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Record W2081672047 · doi:10.1118/1.4864474

Monte Carlo dosimetry for <sup>103</sup>Pd, <sup>125</sup>I, and <sup>131</sup>Cs ocular brachytherapy with various plaque models using an eye phantom

2014· article· en· W2081672047 on OpenAlexafffund
Marielle Lesperance, Martin P. Martinov, Rowan M. Thomson

Bibliographic record

VenueMedical Physics · 2014
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsOhio State University
KeywordsBrachytherapyDosimetryImaging phantomCollimated lightMonte Carlo methodMaterials scienceNuclear medicineSiliconeBiomedical engineeringOpticsRadiation therapyPhysicsMedicineRadiologyMathematicsComposite material

Abstract

fetched live from OpenAlex

PURPOSE: To investigate dosimetry for ocular brachytherapy for a range of eye plaque models containing(103)Pd, (125)I, or (131)Cs seeds with model-based dose calculations. METHODS: Five representative plaque models are developed based on a literature review and are compared to the standardized COMS plaque, including plaques consisting of a stainless steel backing and acrylic insert, and gold alloy backings with: short collimating lips and acrylic insert, no lips and silicone polymer insert, no lips and a thin acrylic layer, and individual collimating slots for each seed within the backing and no insert. Monte Carlo simulations are performed using the EGSnrc user-code BrachyDose for single and multiple seed configurations for the plaques in water and within an eye model (including nonwater media). Simulations under TG-43 assumptions are also performed, i.e., with the same seed configurations in water, neglecting interseed and plaque effects. Maximum and average doses to ocular structures as well as isodose contours are compared for simulations of each radionuclide within the plaque models. RESULTS: The presence of the plaque affects the dose distribution substantially along the plaque axis for both single seed and multiseed simulations of each plaque design in water. Of all the plaque models, the COMS plaque generally has the largest effect on the dose distribution in water along the plaque axis. Differences between doses for single and multiple seed configurations vary between plaque models and radionuclides. Collimation is most substantial for the plaque with individual collimating slots. For plaques in the full eye model, average dose in the tumor region differs from those for the TG-43 simulations by up to 10% for(125)I and (131)Cs, and up to 17% for (103)Pd, and in the lens region by up to 29% for (125)I, 34% for (103)Pd, and 28% for (131)Cs. For the same prescription dose to the tumor apex, the lowest doses to critical ocular structures are generally delivered with plaques containing (103)Pd seeds. CONCLUSIONS: The combined effects of ocular and plaque media on dose are significant and vary with plaque model and radionuclide, suggesting the importance of model-based dose calculations employing accurate ocular and plaque media and geometries for eye plaque brachytherapy.

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)0.001
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.021
GPT teacher head0.294
Teacher spread0.273 · 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

Citations27
Published2014
Admission routes2
Has abstractyes

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