Implementation and experimental validation of a robust hybrid direct aperture optimization approach for mixed‐beam radiotherapy
Bibliographic record
Abstract
PURPOSE: The objectives of the work presented in this paper were to (1) implement a robust-optimization method for deliverable mixed-beam radiotherapy (MBRT) plans within a previously developed MBRT planning framework; (2) perform an experimental validation of the delivery of robust-optimized MBRT plans; and (3) compare PTV-based and robust-optimized MBRT plans in terms of target dose robustness and organs at risk (OAR) sparing for clinical head and neck and brain patient cases. METHODS: A robust-optimization method, which accounts for translational setup errors, was implemented within a previously developed treatment planning framework for MBRT. The framework uses a hybrid direct aperture optimization method combining column generation and simulated annealing. A robust plan was developed and then delivered to an anthropomorphic head phantom using the Developer Mode of a TrueBeam linac. Planar dose distributions were measured and compared to the planned dose. Robust-optimized and PTV-based plans were developed for three clinical patient cases consisting of two head and neck cases and one brain case. The plans were compared in terms of the robustness to 5 mm shifts of the target volume dose as well as in terms of OAR sparing. RESULTS: Using a gamma criterion of 3%/2 mm and a dose threshold of 10%, the agreement between film measurements and dose calculations was better than 97.7% for the total plan and better than 95.5% for the electron component of the plan. For the two head and neck patient cases, the average clinical target volume (CTV) dose homogeneity index (V95%-V107%) over all the considered setup error scenarios was on average 19% lower for the PTV-based plans and it had a larger standard deviation. The robust-optimized plans achieved, on average, a 20% reduction in the OAR doses compared to the PTV-based plans. For the brain patient case, the CTV dose homogeneity index was similar for the two plans, while the OAR doses were 22% lower, on average, for the robust-optimized plan. No clear trend in terms of electron contributions was found across the three patient cases, although robust-optimized plans tended toward higher electron beam energies. CONCLUSIONS: A framework for robust optimization of deliverable MBRT plans has been developed and validated. PTV-based MBRT were found to not be robust to setup errors, while the dose delivered by the robust-optimized plans were clinically acceptable for all considered error scenarios and had better OAR sparing. This study shows that the robust optimization is a promising alternative to conventional PTV margins for MBRT.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".