Experimental verification of <scp>EGS</scp>nrc Monte Carlo calculated depth doses within a realistic parallel magnetic field in a polystyrene phantom
Bibliographic record
Abstract
Purpose Integrating a linac with a magnetic resonance imager (MRI) will revolutionize the accuracy of external beam radiation treatments. Irradiating in the presence of a strong magnetic field, however, will modify the dose distribution. These dose modifications have been investigated previously, mainly using Monte Carlo simulations. The purpose of this work is to experimentally verify the use of the EGSnrc Monte Carlo (MC) package for calculating percent depth doses (PDDs) in a homogeneous phantom, in the presence of a realistic parallel magnetic field. Methods Two cylindrical electromagnets were used to produce a 0.207 T magnetic field parallel to the central axis of a 6 MV photon beam from a clinical linac. The magnetic field was measured at discrete points along orthogonal axes, and these measurements were used to validate a full 3D magnetic field map generated using COMSOL Multiphysics. Using a small parallel plate ion chamber, the depth dose was measured in a polystyrene phantom placed inside the electromagnet bore at two separate locations: phantom top surface coinciding with top of bore, and phantom top surface coinciding with center of bore. BEAMnrc MC was used to model the linac head which was benchmarked against the linac's commissioning measurements. The depth dose in polystyrene was simulated using DOSXYZnrc MC. For the magnetic field case, the DOSXYZnrc code was slightly modified to implement the previously calculated 3D magnetic field map to be used in the standard electromagnetic macros. Results The calculated magnetic field matched the measurements within 2% of the maximum central field (0.207 T) with most points within the experimental uncertainty (1.5%). For the MC linac head model, over 93% of all simulated points passed the 2%, 2 mm γ acceptance criterion, when comparing measured and simulated lateral beam and depth dose profiles. The parallel magnetic field caused a surface dose increase, compared to the no magnetic field case, due to the Lorentz force confining contaminant electrons within the beam. The surface dose increase was measured to be approximately 10% (relative to no field Dmax) when the phantom surface coincided with the top of the electromagnet's bore. This effect was enhanced by moving the phantom surface to the center of the magnet's bore in relatively high magnetic field (> 0.13 T). The surface dose for this setup increased by 30% and the entire buildup region was affected. When the dimensions and composition of the ion chamber air cavity and entrance window were included, EGSnrc was able to accurately simulate these dose increases, both at the surface and in the buildup region. All the simulated points were within 1% of the measurements for both setups. The ferromagnetic linac head was determined to have a negligible effect on the final PDD comparison. Conclusions Irradiating in the presence of a parallel magnetic field causes measurable surface and buildup depth dose increases. We have experimentally verified that the EGSnrc Monte Carlo package is able to accurately calculate the PDDs with these surface and buildup dose modifications in a homogeneous phantom.
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 | 0.003 |
| 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) | 0.003 | 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".