SU‐FF‐T‐316: Measured and Calculated Dose Distribution Around 125I Brachytherapy Seeds in a Breast Phantom
Bibliographic record
Abstract
Purpose: To compare measurement with Gafchromic® EBT films and Monte Carlo (MC) calculations of the dose distribution around LDR brachytherapy 125I seeds in a breast phantom and to analyze the effect of tissue elemental composition. Method: MC simulations of IBt Interseed125 seeds were performed, using MCNP4C. In view of the low energy of the photons, the detailed physics treatment was used, with libraries from EPDL97 and no electron transport. In order to evaluate the perturbation of the film, simulations were carried out to compare the dose distributions in the film and in water or acrylic. The radial dose function of tissues and potential substitutes were determined using MC and compared to associate the best substitute to the desired tissue. Measurements for 5 seeds in an acrylic breast phantom were performed and compared with the MC simulations for the same geometry. Results: Our simulations show no significant differences between dose distributions calculated in films and in water (average difference 0.13%). Similar results can be observed for simulations in acrylic. The radial dose function of acrylic is very close to the one of breast tissue (2/3 mammal gland, 1/3 fat). However, there is a significant difference in the dose distributions in acrylic and water (average 7%, maximum 25%). The comparison between the measurements in the acrylic phantom and the calculations shows a good agreement between the isodose distributions (within 12%). Conclusion: Both in water and in acrylic, EBT films appear to introduce no significant perturbation to the measured dose distribution around 125I LDR brachytherapy seeds. These films are very useful tools for measurements around 125I seeds. There is a significant tissue composition effect that should be taken into account in LDR brachytherapy dosimetry. Acrylic appears to be the best substitute for breast tissue. Seeds furnished by IBt.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".