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Record W3002548445 · doi:10.1002/mp.14048

A modified formalism for electron beam reference dosimetry to improve the accuracy of linac output calibration

2020· article· en· W3002548445 on OpenAlexaff
Bryan Muir

Bibliographic record

VenueMedical Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDosimetryFormalism (music)Monte Carlo methodIonization chamberLaser beam qualityPhysicsIonizationCathode rayLinear particle acceleratorElectronCalibrationAbsorbed doseBeam (structure)Atomic physicsComputational physicsOpticsNuclear medicineNuclear physicsRadiationMathematicsStatisticsIon

Abstract

fetched live from OpenAlex

Purpose To present and demonstrate the accuracy of a modified formalism for electron beam reference dosimetry using updated Monte Carlo calculated beam quality conversion factors. Methods The proposed, simplified formalism allows the use of cylindrical ionization chambers in all electron beams (even those with low beam energies) and does not require a measured gradient correction factor. Data from a previous publication are used for beam quality conversion factors. The formalism is tested and compared to the present formalism in the AAPM TG‐51 protocol with measurements made in Elekta Precise electron beams with energies between 4 MeV and 22 MeV and with fields shaped with a 10 × 10 cm2 clinical applicator as well as a 20 × 20 cm2 clinical applicator for the 18 MeV and 22 MeV beams. A set of six ionization chambers are used for measurements (two cylindical reference‐class chambers, two scanning‐type chambers and two parallel‐plate chambers). Dose per monitor unit is derived using the data and formalism provided in the TG‐51 protocol and with the proposed formalism and data and compared to that obtained using ionization chambers calibrated directly against primary standards for absorbed dose in electron beams. Results The standard deviation of results using different chambers when TG‐51 is followed strictly is on the order of 0.4% when parallel‐plate chambers are cross‐calibrated against cylindrical chambers. However, if parallel‐plate chambers are directly calibrated in a cobalt‐60 beam, the difference between results for these chambers is up to 2.2%. Using the proposed formalism and either directly calibrated or cross‐calibrated parallel‐plate chambers gives a standard deviation using different chambers of 0.4%. The difference between results that use TG‐51 and the primary standard measurements are on the order of 0.6% with a maximum difference in the 4 MeV beam of 2.8%. Comparing the results obtained with the proposed formalism and the primary standard measurements are on the order of 0.4% with a maximum difference of 1.0% in the 4 MeV beam. Conclusions The proposed formalism and the use of updated data for beam quality conversion factors improves the consistency of results obtained with different chamber types and improves the accuracy of reference dosimetry measurements. Moreover, it is simpler than the present formalism and will be straightforward to implement clinically.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.308
Teacher spread0.285 · 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 designBench or experimental
Domainnot available
GenreMethods

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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Citations11
Published2020
Admission routes1
Has abstractyes

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