SU-E-T-120: Measurement of Time Delays in Gated Radiotherapy for Realistic Breath Motions
Bibliographic record
Abstract
Purpose: The accuracy of treatment delivery in gated radiotherapy depends on time delays between target entry into the gated region and beam-on, as well as target exit from the gated region and beam-off. This study measures time delays, extending past work with simple sinusoidal motion to more realistic breath motions. Methods: The setup consisted of two platforms moving synchronously, programmed with realistic breathing motion. The vertical platform supported an infrared marker block, tracked by the Varian Truebeam Real-time Position Management system. The horizontal platform supported an x-ray sensitive film with a copper sheet for build-up. A stationary cone mounted above the film defined a spot, translated into streaks by the moving platform. These film streaks were measured to determine the treatment-beam delivery time, based on the speed of the platform. Time delays were determined from differences between the duration of the gating window and treatment-beam delivery time. To discriminate beam-on and beam-off time delays, either the start or the end of the gating window coincided with a stable point of motion. Time delays were measured for different beam energies and motion patterns. Results: At 6MV beam energy, beam-on time delay was significantly longer (p=0.01) for realistic (mean±SEM of 172±8 ms) than for sinusoidal (mean±SEM of 133±3 ms) motion and beam-off time delay was significantly longer (p=0.05) for realistic (mean±SEM of 83±6 ms) than for sinusoidal (mean±SEM of 64±4 ms) motion. 15 MV results were consistent for beam-on and beam-off delays. The observed late time delays can Results: in treatment inefficiency (beam-on delays) or, more importantly, to geographical miss (beam-off delays). Conclusion: The shape of breath motions may be a significant factor determining the time delay. These preliminary findings suggest that the use of sinusoidal motion may underestimate time delays. Further work is needed to determine if sinusoidal motion is sufficient.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".