Gantry-angle resolved VMAT pretreatment verification using EPID image prediction
Bibliographic record
Abstract
PURPOSE: Pretreatment verification of volumetric modulated arc therapy (VMAT) dose delivery with electronic portal imaging device (EPID) uses images integrated over the entire delivery or over large subarcs. This work aims to develop a new method for gantry-angle-resolved verification of VMAT dose delivery using EPID. METHODS: An EPID dose prediction model was used to calculate EPID images as a function of gantry angle for eight prostate patient deliveries. EPID image frames at 7.5 frames per second were acquired during delivery via a frame-grabber system. The gantry angle for each image was encoded in kV frames which were synchronized to the MV frames. Gamma analysis results as a function of gantry angle were assessed by integrating the frames over 2° subarcs with an angle-to-agreement tolerance of 0.5° about the measured image angle. RESULTS: The model agreed with EPID images integrated over the entire delivery with average Gamma pass-rates at 2%, 2 mm of 99.7% (10% threshold). The accuracy of the kV derived gantry angle for each image was found to be 0.1° (1 SD) using a phantom test. For the gantry-resolved analysis all Gamma pass-rates were greater than 90% at 3%, 3 mm criteria (with only two exceptions), and more than 90% had a 95% pass-rate, with an average of 97.3%. The measured gantry angle lagged behind the predicted angle by a mean of 0.3°±0.3°, with a maximum lag of 1.3°. CONCLUSIONS: The method provides a comprehensive and highly efficient pretreatment verification of VMAT delivery using EPID. Dose delivery accuracy is assessed as a function of gantry angle to ensure accurate treatment.
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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) | 0.001 | 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 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".