SU‐C‐BRA‐03: Investigation of the Performance of a Simulated In‐Line 6 MV Linac in Longitudinal Magnetic Fields
Bibliographic record
Abstract
Purpose: To achieve real‐time image guided radiotherapy, a linac‐MR system is designed with the linac located on the symmetry axis of the MRI. Thus, an investigation was performed in order to determine the performance of an in‐line 6 MV linac in longitudinal magnetic fields. Method and Materials: Magnetic fringe fields from the PARAmed openMR™ were modeled and included in the simulation of an in‐line 6 MV linac. The electron gun simulation was modeled in OPERA‐3d/SCALA. The linac waveguide emulating the Varian 600C was modeled in COMSOL and the resulting dosimetry from the linac model was calculated using BEAMnrcMP 2007 and DOSXYZnrc. Results: With the linac on the symmetry axis of the openMR™ imager, the electron gun is expected to experience longitudinal magnetic fields ranging from 0.0022 to 0.011 T. At these field strengths, the rms emittance of the electron beam injected into the waveguide grew from 0.358 pi‐mm‐mrad at 0T to 3.255 pi‐mm‐mrad at 0.011 T. The increased emittance resulted from an increased beam diameter and an increasingly diverging beam. Upon injection, the larger emittance caused greater beam loss within the waveguide and a two orders of magnitude increase in the full‐width‐half‐maximum of the focal spot at the target. Despite the changes in the focal spot, the mean energy was altered by less than 0.5% and the calculated depth dose and profile distributions were identical to distributions at 0T. Magnetic fields up to 0.2T were also added to the linac simulation representing fringe fields from other MRIs. Both the injection current and target current reached a minimum at 0.06T, but increased slightly at higher field strengths due to increasing collimation in the electron gun anode. Conclusion: The effect of longitudinal magnetic fields on a simulated in‐ line 6 MV linac has been quantified enabling future development of a parallel linac‐MR system.
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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 | 0.000 | 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".