MO‐FF‐A2‐02: A Technique to Determine the Integral Depth Dose of Proton Pencil Beam Spots
Bibliographic record
Abstract
Purpose: To develop and validate a technique to determine the integral depth dose (IDD) from the measured profiles and peak doses of proton pencil beam spots (PPBS). Methods and Materials: The IDDs of 72.5, 146.4 and 221.8 MeV energy PPBS were determined by area integration of their planar dose distributions at different depths. The transverse lateral profiles of the PPBS at selected depths in water were measured by using small volume ion chambers using a beam scanning system. The peak spot dose, D0, was determined by different experimental methods using ion chamber and diode. The extent of anisotropy in spot dose distribution was determined by comparing profiles from film dosimetry along different angles with the principal axes. The IDD was calculated by integrating the measured lateral profiles and the corresponding D0. The IDDs were also measured using PTW Bragg peak chamber (BPC), designed for this purpose, and were compared with the calculated values. Results: The spot dose distributions were found to be isotropic. The magnitude of difference in the calculated and BPC measured IDDs was found to be as much as 15.7% for the lower energy spots, and decreased with increase in beam energy. This difference is mainly due to the size limitation of the BPC. The contribution from the tail region of profiles increases with decrease in beam energy, and the BPC chamber size is not large enough to account for the contribution of these long tails. Correction factors for the BPC size effect on the measured IDD were determined from our calculation. Conclusion: The technique of area integration of profile is found to be useful for determining the IDD values of PPBS, which are important input parameters for beam modeling in the treatment planning system, with reasonable accuracy. Conflict of Interest Statement: Research sponsored by Varian Medical Systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".