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Record W2771556745 · doi:10.1002/mp.12716

Monte Carlo study of ionization chamber magnetic field correction factors as a function of angle and beam quality

2017· article· en· W2771556745 on OpenAlexaff
Victor Malkov, D. W. O. Rogers

Bibliographic record

VenueMedical Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsIonization chamberMonte Carlo methodLaser beam qualityPhysicsQuality (philosophy)DosimetryMagnetic fieldComputational physicsBeam (structure)IonizationOpticsNuclear physicsMedical physicsNuclear medicineMedicineIonLaser beamsMathematicsStatistics

Abstract

fetched live from OpenAlex

Purpose To use EGSnrc Monte Carlo simulations for magnetic field dosimetry to determine optimal measurement orientations, calculate beam quality conversion factors for 32 cylindrical and three parallel‐plate (PP) ion chambers, evaluate the beam quality and angular dependence of these factors, and examine the magnetic field effects on %dd(10) x and TPR . Methods Beam quality conversion factors, k , and magnetic field conversion factors, k B = k /k Q , are calculated as a function of chamber rotation for six cylindrical ionization chamber in either a 60 Co beam with a 0.35 T magnetic field or a 7 MV beam with a 1.5 T field, both magnetic fields are perpendicular to the photon beam. The chambers’ sensitive air volumes are varied by either using the entire geometric volume or excluding the air volume associated with the first 1 mm away from the stem. The k B and k factors are evaluated using four clinical photon spectra. The variation in %dd(10) x and TPR as a function of magnetic field for six photon spectra are studied using DOSXYZnrc. Results When the magnetic field is perpendicular to the photon beam, orienting the chamber parallel with the magnetic field reduces the magnetic field effect on chamber response (i.e., dose to air per water dose) and variations due to the unknown sensitive volume are essentially eliminated. Calculated k B factors are within 1% of unity for the majority of cylindrical chambers, although larger k B values are associated with chambers with high‐Z electrodes. PP chambers have k B corrections as large as 8.9% and have a larger angular sensitivity compared to cylindrical chambers. Values of k B for cylindrical ion chambers are independent of beam quality, except for chambers with high‐Z electrodes. For %dd(10) x values between 63.3% and 73.8%, k B varies by at most (0.26 ± 0.15)% when the magnetic field is perpendicular to the photon beam and parallel to the chamber. Differences in %dd(10) x , between no magnetic field and with a 1.5 T field perpendicular to the photon beam are (0.04 ± 0.10)%, (1.89 ± 0.10)%, and (6.20 ± 0.10)% for a 60 Co, 7, and 25 MV photon beam, respectively, while TPR shows less than (0.36 ± 0.10)% change. Applying the ICRU‐90 recommendations for stopping powers instead of ICRU‐37 is found to change k Q (and hence k B ) by less than 0.1%. Conclusions Orienting the chamber parallel to the magnetic field when the field is perpendicular to the photon beam will minimize the effect of the magnetic field on chamber response, and eliminate the problem of the unknown sensitive volume. Values of k B and k can bring ion chamber dosimetry in magnetic fields in‐line with the TG‐51 protocol. PP chamber are sensitive to the magnetic field and variation in chamber response due to small angular changes makes them unlikely candidates for clinical reference dosimetry in magnetic fields. The stability in TPR , as a function of magnetic fields and beam qualities, makes it the best beam quality specifier in magnetic fields.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.311
Teacher spread0.296 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations83
Published2017
Admission routes1
Has abstractyes

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