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Record W2026359758 · doi:10.1118/1.2874552

Monte Carlo simulation of backscatter from lead for clinical electron beams using EGSnrc

2008· article· en· W2026359758 on OpenAlexafffund
James C. L. Chow, Grigor N. Grigorov

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsGrand River HospitalToronto Metropolitan University
FundersNational Research Council CanadaMcGill UniversityVarian Medical Systems
KeywordsMonte Carlo methodElectronMaterials scienceBeam (structure)Backscatter (email)Cathode rayDosimetryAtomic physicsPhysicsOpticsNuclear medicineNuclear physics

Abstract

fetched live from OpenAlex

In electron radiotherapy of superficial lesions in the eyelid, lip, buccal mucosa, ear, and nose, backscattered electrons are produced from the lead shield used to protect the critical tissue underneath the tumor. In this study, the backscattered electrons, produced by clinical electron beams using a Varian 21 EX linear accelerator, were studied using Monte Carlo simulations. The electron backscatter factor (EBF), defined as the ratio of dose at the tissue-lead interface to the dose at the same point without the presence of backscatter, was calculated using the Monte Carlo EGSnrc-based code. The calculated EBFs were verified with measurements using metal-oxide-semiconductor field effect transistor detectors. The effect of the (1) initial electron beam energy, (2) thickness of bolus over the lead shield, (3) beam's angle of incidence, and (4) presence of an aluminum sheet used to absorb backscattered electrons, on the EBF, were studied. It is found that for lead shielding positioned at any fixed depth, the EBF decreases with an increase in initial electron beam energy (4-16 MeV). In addition, for depths within the electron practical range, Rp, and at a particular beam energy, the EBF increases with depth (or thickness of the treatment volume). When the electron beam angle increases from 0 degrees to 5 degrees, the EBF only decreases slightly (<4%) for all energies. The influence of the beam obliquity on the EBF is important when the treatment surface is not flat and perpendicular to the central beam axis. The use of an aluminum sheet to reduce backscattered electrons was also investigated. For a relatively low electron beam energy (4 MeV), a 2 mm aluminum sheet can reduce backscattering by 31%. While the electron beam energy increased, less backscattered electrons were produced and therefore removed by the same thickness of aluminum (only about 6% for 16 MeV). The Monte Carlo calculated EBFs from this study, characterized by the electron beam energy, depth of bolus above the lead shield, beam obliquity, and presence of an aluminum sheet, may provide important clinical information for radiation oncology staff when considering the effect of electron backscatter on radiotherapy using internal shielding.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.796
Threshold uncertainty score0.507

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 head0.054
GPT teacher head0.389
Teacher spread0.335 · 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 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

Citations27
Published2008
Admission routes2
Has abstractyes

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