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Record W2000162922 · doi:10.1118/1.598936

Modeling photon output caused by backscattered radiation into the monitor chamber from collimator jaws using a Monte Carlo technique

2000· article· en· W2000162922 on OpenAlexfundno aff
H. Helen Liu, T. Rockwell Mackie, Edwin C. McCullough

Bibliographic record

VenueMedical Physics · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsMonte Carlo methodCollimatorBackscatter (email)DosimetryLinear particle acceleratorRadiationPhotonOpticsIonization chamberPhysicsMonitor unitDose profileComputational physicsNuclear medicineBeam (structure)Computer scienceMathematicsMedicine

Abstract

fetched live from OpenAlex

Dose per monitor unit in photon fields generated by clinical linear accelerators can be affected by the backscattered radiation into the monitor chamber from collimator jaws. Thus, it is necessary to account for the backscattered radiation in computing monitor unit setting for a treatment field. In this work, we investigated effects of the backscatter from collimator jaws based on Monte Carlo simulations of a clinical linear accelerator. The backscattered radiation scored within the monitor chamber was identified as originating either from the upper jaws (Y jaws), or from the lower jaws (X jaws). From the results of Monte Carlo simulations, ratios of the monitor-chamber-scored dose caused by the backscatter to the dose caused by the forward radiation, R(x,y), were modeled as functions of the individual X and Y jaw positions. The amount of the backscattered radiation for any field setting was then computed as a compound contribution from both the X and Y jaws. The dose ratios of R(x,y) were then used to calculate the change in photon output caused by the backscatter, Scb(x,y). Results of these calculations were compared with available measured data based on counting the electron pulses or charge from the electron target of an accelerator. Data from this study showed that the backscattered radiation contributes approximately 3% to the monitor-chamber-scored dose. A majority of the backscattered radiation comes from the upper jaws, which are located closer to the monitor chamber. The amount of the backscatter decreases approximately in a linear fashion with the jaw opening. This results in about a 2% increase of photon output from a 10 cm x 10 cm field to a 40 cm x 40 cm field. The off-axis location of the jaw opening does not have a significant effect on the magnitude of the backscatter. The backscatter effect is significant for monitor chambers using kapton windows, particularly for treatment fields using moving jaws. Applying the backscatter correction improves the accuracy of monitor-unit calculation using a model-based dose calculation algorithm such as the convolution method.

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)0.002
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.275
Teacher spread0.264 · 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

Citations61
Published2000
Admission routes1
Has abstractyes

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