Gamma Knife radiosurgery for facial nerve schwannomas: a multicenter study
Bibliographic record
Abstract
OBJECT: Facial nerve schwannomas (FNSs) are rare intracranial tumors, and the optimal management of these tumors remains unclear. Resection can be undertaken, but the tumor's intimate association with the facial nerve makes resection with neurological preservation quite challenging. Stereotactic radiosurgery (SRS) has been used to treat FNSs, and this study evaluates the outcome of this approach. METHODS: At 8 medical centers participating in the North American Gamma Knife Consortium (NAGKC), 42 patients undergoing SRS for an FNS were identified, and clinical and radiographic data were obtained for these cases. Males outnumbered females at a ratio of 1.2:1, and the patients' median age was 48 years (range 11-76 years). Prior resection was performed in 36% of cases. The mean tumor volume was 1.8 cm(3), and a mean margin dose of 12.5 Gy (range 11-15 Gy) was delivered to the tumor. RESULTS: At a median follow-up of 28 months, tumor control was achieved in 36 (90%) of the 40 patients with reliable radiographic follow-up. Actuarial tumor control was 97%, 97%, 97%, and 90% at 1, 2, 3, and 5 years postradiosurgery. Preoperative facial nerve function was preserved in 38 of 42 patients, with 60% of evaluable patients having House-Brackmann scores of 1 or 2 at last follow-up. Treated patients with a House-Brackmann score of 1 to 3 were more likely to demonstrate this level of facial nerve function at last evaluation (OR 6.09, 95% CI 1.7-22.0, p = 0.006). Avoidance of temporary or permanent neurological symptoms was more likely to be achieved in patients who received a tumor margin dose of 12.5 Gy or less (log-rank test, p = 0.024) delivered to a tumor of ≤ 1 cm(3) in volume (log-rank test, p = 0.01). CONCLUSIONS: Stereotactic radiosurgery resulted in tumor control and neurological preservation in most FNS patients. When the tumor is smaller and the patient exhibits favorable normal facial nerve function, SRS portends a better result. The authors believe that early, upfront SRS may be the treatment of choice for small FNSs, but it is an effective salvage treatment for residual/recurrent tumor that remain or progress after resection.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".