BrachyGUI: an adjunct to an accelerated Monte Carlo photon transport code for patient-specific brachytherapy dose calculations and analysis
Bibliographic record
Abstract
A number of accelerated Monte Carlo (MC) codes have been developed in recent years for brachytherapy applications, one of which is PTRAN_CT. Developed as an extension to the well-benchmarked PTRAN code, PTRAN_CT can be used to perform efficient patient-specific dose calculations. The code can explicitly account for the patient geometry converted from computed-tomography (CT) images, as well as perturbations due to the brachytherapy applicator and seeds. We have developed a software tool called BrachyGUI that provides an integrated environment for preparing patient and treatment plan-specific input data files for PTRAN_CT. It also comes with dose calculation, analysis, and treatment planning capabilities. In this article, we will describe the interface of BrachyGUI with PTRAN_CT for CT-based calculations, and examine the calculation efficiency of PTRAN_CT. We conclude that it is now feasible to use PTRAN_CT for high dose rate brachytherapy treatment planning on a routine clinical basis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".