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Record W4403787127 · doi:10.1002/mp.17462

E‐Brachy: New dosimetry package for electronic brachytherapy sources

2024· article· en· W4403787127 on OpenAlexafffund
Azin Esmaelbeigi, Jonathan Kalinowski, Nada Tomic, Mark J. Rivard, T. Vuong, Slobodan Dević, Shirin A. Enger

Bibliographic record

VenueMedical Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsJewish General HospitalMcGill University
FundersJewish General HospitalFondation de l'Hôpital général juifCanada Research Chairs
KeywordsBrachytherapyDosimetryDose rateMedical physicsRadioactive sourceMaterials scienceNuclear medicinePhysicsOpticsRadiation therapyMedicineRadiology

Abstract

fetched live from OpenAlex

Abstract Background Large reported variability in the material composition and geometrical components of the Xoft electronic high dose rate brachytherapy causes inter‐source discrepancy in the source output. This variability is due to the manual manufacturing and assembly of the sources. Purpose This study aimed to develop a dosimetry software tool called E‐Brachy to characterize the Xoft source and quantify the discrepancies in its photon spectrum and dosimetric properties. Methods E‐Brachy is based on the Geant4 Monte Carlo toolkit and consists of two parts. In part one, the geometry and material composition for the source received in the computer‐aided design format from the vendor were converted to the geometry description markup language format using the GUIMesh Python tool and integrated into the E‐Brachy software. There was a large variation in material composition and thickness for some of the tube components. The simulation started from electrons and resulted in x‐ray generations in the anode region. Multithreading, a track length estimation, and the uniform bremsstrahlung splitting variance reduction techniques were used to decrease the simulation time and increase the x‐ray production. The photon energy, position, and momentum were saved into a phase space file as the photon exited the source, but before interacting with the external environment. The obtained x‐ray energy spectrum was compared with measurements from the National Institute of Standards and Technology (NIST). In part two, by sampling from the generated photons, the dose rates and dosimetric parameters according to the TG‐43 protocol were calculated for model S7500 and compared to the ones previously calculated for model S700 source, which were deemed identical by the manufacturer. Results The material composition that resulted in the most similar spectrum as the measured NIST spectrum with Pearson's correlation coefficient of 0.99 and a calculated Euclidean difference of keV was chosen for further dosimetric analysis of the model S7500 source. Characteristic peaks showed the presence of tungsten, yttrium, and silver in the source components. Differences in dose rates between the two source models surpassed 20% for polar angles , reaching a peak at cm and . The differences in the radial dose function values were within 5%. The relative difference in percentage between the anisotropy function values of the two models was closer to 0 for smaller values, but at higher polar angles, they increased to 300%. Conclusions A software package called E‐Brachy was successfully developed for the characterization and dosimetry of Xoft electronic brachytherapy sources. E‐Brachy can be combined with spectral measurements to investigate the inter‐ and intra‐source variability. The software package was tested by comparing the simulated spectra from the S7500 Xoft source model with NIST measurements and its TG‐43 parameters with the S700 model. The TG‐43 parameters between the two sources significantly exceed the recommendations of TG‐56.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.045
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0450.015

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 head0.008
GPT teacher head0.299
Teacher spread0.290 · 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".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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