnosis and benign nature of this lesion. Cytopathologists should be familiarized with this entity to avoid a misdiagnosis of carcinoma.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".