Sci‐AM2 Sat ‐ 06: IMRT prostate planning‐determination of the minimum MU/segment
Bibliographic record
Abstract
For step and shoot IMRT, the combination of high dose rate, multiple beam segments and low dose per segment can lead to significant differences between the planned and delivered dose to the patient. This problem, known as an “overshoot” effect, is the result of current dose servo limitations and is demonstrated by over‐ and under‐dose in the first and the last segment respectively. Segment dose inaccuracy in the range of 10 to 60% of the both segments for 1 monitor unit (MU) per segment irradiated with dose rate (DR) of 100 to 600 MU/min was measured. The object of this study was to find a method for segment dose correction when small MU and high DR are used, and specify the prostate IMRT planning limits for MU/segment and the DR. The reported results were obtained using Pinnacle3‐V6 and Varian Clinac 2100 EX linear accelerator equipped with a 120‐leaf millennium MLC. The methodology for correcting dose employs small field segment dose ratio. The segment dose error after correction was measured to be less than 5 % for all dose rates. For prostate step and shoot IMRT a low limit of 1 MU per segment and DR with upper limit of 600 MU/min can be used. The results of this work relate to the agreement between planned and delivered doses of the prostate IMRT.
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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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".