Effect of the bone heterogeneity on the dose prescription in orthovoltage radiotherapy: A Monte Carlo study
Bibliographic record
Abstract
BACKGROUND: In orthovoltage radiotherapy, since the dose prescription at the patient's surface is based on the absolute dose calibration using water phantom, deviation of delivered dose is found as the heterogeneity such as bone present under the patient's surface. AIM: This study investigated the dosimetric impact due to the bone heterogeneity on the surface dose in orthovoltage radiotherapy. MATERIALS AND METHODS: A 220 kVp photon beam with field size of 5 cm diameter, produced by a Gulmay D3225 orthovoltage X-ray machine was modeled by the BEAMnrc. Phantom containing water (thickness = 1-5 mm) on top of a bone (thickness = 1 cm) was irradiated by the 220 kVp photon beam. Percentage depth dose (PDD), surface dose and photon energy spectrum were determined using Monte Carlo simulations (the BEAMnrc code). RESULTS: PDD results showed that the maximum bone dose was about 210% higher than the surface dose in the phantoms with different thicknesses of water. Surface dose was found to be increased in the range of 2.5-3.7%, when the distance between the phantom surface and bone was increased in the range of 1-5 mm. The increase of surface dose was found not to follow the increase of water thickness, and the maximum increase of surface dose was found at the thickness of water equal to 3 mm. CONCLUSIONS: For the accepted total orthovoltage radiation treatment uncertainty of 5%, a neglected consideration of the bone heterogeneity during the dose prescription in the sites of forehead, chest wall and kneecap with soft tissue thickness = 1-5 mm would cause more than two times of the bone dose, and contribute an uncertainty of about 2.5-3.7% to the total uncertainty in the dose delivery.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".