MO‐D‐224A‐06: Fast Monte Carlo‐Based Computation of ASi‐EPID Dose Images for IMRT Treatment Field Through Phantom
Bibliographic record
Abstract
Purpose: During‐treatment IMRT dosimetric verification can be accomplished with exit dose portal dosimetry; however, differential beam hardening and patient scatter radiation results in inaccuracies in invariant kernel‐based calculation methods. The purpose of this study is to develop an accurate, yet efficient Monte‐Carlo (MC) based algorithm to predict during treatment dosimetric aSi‐EPID images to compare with measured images for plan delivery quality assurance. Method and Materials: To compute EPID images, the VMC++ MC algorithm is used to transport particles through the patient geometry. Particles exiting the patient are scored into 19 energy‐differential fluence‐matrices at the EPID surface. Computed EPID images are generated by summing the contributions of each fluence‐matrix convolved with MC generated mono‐energetic energy deposition kernels. Kernel‐based method validation was performed for open, MLC‐blocked, intensity test‐pattern and a prostate‐IMRT field with and without a 20 cm thick phantom by comparing with full MC computation of EPID images. Additionally, the prostate‐IMRT plan was computed through a pelvic phantom. A cone‐beam CT of the pelvic phantom was used for dose computation particle transport. Comparison metrics include image profiles and gamma‐metric evaluation. Results: For the test fields, kernel‐based methods had >95% of voxels with γ<1 for 1 %, 1mm criteria and >99.1% with a 2%, 2mm criteria with respect to the MC‐calculated fields. For the pelvic phantom, 92.6% of pixels had γ<1 for 1%, 1mm criteria. The systematic discrepancy(∼0.5%) is well below the statistical uncertainty(∼3%). Conclusion: The kernel‐based convolution method is comparable in accuracy with full MC while requiring substantially less computation time than a full MC EPID simulation. Image computation time is independent of MC statistical precision and adds <1min to the MC simulation time. Comparison of measured images with MC‐computed portal images may be a practical method to perform during‐treatment dose validation. Conflict of Interest: Supported in‐part by Varian Medical Systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".