Skin dose investigations on a 0.5 T parallel rotating biplanar linac‐MR using Monte Carlo simulations and measurements
Bibliographic record
Abstract
Abstract Background The Alberta rotating biplanar linac‐MR has a 0.5 T magnetic field parallel to the beamline. When developing a new linac‐MR system, interactions of charged particles with the magnetic field necessitate careful consideration of skin dose and tissue interface effects. Purpose To investigate the effect of the magnetic field on skin dose using measurements and Monte Carlo (MC) simulations. Methods We develop an MC model of our linac‐MR, which we validate by comparison with ion chamber measurements in a water tank. Additionally, MC simulation results are compared with radiochromic film surface dose measurements on solid water. Variations in surface dose as a function of field size are measured using a parallel plate ion chamber in solid water. Using an anthropomorphic computational phantom with a 2 mm‐thick skin layer, we investigate dose distributions resulting from three beam arrangements. Magnetic field on and off scenarios are considered for all measurements and simulations. Results For a 20 × 20 cm2 field size, (the minimum dose to the hottest contiguous 0.2 cc volume) for the top 2 mm of a simple water phantom is 72% when the magnetic field is on, compared to 34% with magnetic field off (values are normalized to the central axis dose maximum). Parallel plate ion chamber measurements demonstrate that the relative increase in surface dose due to the magnetic field decreases with increasing field size. For the anthropomorphic phantom, (minimum skin dose in the hottest 1 × 1 × 1 cm3 cube) shows relative increases of 20%–28% when the magnetic field is on compared to when it is off. With magnetic field off, skin is 71%, 56%, and 21% for medial‐lateral tangents, anterior‐posterior beams, and a five‐field arrangement, respectively. For magnetic field on, the corresponding skin values are 91%, 67%, and 25%. Conclusions Using a validated MC model of our linac‐MR, surface doses are calculated in various scenarios. MC‐calculated skin dose varies depending on field sizes, obliquity, and the number of beams. In general, the parallel linac‐MR arrangement results in skin dose enhancement due to charged particles spiraling along magnetic field lines, which impedes lateral motion away from the central axis. Nonetheless, considering the results presented herein, treatment plans can be designed to minimize skin dose by, for example, avoiding oblique beams and using a larger number of fields.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".