TH‐A‐19A‐01: An Open Source Software for Proton Treatment Planning in Heterogeneous Medium
Bibliographic record
Abstract
Purpose: Due to its success in Radiation Oncology during the last decade, interest in proton therapy is on the rise. Unfortunately, despite the global enthusiasm in the field, there is presently no free, multiplatform and customizable Treatment Planning System (TPS) providing proton dose distributions in heterogenous medium. This restricts substantially the progress of clinical research for groups without access to a commercial Proton TPS. The latest implementation of our pencil beam dose calculation algorithm for proton beams within the 3D Slicer open‐source environment fulfills all the conditions described above. Methods: The core dose calculation algorithm is based on the Hong algorithm (1), which was upgraded with the Kanematsu theory describing the evolution of the lateral scattering of proton beamlets in heterogeneous medium. This algorithm deals with both mono‐energetic beams and Spread Out Bragg Peak (SOBP). In order to be user‐friendly, we provide a graphical user interface implemented with the Qt libraries, and visualization with the 3D Slicer medical image analysis software. Two different pencil beam algorithms were developed, and the clinical proton beam line at our facility was modeled. Results: The dose distributions provided by our algorithms were compared to dose distributions coming from both commercialized XiO TPS and literature (dose measurements, GEANT4 and MCNPx) and turned out to be in a good agreement, with maximum dose discrepancies of 5% in homogeneous phantoms and 10% in heterogeneous phantoms. The algorithm of SOBP creation from an optimized weigthing of mono‐energetic beams results in flat SOBP. Conclusion: We hope that our efforts in implementing this new, open‐source proton TPS will help the research groups to have a free access to a useful, reliable proton dose calculation software.(1) L. Hong et al., A pencil beam algorithm for proton dose calculations, Phys. Med. Biol. 41 (1996) 1305–1330. This project is paid for by NCI/MGH Federal share as a research grant.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 0.017 |
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".