The use of film dosimetry of the penumbra region to improve the accuracy of intensity modulated radiotherapy
Bibliographic record
Abstract
Accurate measurements of the penumbra region are important for the proper modeling of the radiation beam for linear accelerator-based intensity modulated radiation therapy. The usual data collection technique with a standard ionization chamber artificially broadens the measured beam penumbrae due to volume effects. The larger the chamber, the greater is the spurious increase in penumbra width. This leads to inaccuracies in dose calculations of small fields, including small fields or beam segments used in IMRT. This source of error can be rectified by the use of film dosimetry for penumbra measurements because of its high spatial resolution. The accuracy of IMRT calculations with a pencil beam convolution model in a commercial treatment planning system was examined using commissioning data with and without the benefit of film dosimetry of the beam penumbrae. A set of dose-spread kernels of the pencil beam model was calculated based on commissioning data that included beam profiles gathered with a 0.6-cm-i.d. ionization chamber. A second set of dose-spread kernels was calculated using the same commissioning data with the exception of the penumbrae, which were measured with radiographic film. The average decrease in the measured width of the 80%-20% penumbrae of various square fields of size 3-40 cm, at 5 cm depth in water-equivalent plastic was 0.27 cm. Calculations using the pencil beam model after it was re-commissioned using film dosimetry of the penumbrae gave better agreement with measurements of IMRT fields, including superior reproduction of high dose gradient regions and dose extrema. These results show that accurately measuring the beam penumbrae improves the accuracy of the dose distributions predicted by the treatment planning system and thus is important when commissioning beam models used for IMRT.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".