Fine‐needle aspiration of renal and extrarenal rhabdoid tumors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Rhabdoid tumors (RT) are rare, renal or extrarenal, high-grade malignancies. The cytologic diagnosis may be confirmed if combined with genomic results. In the current study, the authors present the cytologic and ancillary techniques used to diagnose RT in their series of 20 tumors in 13 patients. METHODS: Clinical charts as well as cytologic, histologic, karyotypic, and molecular biology results were reviewed. RESULTS: Twelve fine-needle aspirations (FNAs) were performed for primary diagnosis, 7 were to confirm a metastasis, and 1 was to confirm local recurrence. Primary tumors were in the kidney in 7 cases and 13 were extrarenal. Patient age ranged from 5 months to 26 years. There were 7 females and 6 males. FNAs were cell-rich in 16 cases and cell-poor in 4 cases and revealed a mix of atypical spindle-shaped, round, rhabdoid, or epithelioid cells, singly or in clusters. Mitosis and necrosis occasionally were present. The original cytologic diagnosis was malignant in all cases. There were no unsatisfactory or false-negative samples. In the 12 primary tumors, the preliminary FNA diagnosis was RT in 7 cases (58%), rhabdomyosarcoma in 4 cases (33%), and malignant peripheral nerve sheath tumor in 1 case (8%). Karyotypes were available in 6 cases, 3 of which demonstrated chromosome 22 changes. Fluorescence in situ hybridization revealed loss of probe signals for the SMARCB1 gene locus in 5 cases; DNA sequence analysis performed in 9 cases revealed deletions in codons of the SMARCB1 gene in 7 cases and a mutation in 2 cases. CONCLUSIONS: The primary diagnosis of RT is possible on FNA. In the current study, 12 of 13 cases were diagnosed by FNA with a combination of clinical information, immunocytochemistry, and molecular analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it