WE‐C‐108‐04: A Monte Carlo Investigation of Low‐Z Targets in a TrueBeam Linear Accelerator Using Varian Virtualinac
Bibliographic record
Abstract
Purpose: The focus of this work was to investigate the implementation of low‐Z targets in a TrueBeam linear accelerator (linac) using Monte Carlo simulations. Methods: Simulation of a TrueBeam linac was accomplished by using Varian Virtualinac. Virtualinac is a cloud based web application utilizing GEANT4 Monte Carlo code to model TrueBeam components. Phase spaces were recorded above the jaws and used as input to BEAMnrc simulations of the lower portion of TrueBeam. Dose distributions and spectral distributions were calculated using DOSXYZnrc and BEAMdp, respectively. For validation, 6 MV flattened and FFF photon beams were generated and compared to measurement. Two low‐Z targets were investigated: a carbon target operated at 2.35 MeV and the proposed 2.50 MeV commercial imaging target. The carbon target was also simulated in a 2100EX Clinac using BEAMnrc. Contrast simulations were made by scoring the dose in the phosphor layer of an IUD20 detector after propagating through 4 and 20 cm thick water and ICRP bone phantoms. Results: Measured and modeled depth dose curves for 6 MV flattened and FFF beams agree within 2% for 99.7% of points at depths greater than 0.85 cm. The two low‐Z target photon spectra produced in TrueBeam are harder than that from a Clinac. Percent dose at depth 10 cm is greater by 8.6% and 14.2%; the fraction of photons in the diagnostic energy range is lower by 7% and 25%; and contrasts are lower by factors of 1.2 and 1.5 (thin phantom) and 1.06 and 1.4 (thick), for the TrueBeam 2.35 MV/carbon and commercial imaging beams, respectively. Conclusion: Virtualinac is effective for Monte Carlo modeling of novel target designs. A significant spectral difference is observed between the low‐Z target beam on the Clinac platform, and the proposed imaging beam line on TrueBeam, with the former providing greater diagnostic energy content. This research was supported by Varian Medical Systems and was accomplished using Varian's Virtualinac Monte Carlo application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".