SU‐F‐T‐679: Monte Carlo Simulation On Surface Dose in Preclinical Irradiation Using Monoenergetic Photon Beams
Bibliographic record
Abstract
Purpose: This study investigated the surface dose variation in preclinical irradiation using small animal, when monoenergetic photon beams with energy range from 50 keV to 1.25 MeV were used. Methods: Inhomogeneous, homogeneous and bone‐tissue homogeneous mouse phantom based on the same CT image set were used. The homogeneous and bone‐tissue homogeneous phantom were created with the relative electron density of all and only bone voxels of the mouse overridden to one, respectively. Monte Carlo simulation based on the EGSnrc‐based code was used to calculate the surface dose, when the phantoms were irradiated by a 360° photon arc with energies ranging from 50 keV to 1.25 MeV. The mean surface doses of the three phantoms were calculated. In addition, the surface doses from partial arcs, 45°–315°, 125°–225°, 45°–125° and 225°–315° covering the anterior, posterior, right lateral and left lateral region of the mouse were determined using different photon beam energies. Results: When the prescribed dose at the isocenter of the mouse was 2 Gy, the maximum mean surface doses, found at the 50‐keV photon beams, were 0.358 Gy, 0.363 Gy and 0.350 Gy for the inhomogeneous, homogeneous and bone‐tissue homogeneous mouse phantom, respectively. The mean surface dose of the mouse was found decreasing with an increase of the photon beam energy. For surface dose in different orientations, the lateral regions of the mouse were receiving lower dose than the anterior and posterior regions. This may be due to the increase of beam attenuation along the horizontal (left‐right) axis than the vertical (anterior‐posterior) in the mouse. Conclusion: It is concluded that consideration of phantom inhomogeneity in the dose calculation resulted in a lower mean surface dose of the mouse. The mean surface dose also decreased with an increase of photon beam energy in the kilovoltage range.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".