Fine-Needle Aspiration Biopsy Findings Suspicious for Papillary Thyroid Carcinoma: A Review of Cytopathological Criteria
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The objective was to evaluate the usefulness of standard suspect cytological features on fine-needle aspiration biopsy (FNAB) in predicting papillary thyroid carcinoma. STUDY DESIGN: Retrospective chart review of consecutive fine-needle biopsies of the thyroid. METHODS: The study was a retrospective review of consecutive patients presenting with a diagnosis of suspected (group 1) or positive papillary thyroid carcinoma (group 2). The frequency of standard cytological features (i.e., papillary architecture, multinucleated giant cell, nuclear pseudo-inclusions, nuclear grooves, micronucleoli, powdery chromatin, and psammoma bodies) were recorded for each group. These were compared using chi test. Sensitivity and specificity for both individual and a combination of features were calculated for patients in group 1. RESULTS: One hundred eight patients were eligible for the study (group 1, n = 57; group 2, n = 51). Fifty-one patients (89%) in group 1 and all patients in group 2 had a histopathological diagnosis of papillary thyroid carcinoma. Respectively, the most frequent features present on fine-needle aspiration biopsy in group 1 versus group 2 were nuclear grooves (79% vs. 88%), micronucleoli (74% vs. 86%), pseudo-inclusions (58% vs. 88%), and powdery chromatin (47% vs. 59%); P values for these features were P > .05, P > .05, P < .05, and P > .05, respectively. In group 1, the sensitivities of nuclear grooves and micronucleoli were 80% and 71%, respectively. The presence of psammoma bodies was associated with a specificity of 100%. A combination of nuclear grooves, micronucleoli, pseudo-inclusions, powdery chromatin, and multinucleated giant cells was 100% specific in detecting papillary thyroid carcinoma. CONCLUSION: In choosing the most appropriate management of a finding suspect for papillary thyroid carcinoma on fine-needle aspiration biopsy, the surgeon must be aware of the diagnostic importance of certain cytopathological features. The presence of a combination of these factors may allow a more confident surgical approach.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".