Development of a motorized iris collimator for kilovoltage x-ray radiotherapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Objective. To design and build a motorized iris collimator suitable for a novel low-cost kilovoltage dual-robot radiotherapy device and test its reliability and dosimetric capabilities. Approach. A 12-leaflet motorized iris collimator was designed and built weighing 4.8 kg, with 1 mm thick tungsten leaflets, a beam size range of 0.1 cm to 16.5 cm, and a leaflet speed up to 20 cm/s. Dosimetric tests were performed with EBT4 Gafchromic film at depths of 0 to 10 cm in a Solid Water phantom at a source to surface distance of 38 cm using a 225 kVp beam with 2 mm of Al filtration. A Monte Carlo (MC) model of the experimental setup was developed. Beam size was determined by full width at half maximum (FWHM) and penumbra values were calculated for both film and MC. The beam size was measured experimentally using digital radiographs acquired for sizes between 5 and 150 mm to evaluate the robustness of the system. Main results. The collimator demonstrated sharp profiles with penumbra values ≤1.2 mm at 2 cm depth. 2D dose distributions from film measurements found dose leakage within the designed 2% as well as a single offset leaflet as a result of machining tolerance. MC matched film measurements with surface central dose differences ≤1.1%, a beam penumbra match within 0.08 mm, and a FWHM match within 1.1 mm. The linearity and repeatability showed that beam sizes can be set with an accuracy of ≤1.25 mm for beams ≥1 cm. Significance. This work showcases a motorized iris collimator designed for a novel low-cost radiotherapy device, capable of delivering sharp dose distributions. An MC model was successfully developed and matched to film measurements, allowing for accurate simulation of radiotherapy delivery.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it