Dosimetric evaluation of the clinical implementation of the first commercial IMRT Monte Carlo treatment planning system at 6 MV
Bibliographic record
Abstract
In this work we dosimetrically evaluated the clinical implementation of a commercial Monte Carlo treatment planning software (PEREGRINE, North American Scientific, Cranberry Township, PA) intended for quality assurance (QA) of intensity modulated radiation therapy treatment plans. Dose profiles calculated in homogeneous and heterogeneous phantoms using this system were compared to both measurements and simulations using the EGSnrc Monte Carlo code for the 6 MV beam of a Varian CL21EX linear accelerator. For simple jaw-defined fields, calculations agree within 2% of the dose at d(max) with measurements in homogeneous phantoms with the exception of the buildup region where the calculations overestimate the dose by up to 8%. In heterogeneous lung and bone phantoms the agreement is within 3%, on average, up to 5% for a 1 x 1 cm2 field. We tested two consecutive implementations of the MLC model. After matching the calculated and measured MLC leakage, simulations of static and dynamic MLC-defined fields using the most recent MLC model agreed to within 2% with measurements.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".