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Record W6982442709

Improving the energy response of external beam therapy (EBT) GAFCHROMIC Dosimetry films at low energies (s100keV)

2013· dissertation· en· W6982442709 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldArts and Humanities
TopicPhotography and Visual Culture
Canadian institutionsnot available
FundersJewish General Hospital
KeywordsDosimetryMonte Carlo methodBeam (structure)Energy (signal processing)Beam energyMockup
DOInot available

Abstract

fetched live from OpenAlex

Many studies have been conducted to investigate the energy dependence of External Beam Therapy (EBT) GAFCHROMICTM dosimetry films and showed that the different film models are water equivalent down to about 100 keV and their response is energy independent down to about 100 keV. The purpose of our study is to investigate the energy dependence of commercially available films to understand the physics behind the energy variation of the films response as well as the intrinsic energy dependence and to develop a new prototype with more uniform energy response at low energies (≤100 keV). The study is comprised of two components. The first component is evaluating the energy dependence of three different commercial GAFCHROMICTM dosimetry film models that represent the three different film configurations, EBT, EBT2 and EBT3 that have been manufactured up to date. The energy dependence evaluation can be further divided into two parts. The first part is experimentally evaluating the energy dependence of the response by irradiating the films to a fixed dose of 2Gy to water at different beam qualities (ranging from 50kVp to 60Co) and then measuring the corresponding response of the film, i.e. net optical density change, using a flat bed document scanner. The second part of the energy dependence evaluation is using the DOSRZnrc Monte Carlo code, which is one of the user codes of the EGSnrcMP (Electron-Gamma-Shower) Monte Carlo code, to calculate the corresponding absorbed dose to water energy dependence of the films, i.e. the ratio of dose to water to dose to the active volume of the film, using the experimental beams spectra, which were calculated using SpekCalc, an x-ray spectrum generating software, by matching the measured HVL, tube potential and added filtration of the experimental beams. The first component of our study would help us 1) understand the physics behind the energy variation of the film response, 2) evaluate the intrinsic energy dependence of the film, i.e. dose to film sensitive layer per unit film response as a function of beam quality, using the measured energy response and the corresponding absorbed dose to water energy dependence, 3) guide us to what can be done to improve the energy dependence at low energies. The second component of the study is adjusting the film sensitive layer composition with the guidance of Monte Carlo simulations of the absorbed dose to water energy dependence of the film to reduce the energy dependence of the film response at low energies, and making new film prototypes based on the new possible elemental compositions, then experimentally evaluating their energy response. Improving the energy dependence of the EBT GAFCHROMICTM dosimetry film at low energies will make it more suitable for high quality clinical dosimetry. It would be very convenient for clinical dosimetry to have one film dosimetry calibration curve that works at kilovoltage and megavoltage beam qualities. This would allow us to create the film dosimetry calibration curve at, for example, 60Co and then use it for film dosimetry at kilovoltage and other megavoltage beam qualities. On the other hand, since the x-ray spectrum changes in quality and quantity with depth as it penetrates into patient tissue, it is very important that the response of the detector as a function of beam quality be as flat as possible to minimize the uncertainty and error in dose determination. Thus, improving the energy dependence at low energy will result in improving the accuracy of film dosimetry.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.017
GPT teacher head0.229
Teacher spread0.213 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2013
Admission routes1
Has abstractyes

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