Depth Dose Enhancement on Flattening-Filter-Free Photon Beam: A Monte Carlo Study in Nanoparticle-Enhanced Radiotherapy
Bibliographic record
Abstract
The aim of this study is to investigate the variations of depth dose enhancement (DDE) on different nanoparticle (NP) variables, when using the flattening-filter-free (FFF) photon beam in nanoparticle-enhanced radiotherapy. Monte Carlo simulation under a macroscopic approach was used to determine the DDE ratio (DDER) with variables of NP material (gold (Au) and iron (III) oxide (Fe2O3)), NP concentration (3–40 mg/mL) and photon beam (10 MV flattening-filter (FF) and 10 MV FFF). It is found that Au NPs had a higher DDER than Fe2O3 NPs, when the depths were shallower than 6 and 8 cm for the 10 MV FF and 10 MV FFF photon beams, respectively. However, in a deeper depth range of 10–20 cm, DDER for the Au NPs was lower than Fe2O3 NPs mainly due to the beam attenuation and photon energy distribution. It is concluded that DDER for the Au NPs and Fe2O3 NPs decreased with an increase of depth in the range of 10–20 cm, with rate of decrease depending on the NP material, NP concentration and the use of FF in the photon beam.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".