SU-E-T-604: Dosimetric Dependence On the Collimator Angle in Prostate Volumetric Modulated Arc Therapy
Bibliographic record
Abstract
Purpose: The purpose of this study is to investigate the dose-volume variations of planning target volume (PTV) and organs-at-risk (OARs) in prostate volumetric modulated arc therapy (VMAT) when using different collimator angles. It is because collimator angle awareness is essential for planner to produce an optimal prostate VMAT plan in a rational time. Methods: Single-arc VMAT plans at different collimator angles (0o, 15o, 30o, 45o, 60o, 75o and 90o) were created systematically using a Harold heterogeneous pelvis phantom. For each change of collimator angle, a new plan was re-optimized for that angle. The prescription dose was 78 Gy per 39 fractions. Conformity index (CI), homogeneity index (HI), gradient index, machine monitor unit, dose-volume histogram, the mean and maximum doses of the PTV were calculated and analyzed. On the other hand, dose-volume histogram, the mean and maximum doses of the OARs such as bladder, rectum and femoral heads for different collimator angles were determined from the plans. Results: There was no significance difference, based on the plan dose-volume evaluation criteria, found in the VMAT optimizations for all studied collimator angles. Higher CI and lower HI were found for the 45o collimator angle. In addition, the 15o collimator angle provided lower HI similar to the 45o collimator angle. The 75o and 90o collimator angle were found good for the rectum sparing, and the 75o and 30o collimator angle were found good for the right and left femur sparing, respectively. The PTV dose coverage for each plan was comparatively independent of the collimator angle. Conclusion: The dosimetric results in this study are useful to the planner to select different collimator angles to improve the PTV coverage and OAR sparing in prostate VMAT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".