Hippocampus avoidance with fan beam and volumetric arc radiotherapy for base of skull tumours
Bibliographic record
Abstract
Abstract Radiosensitive neurogenic stem cells reside in the hippocampi, suggesting that avoidance of the hippocampi may be an important strategy to reduce potential radiation-related cognitive effects. Six patients treated for base of skull tumours were re-planned using co-planar helical fan beam arc therapy (tomotherapy) and co-planar and non-coplanar volumetric arc techniques (RapidArc). The hippocampi were contoured as avoidance structures with the specific goal of minimising the dose. Two gross target volume (GTV) to planning target volume (PTV) expansions (10 and 2 mm) were considered to evaluate the impact of margin selection on organ at risk (OAR) sparing. The dose prescription was 50 Gy to >95% of the PTV. Comparison of the hippocampus avoidance plans demonstrated the importance of non-coplanar delivery when the 10 mm margin was used. With the 2 mm margin, both co-planar and non-coplanar delivery provided similar degrees of sparing. A mean dose of 3–4 Gy and a V6Gy <5% to the hippocampi was realised with the hippocampus sparing techniques. Our comparisons suggest interventions to minimise GTV to PTV margins will have a more profound influence on multiple OAR sparing than the choice of intensity modulated arc delivery technique.
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 | 0.000 | 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) | 0.002 | 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".