Morphological parameters able to predict <scp><i>BRAF<sup>V600E</sup></i></scp>‐mutated malignancies on thyroid fine‐needle aspiration cytology: Our institutional experience
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Bibliographic record
Abstract
BACKGROUND: The BRAF(V600E) mutation is the most common diagnostic/prognostic marker in papillary thyroid carcinoma (PTC). Its evaluation is typically performed with DNA-based techniques; nonetheless, a few articles have recently proposed the morphological prediction of BRAF(V600E) in histological PTCs. We investigated this morphological parameter in our cytological series. METHODS: We re-analyzed all 72 cytohistological samples diagnosed as positive for malignancy (favoring PTC) on fine-needle aspiration cytology from January 2012 to December 2013. We included 22 male patients and 50 female patients. The cytological cases were processed with liquid-based cytology. We performed molecular analysis and immunocytochemistry for the VE1 BRAF(V600E) antibody. RESULTS: We reported 47 mutated cases and 25 wild-type (WT) cases with 100% cytohistological concordance. The cytological evaluations revealed plump cells (abundant eosinophilic cytoplasm and PTC nuclei) in all 47 mutated cases, with only 6 having a focal plump cell component (≤20% cells). Furthermore, 5 of the 25 WT cases showed focal plump cells. A distinctive sickle nuclear shape was found only in the mutated cases. VE1 yielded 100% positivity for all 24 mutated cases that were tested, including 3 cases with focal plump cells. CONCLUSIONS: We demonstrated that the BRAF(V600E) mutation might be predicted in cytological samples on the basis of some specific morphological features. Although the detection of plump cells (mainly focal) was also observed in WT cases, the detection of sickle-shaped nuclei provided the highest specificity and sensitivity as a predictive mutational parameter. These morphological features might be a valid tool for selecting cases for molecular analysis.
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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 | 0.000 | 0.001 |
| 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 it