Systematic review of the incidence and risk factors for cerebral vasculopathy and stroke after cranial proton and photon radiation for childhood brain tumors
Bibliographic record
Abstract
BACKGROUND: The aim of our study is to determine the incidence, timing, and risk factors for cerebral vasculopathy after cranial proton and photon radiation for pediatric brain tumors. METHODS: We performed a single-institution retrospective review of a cohort of children treated with proton radiation for brain tumors. MRA and/or MRI were reviewed for evidence of cerebral vascular stenosis and infarcts. Twenty-one similar studies (17 photon, 4 proton) were identified by systematic literature review. RESULTS: For 81 patients with median follow-up of 3 years, the rates of overall and severe vasculopathy were 9.9% and 6.2% respectively, occurring a median of 2 years post radiation. Dose to optic chiasm greater than 45 Gy and suprasellar location were significant risk factors. Results were consistent with 4 prior proton studies (752 patients) that reported incidence of 5% to 6.7%, 1.5 to 3 years post radiation. With significantly longer follow-up (3.7-19 years), 9 studies (1108 patients) with traditional photon radiation reported a higher rate (6.3%-20%) and longer time to vasculopathy (2-28 years). Significant risk factors were neurofibromatosis type 1 (NF-1; rate 7.6%-60%) and suprasellar tumors (9%-20%). In 10 studies with photon radiation (1708 patients), the stroke rate was 2% to 18.8% (2.3-24 years post radiation). CONCLUSIONS: Childhood brain tumor survivors need screening for vasculopathy after cranial radiation, especially with higher dose to optic chiasm, NF-1, and suprasellar tumors. Prospective studies are needed to identify risk groups, and ideal modality and timing, for screening of this toxicity.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".