Fine‐needle aspiration of leiomyosarcoma: A correlative cytohistopathological study of 96 tumors in 68 patients
Bibliographic record
Abstract
To better define the cytological features of various leiomyosarcoma (LMS) variants, we reviewed the fine-needle aspiration material and the corresponding histologic sections of 96 tumors in 68 patients. Histological variants of LMS were as follows: 80 (83.3%) were of the classical/usual, seven (7.3%) were epithelioid, and nine (9.4%) were myxoid. Review of original cytology reports showed that 23 (24%) tumors were diagnosed as LMS and 69 (71.8%) as other types of malignancies. Two (2.1%) cases were reported as suspicious and two (2.1%) were unsatisfactory. The classical variants of LMS were characterized cytologically by various proportions of spindle-shaped, cohesive, small- or large-sized cells arranged in parallel alignment. Large spindle, round, binucleated, giant cells with intracytoplasmic granulations were frequently seen. Blunt-ended nuclei, intranuclear inclusions and mitotic figures were occasionally seen, as well as stromal fragments. The epithelioid tumors were composed of an admixture of small and large, spindle-shaped and round cells, also arranged in parallel alignment. Tumor cells with granular cytoplasm, blunt-ended nuclei, intranuclear inclusions, mitotic figures, fibrous or myxoid stroma were not observed. The myxoid tumors disclosed large amounts of background myxoid matrix containing large spindle-shaped and giant cells. Entities such as leiomyoma, malignant peripheral nerve sheath tumor, monophasic synovial sarcoma, and malignant fibrous histiocytoma should be considered in the differential diagnosis of LMS of the classical type. Epithelioid leiomyoma may share similar cytological features with epithelioid LMS. The cytological features of the myxoid variant of LMS can be easily confused with other types of benign and malignant mesenchymal tumors depicting degenerative myxoid changes and/or a myxoid matrix component.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".