Radiosurgery for pediatric central nervous system lesions – initial report and insights from a multicenter registry
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Brain tumors are the most common solid neoplasms in pediatric patients. However, treatment options remain limited in cases of local recurrence, metastasis, or inoperability. Stereotactic radiosurgery (SRS) offers a potential treatment option in these scenarios. This multicenter study reviews the indications and outcomes of SRS in treating pediatric central nervous system (CNS) lesions. MATERIALS AND METHODS: Pediatric patients, <18 years of age at the time of treatment, who underwent SRS for a CNS lesion at four institutions were retrospectively and prospectively analyzed. RESULTS: A total of 84 pediatric patients were treated for 164 benign or malignant CNS lesions between 2005 and 2023. The most common lesions were arteriovenous malformations (28.6%), schwannoma (26.2%), ependymoma (14.3%), and astrocytoma (10.7%). The primary indications for SRS were the need for salvage treatment (79.3%) and palliative care (42.7%). Most treatments (90.9%) were performed with single-fraction SRS. The median follow-up time was 30.4 months. In patients treated for AVM, the median times to at least partial obliteration and to complete obliteration were 12.0 months and 38.4 months, respectively. The median local control rates for ependymoma and astrocytoma were 35.5 months and 23.9 months, respectively, while the median local control rates for schwannoma and metastases were not reached. The rate of high-grade treatment-associated toxicity was low (3.6%). CONCLUSION: SRS in pediatric patients demonstrated a safety and efficacy profile comparable to that of adult patients. SRS should be considered when conventional treatment options are limited and further evaluated as a treatment option for pediatric patients.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".