WE-AB-303-10: The Use of On-Board KV Imaging During Respiratory-Gated VMAT Delivery to Determine the Correlation and Phase Shift Between External Marker Motion and Internal Tumour Motion
Bibliographic record
Abstract
Purpose: To determine the correlation between internal tumor motion and external surrogate motion and any potential phase shifts during respiratory-gated VMAT delivery using on-board kV imaging. Methods: A respiratory motion phantom was used to trace the motion of an internal target, embedded with a 3 cm moving target, and an external surrogate. On-board kV projections were acquired at 11 frames per second during VMAT delivery on a TrueBeam v.1.6 (Varian Medical Systems, Palo Alto, CA) operating in developer mode. Full motion encompassed treatment delivery using sinusoidal motion with 4 second period and 2 cm peak-to-peak amplitude, and real-patient breathing (RPB) motion was programmed to the phantom. Respiratory-gated treatment deliveries (30–60% gating window) on five additional RPB waveforms were programmed to investigate correlation within the gating window. To investigate the capability of during treatment kV imaging to detect phase shifts during gated delivery, a second phantom with independent motion was used. Eight controlled phase shifts in intervals of 0.4 seconds were added to the sinusoidal motion. For each phase shift, the Pearson linear correlation coefficient statistical test was performed for each set of respiratory traces. The phase shift was calculated by shifting the external trace, in time, until maximum correlation was obtained. Results: A strong internal and external correlation was obtained for both the free-breathing (sinusoidal R2=0.993 and RPB R2=0.990) and respiratory-gated cases (range from R2=0.986–0.996). There was no significant difference between the programmed shift and that acquired using on-board kV imaging (p=0.899, R-squared = 0.997). Conclusion: During treatment kV imaging has the capability to verify intrafractional anatomical position. It can be accurately used as a tool to quantify internal and external correlation, and determine phase shifts within the gating window, and ultimately, the accuracy of respiratory-gating treatment delivery.
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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".