33 Is hypofractionation safer than single-fraction radio surgery? The effect of fractionation on radionecrosis
Bibliographic record
Abstract
Introduction: Radiation-induced brain necrosis (RN) is a relatively uncommon (5-20%) but potentially severe adverse effect of stereotactic radiosurgery (SRS) for brain metastasis(BM). We attempted to establish the effect of hypo-fractionation on RN rates by reviewing patients having simultaneous multi-fraction and single fraction treatment of BM at our centre. Methods: Patients receiving simultaneous 1 (20-24Gy) or 3 fraction (21-24Gy) SRS treatments were identified in our institution’s database. Serial post-SRS MRIs were reviewed to determine the lesion quotient (LQ), or maximum cross sectional area on T1 plus gadolinium divided by T2 FLAIR sequences. LQ less than 0.3 was considered RN. Result: Twenty-two patients were followed for a median 320 days. Sixteen patients developed radionecrosis in 21 of 62 lesions (33%), four of which were symptomatic (20%). Eleven of these lesions received 3 fractions and ten received one fraction. RN risk increased with increasing tumor volume (log odds ratio=1.12, p=0.04). There was no difference in incidence of RN in patients who received whole brain radiotherapy (WBRT) (p=0.11), hypo-fractionation (p=0.98) or had a higher maximum dose (p=0.71). Radiographic RN, however, did not clear in any patients who developed it. Eight patients developed a local recurrence (12%), six of which occurred in the single fraction group. Conclusion: Radionecrosis was significantly related to tumor volume but not fractionation, WBRT, or maximum dose. Overall, our results indicate patients receiving SRS for multiple brain metastasis have a higher rate of radionecrosis than the literature and poorer survival despite having equivalent local control.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".