Monte Carlo iodine brachytherapy dosimetry: study for a clinical application
Bibliographic record
Abstract
At present, all clinical algorithms used in brachytherapy are based on the TG-43 algorithm, which has the advantage to offer very fast calculation time. However, this formalism has many simplifications, assuming for example the patient tissue composition equivalent to water. For low energy brachytherapy seeds such as iodine seeds, it is of interest to evaluate the dosimetric differences between calculations based on Monte Carlo simulations (considered the gold standard) and the TG-43 formalism. For a 6711 model 125 I seed calculated photon spectra were compared to spectra measured with a CdTe spectrometer. Good agreement was found except for the lowest energy peak which seems to be over-estimated by the experiment due to the contribution of the spectrometer CdTe diode to the measurement. Dose distributions in water are measured with EBT Gafchromic film and compared to the Monte Carlo calculation. A very good agreement is found. Finally, the method to create a MCNPX input file from computed tomography (CT) scanner images is explained and some preliminary isodose distributions are presented.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".