Evaluation of a new commercial Monte Carlo dose calculation algorithm for electron beams
Bibliographic record
Abstract
PURPOSE: In this report the authors present the validation of a Monte Carlo dose calculation algorithm (XiO EMC from Elekta Software) for electron beams. METHODS: Calculated and measured dose distributions were compared for homogeneous water phantoms and for a 3D heterogeneous phantom meant to approximate the geometry of a trachea and spine. Comparisons of measurements and calculated data were performed using 2D and 3D gamma index dose comparison metrics. RESULTS: Measured outputs agree with calculated values within estimated uncertainties for standard and extended SSDs for open applicators, and for cutouts, with the exception of the 17 MeV electron beam at extended SSD for cutout sizes smaller than 5 × 5 cm(2). Good agreement was obtained between calculated and experimental depth dose curves and dose profiles (minimum number of measurements that pass a 2%/2 mm agreement 2D gamma index criteria for any applicator or energy was 97%). Dose calculations in a heterogeneous phantom agree with radiochromic film measurements (>98% of pixels pass a 3 dimensional 3%/2 mm γ-criteria) provided that the steep dose gradient in the depth direction is considered. CONCLUSIONS: Clinically acceptable agreement (at the 2%/2 mm level) between the measurements and calculated data for measurements in water are obtained for this dose calculation algorithm. Radiochromic film is a useful tool to evaluate the accuracy of electron MC treatment planning systems in heterogeneous media.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".