Cytology of Extraneural Metastases of Nonhematolymphoid Primary Central Nervous System Tumors: Six Cases with Histopathological Correlation and Literature Update
Bibliographic record
Abstract
INTRODUCTION: Extraneural/-cranial metastases (ENM) of primary central nervous system (CNS) tumors are rare and may be diagnostically challenging. We describe the cytomorphological and pertinent clinical features of ENM in a case series assessed by fine-needle aspiration (FNA). A search of the laboratory information systems of 2 tertiary care centers in Toronto (2000-2015) was performed. Cases with direct extracranial/-spinal extension of CNS neoplasms were excluded. Microscopic slides of FNA and surgical specimens were reviewed. Demographic and clinicopathological data were retrieved. CASE PRESENTATION: Six cases were identified with the original diagnoses of glioblastoma, glioblastoma with primitive neuroectodermal tumor-like components, anaplastic ependymoma, myxopapillary ependymoma, atypical meningioma, and hemangiopericytoma. Median patient age at first diagnosis was 44 years (range 22-56). The time interval between initial diagnosis and first metastatic disease manifestation was 3 months to 19 years. All FNA diagnoses were rendered correctly. In 4 cases, immunohistochemistry was used to support the diagnosis. All cases had prior surgical intervention at the primary tumor site. In 4 cases, the ENM location was the ipsilateral parotid or buccal area. Two primary tumors in midline location developed ENM in the scapular area. DISCUSSION/CONCLUSION: ENM are a rare manifestation of a range of different primary CNS tumors and may involve the ipsilateral head and neck mimicking clinically a salivary gland neoplasm. FNA can rapidly discriminate ENM from other, potentially more indolent conditions. Awareness of the clinical history is paramount to avoid diagnostic confusion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".