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Record W2017081951 · doi:10.1118/1.4861715

Model‐based dose calculations for COMS eye plaque brachytherapy using an anatomically realistic eye phantom

2014· article· en· W2017081951 on OpenAlexaff
Marielle Lesperance, M. Inglis‐Whalen, Rowan M. Thomson

Bibliographic record

VenueMedical Physics · 2014
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsCarleton University
Fundersnot available
KeywordsImaging phantomBrachytherapyDosimetryNuclear medicineAttenuationMaterials scienceVoxelBiomedical engineeringAbsorption (acoustics)Monte Carlo methodOpticsPhysicsMedicineRadiation therapyMathematicsRadiology

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the effects of the composition and geometry of ocular media and tissues surrounding the eye on dose distributions for COMS eye plaque brachytherapy with(125)I, (103)Pd, or (131)Cs seeds, and to investigate doses to ocular structures. METHODS: An anatomically and compositionally realistic voxelized eye model with a medial tumor is developed based on a literature review. Mass energy absorption and attenuation coefficients for ocular media are calculated. Radiation transport and dose deposition are simulated using the EGSnrc Monte Carlo user-code BrachyDose for a fully loaded COMS eye plaque within a water phantom and our full eye model for the three radionuclides. A TG-43 simulation with the same seed configuration in a water phantom neglecting the plaque and interseed effects is also performed. The impact on dose distributions of varying tumor position, as well as tumor and surrounding tissue media is investigated. Each simulation and radionuclide is compared using isodose contours, dose volume histograms for the lens and tumor, maximum, minimum, and average doses to structures of interest, and doses to voxels of interest within the eye. RESULTS: Mass energy absorption and attenuation coefficients of the ocular media differ from those of water by as much as 12% within the 20-30 keV photon energy range. For all radionuclides studied, average doses to the tumor and lens regions in the full eye model differ from those for the plaque in water by 8%-10% and 13%-14%, respectively; the average doses to the tumor and lens regions differ between the full eye model and the TG-43 simulation by 2%-17% and 29%-34%, respectively. Replacing the surrounding tissues in the eye model with water increases the maximum and average doses to the lens by 2% and 3%, respectively. Substituting the tumor medium in the eye model for water, soft tissue, or an alternate melanoma composition affects tumor dose compared to the default eye model simulation by up to 16%. In the full eye model simulations, the average dose to the lens is larger by 7%-9% than the dose to the center of the lens, and the maximum dose to the optic nerve is 17%-22% higher than the dose to the optic disk for all radionuclides. In general, when normalized to the same prescription dose at the tumor apex, doses delivered to all structures of interest in the full eye model are lowest for(103)Pd and highest for (131)Cs, except for the tumor where the average dose is highest for (103)Pd and lowest for (131)Cs. CONCLUSIONS: The eye is not radiologically water-equivalent, as doses from simulations of the plaque in the full eye model differ considerably from doses for the plaque in a water phantom and from simulated TG-43 calculated doses. This demonstrates the importance of model-based dose calculations for eye plaque brachytherapy, for which accurate elemental compositions of ocular media are necessary.

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 score0.903
Threshold uncertainty score0.604

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 head0.051
GPT teacher head0.383
Teacher spread0.331 · 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

Citations43
Published2014
Admission routes1
Has abstractyes

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