Dosimetric variations in calculation grid size in prostate VMAT: a dose-volume histogram analysis using the Gaussian error function
Bibliographic record
Abstract
Abstract Background Varying the calculation grid size can change the results of dose-volume and radiobiological parameters in a treatment plan, and therefore has an impact on the treatment planning quality assurance. Purpose This study investigated the dosimetric influence of the calculation grid size variation in the prostate volumetric modulated arc therapy (VMAT) plan. Methods and materials Dose distributions of 10 prostate VMAT plans were acquired using calculation grid sizes of 1–5 mm. Dose-volume histogram (DVH) analysis was carried out to determine the dose-volume variation corresponding to the grid size change using the Gaussian error function (GEF). At the same time, dose-volume points, dose-volume parameters and radiobiological parameters were calculated based on DVHs of targets and organs at risk (OARs) for each grid size. Results Comparing percentage variations of GEF parameters between the planning target volume (PTV) and clinical target volume (CTV), GEF parameters of the PTV were found varied more significantly than the CTV. This resulted in larger variations of dose-volume (%ΔCI=40·02 versus 13·55%, %ΔHI=12·45 versus 2·93% and %ΔGI=0·22 versus 0·06%) and radiobiological parameters (%ΔTCP=0·61 versus 0·25% and %ΔEUD=2·11 versus 0·26%) of the PTV compared with CTV. For OARs, the rectal wall showed a larger dose-volume variation than the rectum. However, similar dose-volume variation due to grid size change was not found in the bladder, bladder wall and femur. Conclusions Knowing the dosimetric variation in this study is important to the radiotherapy staff in the quality assurance for the prostate VMAT planning.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".