Adverse radiation effects in volume-staged radiosurgery for large arteriovenous malformations: a multiinstitutional study
Bibliographic record
Abstract
OBJECTIVE: The optimal treatment paradigm for large arteriovenous malformations (AVMs) is controversial. One approach is volume-staged stereotactic radiosurgery (VS-SRS). The authors previously reported efficacy of VS-SRS for large AVMs in a multiinstitutional cohort; here they focus on risk of symptomatic adverse radiation effects (AREs). METHODS: This is a multicentered retrospective review of patients treated with a planned prospective volume staging approach to stereotactically treat the entire nidus of an AVM, with volume stages separated by intervals of 3-6 months. A total of 9 radiosurgical centers treated 257 patients with VS-SRS between 1991 and 2016. The authors evaluated permanent, transient, and total ARE events that were symptomatic. RESULTS: Patients received 2-4 total volume stages. The median age was 33 years at the time of the first SRS volume stage, and the median follow-up was 5.7 years after VS-SRS. The median total AVM nidus volume was 23.25 cm3 (range 7.7-94.4 cm3), with a median margin dose per stage of 17 Gy (range 12-20 Gy). A total of 64 patients (25%) experienced an ARE, of which 19 were permanent. Rather than volume, maximal linear dimension in the Z (craniocaudal) dimension was associated with toxicity; a threshold length of 3.28 cm was associated with an ARE, with a 72.5% sensitivity and a 58.3% specificity. In addition, parietal lobe involvement for superficial lesions and temporal lobe involvement for deep lesions were associated with an ARE. CONCLUSIONS: Size remains the dominant predictor of toxicity following SRS, but overall rates of AREs were lower than anticipated based on baseline features, suggesting that dose and size were relatively dissociated through volume staging. Further techniques need to be assessed to optimize outcomes.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".