Gamma Knife Radiosurgery of Cavernous Sinus Meningiomas: An Institutional Review
Bibliographic record
Abstract
INTRODUCTION: Stereotactic radiosurgery offers a unique and effective means of controlling cavernous sinus meningiomas with a low rate of complications. METHODS: We retrospectively reviewed all cavernous sinus meningiomas treated with Gamma Knife (GK) radiosurgery between November 2003 and April 2011 at our institution. RESULTS: Thirty patients were treated, four were lost to follow- up. Presenting symptoms included: headache (9), trigeminal nerve dysesthesias/paresthesias (13), abducens nerve palsy (11), oculomotor nerve palsy (8), Horner's syndrome (2), blurred vision (9), and relative afferent pupillary defect (1). One patient was asymptomatic with documented tumor growth. Treatment planning consisted of MRI and CT in 17 of 30 patients (56.7%), the remainder were planned with MRI alone (44.3%). There were 8 males (26.7%) and 22 females (73.3%). Twelve patients had previous surgical debulking prior to radiosurgery. Average diameter and volume at time of radiosurgery was 3.4 cm and 7.9 cm3 respectively. Average dose at the 50% isodose line was 13.5 Gy. Follow-up was available in 26 patients. Average follow-up was 36.1 months. Mean age 55.1 years. Tumor size post GK decreased in 9 patients (34.6%), remained stable in 15 patients (57.7%), and continued to grow in 2 (7.7%). Minor transient complications occurred in 12 patients, all resolving. Serious permanent complications occurred in 5 patients: new onset trigeminal neuropathic pain (2), frame related occipital neuralgia (1), worsening of pre-GK seizures (1), and panhypopituitarism (1). CONCLUSION: GK offers an effective treatment method for halting meningioma progression in the cavernous sinus, with an acceptable permanent complication rate.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".