Radiosurgical Retreatment for Brain Arteriovenous Malformation
Bibliographic record
Abstract
OBJECTIVE: To analyze our experience with a second radiosurgical treatment for brain arteriovenous malformations (BAVMs) after an unsuccessful first radiosurgical treatment. METHODS: Between 1993 and 2000, 242 patients were treated by the Toronto Sunnybrook Regional Cancer Center using a LINAC system. Fifteen of these patients required a second radiosurgical intervention due to the failure of the first procedure. Data was collected on baseline patient characteristics, BAVM features, radiosurgery treatment plan and outcomes. Brain arteriovenous malformation obliteration was determined by follow-up MRI and angiography and the obliteration prediction index (OPI) calculated according to a previously established formula. RESULTS: The median interval between the first and second treatment was 46 months (range 39-109). The median follow-up after the second procedure was 39 months (range 26 to 72). The mean BAVM volume before the first treatment was 8.9cm3 (range 0.3-21) and before the second treatment was 3.6cm3 (range 0.2-11.6). The mean marginal dose during the first treatment was 18Gy (range 12-25) and during the second treatment was 16Gy (range 12-20). After the second treatment, nine patients had obliteration of their BAVM confirmed by angiography and one patient had obliteration confirmed by MRI, resulting in an obliteration rate of 66.6%, which is very comparable to that predicted by the OPI (65%). After the second treatment two patients had a radiation-induced complication (13.3%). CONCLUSION: Retreatment of BAVM using a second radiosurgery procedure is a safe and effective option that offers the same rate of success as the initial radiosurgery and an acceptable risk of radiation-induced complication.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".