Metastatic adenoid cystic carcinoma with high‐grade transformation (“dedifferentiation”) in pleural effusion and neck lymph node: A diagnostic challenge on cytology?
Bibliographic record
Abstract
High-grade transformation (HGT) or "dedifferentiation" is an uncommon phenomenon among salivary gland carcinomas including adenoid cystic carcinoma (ACC), which is important to recognize because it is associated with increased tumor aggressiveness, with a high propensity for lymph node and distant metastases. ACC with HGT is histologically characterized by a distinct population of poorly differentiated cells with loss of the typical biphasic ductal and myoepithelial differentiation seen in conventional ACC, associated with pleomorphism, necrosis and increased mitotic activity. We report the cytologic features of a case of metastatic ACC-HGT in cervical lymph node and effusion, which, to the best of our knowledge, have not been described previously. When ACC presents both in atypical locations and with HGT, the danger of misdiagnosis is increased if the clinical history is lacking, incomplete or inaccurate. Since ACC-HGT are rare (and possibly underdiagnosed) and do not have a specific set of cytological and/or immunohistochemical features, it is important for practicing cytopathologists to be aware of the possibility of encountering them, especially in specimens from patients with a history of ACC, in order to render the correct diagnosis.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 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".