Monte Carlo study on mucosal dose in oral and naval cavity using photon beams with small field
Bibliographic record
Abstract
Abstract We study how mucosal dose in the oral or nasal cavity depends on the irradiated small segmental photon fields varying with beam energy, beam angle and mucosa thickness. Dose ratio (mucosal dose with bone underneath to dose at the same point without bone) reflecting the dose enhancement due to the bone backscatter was determined by Monte Carlo simulation (EGSnrc-based code), validated by measurements. Phase space files based on the 6 and 18 MV photon beams with small field size of 1 × 1 cm 2 , produced by a Varian 21 EX linear accelerator, were generated using the BEAMnrc Monte Carlo code. Mucosa phantoms (mucosa thickness = 1, 2 and 3 mm) with and without a bone under the mucosa were irradiated by photon beams with gantry angles varying from 0 to 30°. Doses along the central beam axis in the mucosa and the dose ratio were calculated with different mucosa thicknesses. For the 6 MV photon beams, the dose at the mucosa-bone interface increased by 44.9–41.7%, when the mucosa thickness increased from 1 to 3 mm for the beam angle ranging from 0 to 30°. These values were lower than those (58.8–53.6%) for the 18 MV photon beams with the same beam angle range. For both the 6 and 18 MV photon beams, depth doses in the mucosa were found to increase with an increase of the beam angle. Moreover, the dose gradient in the mucosa was greater for the 18 MV photon beams compared to the 6 MV. For the dose ratio, it was found that the dose enhancement due to the bone backscatter increased with a decrease of mucosa thickness, and was more significant at both the air-mucosa and mucosa-bone interface. Mucosal dose with bone was investigated by Monte Carlo simulations with different experimental configurations, and was found vary with the beam energy, beam angle and mucosa thickness for a small segmental photon field. The dosimetric information in this study should be considered when searching for an optimized treatment strategy to minimize the mucosal complications in the head-and-neck intensity-modulated radiation therapy.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".