Beam collimation and filtration optimization for a novel orthovoltage radiotherapy system
Bibliographic record
Abstract
Abstract Background The inaccessibility of clinical linear accelerators in low‐ and middle‐income countries creates a need for low‐cost alternatives. Kilovoltage (kV) x‐ray tubes have shown promise as a source that could meet this need. However, performing radiotherapy with a kV x‐ray tube has numerous difficulties, including high skin dose, rapid dose fall‐off, and low dose rates. These limitations create a need for highly effective beam collimation and filtration. Purpose To improve the treatment potential of a novel kV x‐ray system by optimizing an iris collimator and beam filtration using Bayesian techniques and Monte Carlo (MC) simulations. Methods The Kilovoltage Optimized AcceLerated Adaptive therapy system's current beam configuration consists of a 225 kVp x‐ray tube, a 12‐leaflet tungsten iris collimator, and a 0.1 mm copper filter. A Bayesian optimization was performed for the large and small focal spot sizes of the kV x‐ray tube source at 220 kVp using TopasOpt, an open‐source library for optimization in TOPAS. Collimator thickness, copper filter thickness, source‐to‐collimator distance (SCD), and source‐to‐surface distance (SSD) were the variables considered in the optimization. The objective function was designed to maximize the dose rate and the dose at a depth of 5 cm while minimizing the beam penumbra width and the out‐of‐field dose (OFD), all evaluated in a water phantom. Post‐optimization, the optimal beam configuration was simulated and compared to the existing configuration. Results The optimal collimation setup consisted of 2.5 mm thick tungsten leaflets for the iris collimator and a 350 mm SSD for both focal spot sizes. The optimal copper filtration was 0.22 mm for the large focal spot and 0.15 mm for the small focal spot, with a SCD of 148.5 mm for the large focal spot and 125.8 mm for the small focal spot. For the large focal spot, the surface dose rate decreased by 9.4%, while the PDD at 5cm depth () increased by 7.7% compared to the existing iris collimator. Additionally, the surface beam penumbra width was reduced by 31.3%, and no significant changes in the OFD were observed. For the small focal spot, the surface dose rate for the new collimator increased by 3.7% and the increased by 5.3%, with no statistically significant changes in the beam penumbra width or OFD. Conclusion The optimal beam collimation and filtration for both x‐ray tube focal spot sizes of a kV radiotherapy system was determined using Bayesian optimization and MC simulations and resulted in improved dose distributions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".