TH‐C‐AUD A‐10: LDR Brachytherapy Dosimetry: Monte Carlo Code and TG‐43 Comparisons
Bibliographic record
Abstract
Purpose To study the Monte Carlo codes PTRAN_CT and MCNPX2.5 and compare the dosimetry results with the TG‐43 formalism for a permanent seed implant of a breast brachytherapy. Method and Materials: The geometry validation of a model 6711 iodine seed was studied calculating the radial dose function in water and the energy spectrum of the seed in air. The results for the calculated spectrum were compared with an experiment carried out with an Amptek XR‐100T spectrometer. The calculation times for MCNPX and PTRAN_CT were analyzed by calculating the figure of merit for water phantoms with different voxel numbers. The absolute dose was validated comparing the absolute dose in water with TG‐43 and the absolute isodoses obtained from EBT Gafchromic film. The results of a treatment plan for a breast brachytherapy were compared with TG‐43 calculations. Results: The discrepancy between the calculated and published radial dose function values is less than 3% for the two MC codes. The comparison of the energy spectrum with the experiment reveals a contribution of the detector diode for the energy inferior to 5 keV. The calculation time comparison between MCNPX and PTRAN_CT shows that PTRAN_CT is 10%–30% faster than MCNPX for a voxel number between 200,000 and 500,000. A good agreement is obtained for the absolute dose calculated by the two MC codes compared to the TG‐43 calculation in water and the absolute isodoses measured in the Gafchromic film. The breast cancer patient plan shows that the MC results differ 12.7% in comparison with the TG‐43 results. Conclusion: MCNPX and PTRAN_CT simulations agree with the absolute dose in water obtained with TG‐43 and experiments. Moreover, the patient dosimetry study reveals the interest to use a MC code where the tissue composition and the interseed attenuation are taken into account.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".