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Record W3209325225 · doi:10.1088/1361-6560/ac3344

Monte Carlo calculation of detector perturbation and quality correction factors in a 1.5 T magnetic resonance guided radiation therapy small photon beams

2021· article· en· W3209325225 on OpenAlexafffund
Yunuen Cervantes, Jasmine Duchaine, Ilias Billas, S Duane, Hugo Bouchard

Bibliographic record

VenuePhysics in Medicine and Biology · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsAlgorithmNuclear magnetic resonanceComputer science

Abstract

fetched live from OpenAlex

Abstract Objective. With future advances in magnetic resonance imaging-guided radiation therapy, small photon beams are expected to be included regularly in clinical treatments. This study provides physical insights on detector dose-response to multiple megavoltage photon beam sizes coupled to magnetic fields and determines optimal orientations for measurements. Approach. Monte Carlo simulations determine small-cavity detector (solid-state: PTW60012 and PTW60019, ionization chambers: PTW31010, PTW31021, and PTW31022) dose-responses in water to an Elekta Unity 7 MV FFF photon beam. Investigations are performed for field widths between 0.25 and 10 cm in four detector axis orientations with respect to the 1.5 T magnetic field and the photon beam. The magnetic field effect on the overall perturbation factor (P MC) accounting for the extracameral components, atomic composition, and density is quantified in each orientation. The density (P ρ ) and volume averaging (P vol) perturbation factors and quality correction factors ( k Q B , Q f B , f ) accounting for the magnetic field are also calculated in each orientation. Main results. Results show that P vol remains the most significant perturbation both with and without magnetic fields. In most cases, the magnetic field effect on P vol is 1% or less. The magnetic field effect on P ρ is more significant on ionization chambers than on solid-state detectors. This effect increases up to 1.564 ± 0.001 with decreasing field size for chambers. On the contrary, the magnetic field effect on the extracameral perturbation factor is higher on solid-state detectors than on ionization chambers. For chambers, the magnetic field effect on P MC is only significant for field widths <1 cm, while, for solid-state detectors, this effect exhibits different trends with orientation, indicating that the beam incident angle and geometry play a crucial role. Significance. Solid-state detectors’ dose-response is strongly affected by the magnetic field in all orientations. The magnetic field impact on ionization chamber response increases with decreasing field size. In general, ionization chambers yield k Q B , Q f B , f closer to unity, especially in orientations where the chamber axis is parallel to the magnetic field.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.108
GPT teacher head0.373
Teacher spread0.265 · 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

Citations22
Published2021
Admission routes2
Has abstractyes

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