Diagnostic pitfalls in fine needle aspiration biopsy of the spleen
Bibliographic record
Abstract
Fine needle aspiration (FNA) of the spleen is rarely performed, due to fear of procedure complications. The objective of this study is to review the cytologic diagnoses of aspiration biopsy of the spleen performed in a cancer center. Archival material (9-year period) was reviewed and correlated with histologic and ancillary test results, when available.Forty-one splenic FNA specimens were identified. There were no reported procedure complications. Nineteen cases were diagnosed as malignant. Of these, 11 were lymphomas. Nineteen cases were diagnosed as benign. There was one false-negative case and four false-positive cases. Primary splenic neoplasms were rare and misinterpreted as malignant. It is important to be familiar with the normal cytology of this uncommonly aspirated organ in order to successfully identify neoplastic and malignant processes. The use of ancillary studies is important in the definitive classification of benign and malignant splenic lesions.
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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 | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".