The radial dose function of low-energy brachytherapy seeds in different solid phantoms: comparison between calculations with the EGSnrc and MCNP4C Monte Carlo codes and measurements
Bibliographic record
Abstract
The use of low-energy photon emitters for brachytherapy applications, as in the treatment of the prostate or of eye tumours, has drastically increased in the last few years. New seed models for 103Pd and 125I have recently been introduced. The American Association of Physicists in Medicine recommends that measurements are made to obtain the dose rate constant, the radial dose function and the anisotropy function. These results must then be compared with Monte Carlo calculations to finally obtain the dosimetric parameters in liquid water. We have used the results obtained during the characterization of the new InterSource (furnished by IBt, Seneffe, Belgium) palladium and iodine sources to compare two Monte Carlo codes against experiment for these low energies. The measurements have been performed in three different media: two solid water plastics, WT1 and RW1, and polymethylmetacrylate. The Monte Carlo calculations were made using two different codes: MCNP4C and EGSnrc. These codes use photon cross-section data of a different origin. Differences were observed between both sets of input data below 100 keV, especially for the photoelectric effect. We obtained differences in the radial dose functions calculated with each code, which can be explained by the difference between the input data. New cross-section data were then tested for both codes. The agreement between the calculations using these new libraries is excellent. The differences are within the statistical uncertainties of the calculations. These results were compared with the experimental data. A good agreement is reached for both isotopes and in the three phantoms when the measured values are corrected for the presence of the TLDs in the phantom.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".