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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".