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Record W4403895484 · doi:10.1002/mp.17495

Monte Carlo modeling of the origin of contaminant electrons on a 0.5T bi‐planar Linac‐MR

2024· article· en· W4403895484 on OpenAlexaff
Michael Reynolds, Patricia Oliver, T. R. Wood, Eugene Yip, Shima Yaghoobpour Tari, Keith Wachowicz, B Burke, B. G. Fallone

Bibliographic record

VenueMedical Physics · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsUniversity of AlbertaNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsMonte Carlo methodLinear particle acceleratorPlanarElectronPhysicsDosimetryNuclear physicsComputational physicsMedical physicsNuclear medicineOpticsComputer scienceMedicineBeam (structure)Computer graphics (images)MathematicsStatistics

Abstract

fetched live from OpenAlex

INTRODUCTION: In the last decade, hybrid linear accelerator magnetic resonance imaging (Linac-MR) devices have evolved into FDA-cleared clinical tools, facilitating magnetic resonance guided radiotherapy (MRgRT). The addition of a magnetic field to radiation therapy has previously demonstrated dosimetric and electron effects regardless of magnetic field orientation. PURPOSE: This study uses Monte Carlo simulations to investigate the importance and efficacy of the magnetic field design in mitigating surface dose enhancement in the Aurora-RT, focusing specifically on contaminant electrons, their origin, and energy spectrum. METHODS: The Aurora-RT 0.5 T Biplanar Linac-MR device was modeled using the BEAMnrc package using the updated EM macros, a magnetic field map generated from Opera 3D. Simulation generated phasespace data at the distal side of the first magnetic pole plate (89 cm) and at machine isocenter (120 cm) were analyzed with respect to electron energy spectra and electron creation origins, both with and without the static magnetic field. RESULTS: The presence of the main magnetic field was verified to affect the origin and distribution of contaminant electrons, removing them from the air column up to 60 cm from the target, and focusing them along the CAX within the region below. Analysis of the remaining electron energy fluence reveals the net removal of electrons with energies > 2 MeV and generation of electrons with energies < 2 MeV in the presence of the static magnetic field as compared to no magnetic field. Moreover, in the presence of the magnetic field the integral energy contained in the contaminant electrons increases from 89 cm to isocenter but is still 15% less overall than the integral energy contained in contaminant electrons without the magnetic field. CONCLUSION: This study provides an analysis of contaminant electrons in the Aurora-RT 0.5 T Linac-MR, emphasizing the role of magnetic field design in successfully minimizing electron contaminants.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.019
GPT teacher head0.293
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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