Trajectory‐based VMAT for cranial targets with delivery at shortened SAD
Bibliographic record
Abstract
INTRODUCTION: Trajectory-based volumetric modulated arc therapy (tr-VMAT) treatment plans enable the option for noncoplanar delivery yielding steeper dose gradients and increased sparing of critical structures compared to conventional treatment plans. The addition of translational couch motion to shorten the effective source-to-axis distance (SAD) may result in improved delivery precision and an increased effective dose rate. In this work, tr-VMAT treatment plans using a noncoplanar "baseball stitch" trajectory were implemented, applied to patients presented with cranial targets, and compared to the clinical treatment plans. METHODS: A treatment planning workflow was implemented: (a) beamlet doses were calculated for control points defined along a baseball stitch trajectory using a collapsed-cone convolution-superposition algorithm; (b) VMAT treatment plans were optimized using the column generation approach; (c) a final dose distribution was calculated in Varian Eclipse using the analytical anisotropic algorithm by importing the optimized treatment plan parameters. Tr-VMAT plans were optimized for ten patients presented with cranial targets at both standard and shortened SAD, and compared to the clinical treatment plans through isodose distributions, dose-volume histograms, and dosimetric indices. The control point specifications of the optimized tr-VMAT plans were used to estimate the delivery time. RESULTS: The optimized tr-VMAT plans with both shortened and standard SAD delivery yielded a comparable plan quality to the clinical treatment plans. A statistically significant benefit was observed for dose gradient index and monitor unit efficiency for shortened SAD tr-VMAT plans, while improved target volume conformity was observed for the clinical treatment plan (P ≤ 0.05). A clear dosimetric benefit was not demonstrated between tr-VMAT delivery at shortened SAD compared to standard SAD, but shortened SAD delivery yielded a fraction size-dependent reduction in the estimated delivery time. CONCLUSION: The implementation of "baseball stitch" tr-VMAT treatment plans to patients presented with cranial targets demonstrated comparable plan quality to clinical treatment plans. The delivery at shortened SAD produced a fraction size-dependent decrease in estimated delivery time.
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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 | 0.000 |
| 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) | 0.003 | 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".