Evaluating the biological impact of increased scattered radiation in single and composite field radiation beams
Bibliographic record
Abstract
Abstract Low energy scattered particles cause the average energy at the treatment field edge to be lower relative to the center of the beam. These particles have a higher LET, making them more biologically damaging. With a single beam (large field-size (FS)), the amount of these highly damaging electrons is low relative to within the treatment beam. However, when multiple beam angles and smaller FS are used (IMRT/VMAT), the relative contribution of scattered radiation increases and biological consequences may vary. The purpose of this study was to evaluate the theoretical impact of increased scattered radiation in single and composite field beams. Monte Carlo Geant4.10.3 was used to score the electron energy spectra at different depths in water with a 6 MV photon beam incident. The energy spectra were then used to calculate the maximum RBE, RBE M . Beams examined were phase-spaces of a Varian Clinac 600C 6 MV linac (10 × 10 cm 2 beam, 1 × 1 cm 2 beam), and a composite 10 × 10 cm 2 beam. The composite 10 × 10 cm 2 treatment field (simple IMRT) was created by summating one hundred 1 × 1 cm 2 beams to form a relatively uniform 10 × 10 cm 2 field. For smaller FS (1.5 cm depth), an increase in RBE M was seen 5.2 cm outside the beam (17%). The 10 × 10 cm 2 beam showed an increase of 14%, 9.2 cm away from beam’s edge (1.5 cm depth). The composite 10 × 10 cm 2 beam exhibited similar RBE M enhancement to the 10 × 10 cm 2 phase-space, however, the region of increased damage occurred closer to the beam (5.6 cm away). The results indicate that although the region inside the primary beam is not affected, the contribution of damaging particles happens much closer to the beam’s edge in the composite field case relative to an open field. This may have potential implications regarding the effective dose to organs at risk during radiotherapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".