Benchmark of the PenRed Monte Carlo framework for HDR brachytherapy
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to validate the PenRed Monte Carlo framework for clinical applications in brachytherapy. PenRed is a C++ version of Penelope Monte Carlo code with additional tallies and utilities. METHODS AND MATERIALS: Six benchmarking scenarios are explored to validate the use of PenRed and its improved bachytherapy-oriented capabilities for HDR brachytherapy. A new tally allowing the evaluation of collisional kerma for any material using the track length kerma estimator and the possibility to obtain the seed positions, weights and directions processing directly the DICOM file are now implemented in the PenRed distribution. The four non-clinical test cases developed by the Joint AAPM-ESTRO-ABG-ABS WG-DCAB were evaluated by comparing local and global absorbed dose differences with respect to established reference datasets. A prostate and a palliative lung cases, were also studied. For them, absorbed dose ratios, global absorbed dose differences, and cumulative dose-volume histograms were obtained and discussed. RESULTS: ) and 0.1% (Λ). With respect to the first three WG-DCAB test cases, more than 99.8% of the voxels present local (global) differences within ±1%(±0.1%) of the reference datasets. For test Case 4 reference dataset, more than 94.9%(97.5%) of voxels show an agreement within ±1%(±0.1%), better than similar benchmarking calculations in the literature. The track length kerma estimator scorer implemented increases the numerical efficiency of brachytherapy calculations two orders of magnitude, while the specific brachytherapy source allows the user to avoid the use of error-prone intermediate steps to translate the DICOM information into the simulation. In both clinical cases, only minor absorbed dose differences arise in the low-dose isodoses. 99.8% and 100% of the voxels have a global absorbed dose difference ratio within ±0.2% for the prostate and lung cases, respectively. The role played by the different segmentation and composition material in the bone structures was discussed, obtaining negligible absorbed dose differences. Dose-volume histograms were in agreement with the reference data. CONCLUSIONS: PenRed incorporates new tallies and utilities and has been validated for its use for detailed and precise high-dose-rate brachytherapy simulations.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".