Sci‐Fri PM: Planning‐03: Fundamental understanding of the inter‐relation of arc range, angular dose rate and MLC leaf position optimization of Intensity Modulated Arc Therapy for a concave target
Bibliographic record
Abstract
Intensity Modulated Arc Therapy (IMAT) is a rotational variant of Intensity Modulated Radiation Therapy (IMRT) that can be implemented with or without angular dose rate optimization. The purpose of this study is to determine the inter-relationship among arc range, Multi-Leaf Collimator (MLC) leaf positions and angular dose rate optimizations for IMAT delivery of a concave target. A concave planning target volume (PTV) with central cylindrical organ at risk (OAR) was used in dissecting the inter-relationships. Plans with full and limited arc range were generated using leaf position optimization (LPO) alone, angular dose rate optimization (ADRO) alone or LPO followed by ADRO. Two initial IMAT arcs were conformal avoidance arcs created with 5° angular increments where MLC leaf positions were determined from the beams eye view to irradiate the PTV but avoid the OAR. The objective function value (evaluating dose to PTV and OAR), a conformity index, dose homogeneity index, mean dose to OAR and normal tissues were computed and used to evaluate the treatment plans. Dose rate variations and MLC leaf movements as a function of gantry angle were examined in this approach. The results demonstrate that LPO followed by ADRO provided the lowest objective function values, best conformity and dose homogeneity indices, and third in mean dose to OAR and normal tissues for the complete arc range. Future work will address different strategies for simultaneously optimizing both the MLC leaf positions and the variable angular dose rate for IMAT delivery and compare single and multiple arc plans.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".