Clinical dose profile of Gamma Knife stereotactic radiosurgery for extensive brain metastases
Bibliographic record
Abstract
OBJECTIVE: The use of Gamma Knife stereotactic radiosurgery (GKSRS) for the treatment of extensive intracranial metastases has been expanding due to its superior dosimetry and efficacy. However, there remains a dearth of data regarding the dose parameters in actual clinical scenarios. The authors endeavored to calculate the radiation dose to the brain when treating ≥ 15 brain metastases with GKSRS. METHODS: This retrospective analysis reviewed dosage characteristics for patients requiring single-session GKSRS for the treatment of ≥ 15 brain metastases. Forty-two patients met the inclusion criteria between 2008 and 2017. The median number of tumors at the initial GKSRS procedure was 20 (range 15-39 tumors), accounting for 865 tumors in this study. The median aggregate tumor volume was 3.1 cm3 (range 0.13-13.26 cm3), and the median marginal dose was 16 Gy (range 14-19 Gy). RESULTS: The median of the mean brain dose was 2.58 Gy (range 0.95-3.67 Gy), and 79% of patients had a dose < 3 Gy. The 12-Gy dose volume was a median of 12.45 cm3, which was equivalent to 0.9% of the brain volume. The median percentages of brain receiving 5 Gy and 3 Gy were 6.7% and 20.4%, respectively. There was no correlation between the number of metastases and the mean dose to the brain (p = 0.8). A greater tumor volume was significantly associated with an increased mean brain dose (p < 0.001). The median of the mean dose to the bilateral hippocampi was 2.3 Gy. Sixteen patients had supplementary GKSRS, resulting in an additional mean dose of 1.4 Gy (range 0.2-3.8 Gy) to the brain. CONCLUSIONS: GKSRS is a viable means of managing extensive brain metastases. This procedure provides a relatively low dose of radiation to the brain, especially when compared with traditional whole-brain radiation protocols.
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".