Stereotactic radiosurgery optimization with hippocampal-sparing in patients treated for brain metastases
Bibliographic record
Abstract
Background and purposeCranial irradiation is associated with significant neurocognitive sequelae, secondary to radiation-induced damage to hippocampal cells. It has been shown that hippocampal-sparing (HS) leads to modest benefit in neurocognitive function in patients with brain metastases, but further improvement is possible. We hypothesized that improved benefits could be seen using HS in patients treated with stereotactic radiation (HS-SRS). Our study evaluated whether the hippocampal dose could be significantly reduced in the treatment of brain metastases using SRS, while maintaining target coverage.Materials and methodsSixty SRS plans were re-planned to minimize dose to the hippocampus while maintaining target coverage. Patients with metastases within 5 mm of the hippocampus were excluded. Minimum, mean, maximum and dose to 40% (mean equivalent dose in 2 Gy per fraction, EQD2 to the hippocampus) were compared between SRS and HS-SRS plans. Median number of brain metastases was two.ResultsCompared to baseline SRS plans, hippocampal-sparing plans demonstrated Dmin was reduced by 35%, from 0.4 Gy to 0.3 Gy (p-value 0.02). Similarly, Dmax was reduced by 55%, from 8.2 Gy to 3.6 Gy, Dmean by 52%, from 1.6 Gy to 0.5 Gy, and D40 by 50%, from 1.8 Gy to 0.9 Gy (p-values <0.001).ConclusionsOur study demonstrated that further reduction of hippocampal doses of more than 50% is possible in the treatment of brain metastases with SRS using dose optimization. This could result in significantly improved neurocognitive outcomes for patients treated for brain metastases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".