Backscatter dose effects for high atomic number materials being irradiated in the presence of a magnetic field: A Monte Carlo study for the MRI linac
Bibliographic record
Abstract
PURPOSE: To quantify and explain the backscatter dose effects for clinically relevant high atomic number materials being irradiated in the presence of a 1.5 T transverse magnetic field. METHODS: Interface effects were investigated using Monte Carlo simulation techniques. We used gpumcd (v5.1) and geant4 (v10.1) for this purpose. gpumcd is a commercial software written for the Elekta AB, MRI linac. Dose was scored using gpumcd in cubic voxels of side 1 and 0.5 mm, in two different virtual phantoms of dimensions 20 × 20 × 20 cm and 5 × 5 × 13.3 cm, respectively. A photon beam was generated from a point 143.5 cm away from the isocenter with energy distribution sampled from a histogram representing the true Elekta, MRI linac photon spectrum. A slab of variable thickness and position containing either bone, aluminum, titanium, stainless steel, or one of the two different dental filling materials was inserted as an inhomogeneity in the 20 × 20 × 20 cm phantom. The 5 × 5 × 13.3 cm phantom was used as a clinical test case in order to explain the dose perturbation effects for a head and neck cancer patient. The back scatter dose factor (BSDF) was defined as the ratio of the doses at a given depth with and without the presence of the inhomogeneity. Backscattered electron fluence was calculated at the inhomogeneity interface using geant4. A 1.5 T magnetic field was applied perpendicular to the direction of the beam in both phantoms, identical to the geometry in the Elekta MRI linac. RESULTS: With the application of a 1.5 T magnetic field, all the BSDF's were reduced by 12%-47%, compared to the no magnetic field case. The corresponding backscattered electron fluence at the interface was also reduced by 45%-64%. The reduction in the BSDF at the interface, due to the application of the magnetic field, is manifested in a different manner for each material. In the case of bone, the dose drops at the interface contrary to the expected increase when no magnetic field is applied. In the case of aluminum, the dose at the interface is the same with and without the presence of the aluminum. For all of the other materials the dose increases at the interface. CONCLUSIONS: The reduction in dose at the interface, in the presence of the magnetic field, is directly related to the reduction in backscattered electron fluence. This reduction occurs due to two different reasons. First, the electron spectrum hitting the interface is changed when the magnetic field is turned on, which results in changes in the electron scattering probability. Second, some electrons that have curved trajectories due to the presence of the magnetic field are absorbed by the higher density side of the interface and no longer contribute to the backscattered electron fluence.
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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 | 0.001 |
| 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".