Poster — Wed Eve—02: <i>Monte Carlo Dose Calculation of Critical Organs in MDR Cs‐137 Afterloading Intracavitary Brachytherapy</i>
Bibliographic record
Abstract
The aim of this study is to perform Monte Carlo dose calculations on two critical organs, bladder and rectum, by considering the effects of applicator attenuation for three different applicator diameters of the Selectron/MDR intracavitary brachytherapy system. Three different pelvic phantoms, with a gynecological cylinder, were used to simulate the treatments. Dosimetric measurements were carried out in five different positions in the rectum and one position in the bladder using p‐type diode detectors. The absorbed doses at clinical points in the phantoms were calculated using the MCNP5 Monte Carlo code and the PLATO commercial treatment planning system (TPS). It was found that the dose‐rate constant for the pellet source was with uncertainty within 1.33% compared to the latest published data. In all cases, results of the Monte Carlo based calculations agreed better with measured doses than those of the PLATO TPS, with the maximum deviation occurring for the 3 cm diameter applicator in the rectum. The largest discrepancy seen in this study, between measured dose and the TPS calculated dose, was 7.1%. The Monte Carlo calculation, for the same position, had a dose discrepancy of 3.0%. The average deviation between the PLATO TPS calculated doses and measured doses was approximately double what was seen between the Monte Carlo results and measured doses. This is due to the absence of the applicator attenuation effect in the PLATO TPS. Therefore, Monte Carlo simulation can be considered a more accurate dose calculation method in this study.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".