Evaluation of treatment planning system monitor unit calculations for three intensity modulated radiotherapy delivery techniques
Bibliographic record
Abstract
Background: We have validated the monitor unit calculations from a commercially available treatment planning system (TPS) for three intensity modulated radiotherapy (IMRT) planning techniques for tangential breast irradiation by using ionization chamber measurements. Materials and Methods: Treatment plans were generated for forty-two breast patients by a forward planned field in field technique, electronic tissue compensation (ETC), and an inverse planned sliding window technique. We also performed a reproducibility of delivery and dose linearity analysis for each technique. The treatments were delivered to a phantom using a Varian CL21EX linear accelerator. A 2571 0.6 cm 3 Farmer type ionization chamber and Farmer 2570/1 electrometer from NE Technology was used to measure output of the linear accelerator and the dose at predefined point in the verification plan. Results: The agreement between the measured and calculated dose was -0.87% ± 0.54% for field in field technique, -0.74% ± 0.23% for electronic tissue compensators, and -1.26% ± 0.48% for the inverse planning technique and. In terms of reproducibility the mean deviation was -1.10% ± 0.44% for the field in field technique, -0.38% ± 0.42% for electronic tissue compensators, -1.04% ± 0.42% for inverse planning technique. Dose linearity experiments showed no significant variations for clinical situations but a breakdown was observed in relative dose for very low monitor units. Conclusion: We have found that the monitor unit calculations for all three planning techniques are correct to the order of 1%, and that the plans can be delivered in a reproducible and accurate manner. Iran. J. Radiat. Res., 2011; 9(3): 145150
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".