Fine‐needle aspiration of primary and recurrent benign fibrous histiocytoma: Classic, aneurysmal, and myxoid variants
Bibliographic record
Abstract
There is a limited number of correlative cytopathological studies of fibrous histiocytoma (FHC). To better define cytopathological criteria of diagnosis, we have reviewed fine-needle aspirates (FNA) from 36 FHCs (32 classical, 1 myxoid, and 3 aneurysmal variants on corresponding histological sections). Original cytological diagnoses were benign in 33 (91.7%) cases (22 accurate) and false positive in 3 (8.3%) cases. All smears were surprisingly homogenous and composed of histiocytic cells with finely vacuolated cytoplasm in 27 (75%) cases, small regular spindle cells in 25 (69%) cases, and giant cells in 17 (47%) cases. Histiocytic cells were attached to vascular structures in 9 (25%) cases. Slight cytonuclear atypia was seen in five (14%) cases. Three (8.3%) cases showed numerous siderophages. In two (5.6%) cases, there were abundant inflammatory backgrounds and in one (3%) case there was a scant myxoid background. Storiform patterns, round cells, prominent atypia, necroses, or mitotic figures were not seen. FHC should be differentiated from other benign, low- and intermediate-grade spindle-cell neoplasms such as low-grade fibrosarcoma, dermatofibrosarcoma protuberans, nodular fasciitis, spindle-cell malignant melanoma, and monophasic synovial sarcoma. Some cases may be misinterpreted as malignant, especially in cases of recurrence or in patients with a cancer history.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".