Electron beam treatment verification using measured and Monte Carlo predicted portal images
Bibliographic record
Abstract
Electron beam treatments may benefit from techniques to verify patient positioning and dose delivery. This is particularly so for complex techniques such as mixed photon and electron beam radiotherapy and electron beam modulated therapy. This study demonstrates that it is possible to use the bremsstrahlung photons in an electron beam from a dual scattering foil linear accelerator to obtain portal images of electron beam treatments. The possibility of using Monte Carlo (MC) simulations to predict the electron beam treatment portal images was explored. The MC code EGSnrc was used to model a Varian CL21EX linear accelerator (linac) and to characterize the bremsstrahlung photon production in the linac head. It was found that the main sources of photons in the electron beam are the scattering foils, the applicator and the beam-shaping cut-out. Images were acquired using the Varian CL21EX linac and the Varian aS500 electronic portal imager (EPI); four electron energies (6, 9, 12, 16 MeV), and different applicator and cut-out sizes were used. It was possible to acquire images with as little as 10.7 MU per image. The contrast, the contrast-to-noise ratio (CNR), the signal-to-noise ratio (SNR), the resolution and an estimate of the modulated transfer function (MTF) of the electron beam portal images were computed using a quality assurance (QA) phantom and were found to be comparable to those of a 6 MV photon beam. Images were also acquired using a Rando anthropomorphic phantom. MC simulations were used to model the aS500 EPID and to obtain predicted portal images of the QA and Rando phantom. The contrast in simulated and measured portal images agrees within +/-5% for both the QA and the Rando phantom. The measured and simulated images allow for a verification of the phantom positioning by making sure that the structure edges are well aligned. This study suggests that the Varian aS500 portal imager can be used to obtain patient portal images of electron beams in the scattering foil linacs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".