Fine‐needle aspiration in myxofibrosarcoma: Experience of Institut Curie
Bibliographic record
Abstract
Myxofibrosarcoma (MFS) is a well-established nosologic entity different from the myxoid variant of malignant fibrous histiocytoma. In an attempt to better define the representative cytologic criteria of MFS, we undertook a review and a reanalysis of a series of 14 cytology samples in 12 patients whose tumors were diagnosed as MFS.Using FNA technique and reviewing the original diagnoses, 11 cases were diagnosed as malignant and three as benign tumors. The cytologic diagnosis of MFS was accurate in seven cases (2 primary tumors, 4 recurrences, and 1 metastasis). Four cases were classified malignant myxoid sarcoma (1 primary and 3 recurrences), whereas three cases (2 primary and 1 recurrence) were false-negative.The smears were cell-rich in 12 cases and cell-poor in two cases. They were constantly composed of isolated and regular small spindle-shaped and stellated cells with elongated nuclei containing small inconspicuous nucleoli. Cytoplasm was pale with elongated processes. Clusters of wavy spindle-shaped cells, round cells without specific pattern, moderate cytonuclear atypia, and abundant myxoid background as well as curvilinear vascular structures were always seen. In the vast majority of cases, the cytologic distinction of MFS from other low-grade myxoid lesions is difficult. Entities such as myxoid MFH, myxoid liposarcoma (MLP), myxoid DFSP, and myxoma should be considered in the differential diagnosis. The cytological misdiagnosis is of limited clinical consequence because FNA findings suggestive of a myxoid tumor will be indicative for a surgical removal followed by the histopathological analysis.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".