Leptomeningeal dissemination of a low-grade lumbar paraganglioma: case report
Bibliographic record
Abstract
Leptomeningeal dissemination of paraganglioma is rare, with only 2 prior cases in the literature. The authors present the case of a metastatic low-grade lumbar paraganglioma via leptomeningeal dissemination. This report emphasizes the utility of 3,4-dihydroxy-6-18F-fluoro-l-phenylalanine (18F-FDOPA) PET scanning for diagnosis, as well as the combination of radiation therapy and alkylating chemotherapeutic agents for the treatment of this rare phenomenon. The patient was a 61-year-old woman who presented with low-back pain and was found to have an isolated L-3 intrathecal tumor on MRI. Sixteen months after gross-total en bloc resection of the paraganglioma, the patient again became symptomatic with new neurological symptoms. MRI findings revealed enhancing leptomeningeal nodules throughout the spine. 18F-FDOPA PET/CT scanning was used to confirm the diagnosis of disseminated paraganglioma. Intrathecal thiotepa, radiation therapy, and systemic therapy with capecitabine and temozolomide have been used sequentially over a 2-year period, with each able to stabilize tumor growth for several months. The authors also summarize the 2 other reports of leptomeningeal dissemination of paragangliomas in the literature and compare the course and management of the 3 cases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".