SU‐E‐T‐464: Implementation and Validation of 4D Acuros XB Dose Calculations
Bibliographic record
Abstract
Purpose: In this abstract we implement and validate a 4D VMAT Acuros XB dose calculation using Gafchromic film. Special attention is paid to the physical material assignment in the CT dataset and to reported dose to water and dose to medium. Methods: A QUASAR phantom with a 3 cm sinusoidal tumor motion and 5 second period was scanned using 4D computed tomography. A CT was also obtained of the static QUASAR phantom with the tumor at the central position. A VMAT plan was created on the average CT dataset and was delivered on a Varian TrueBeam linear accelerator. The trajectory log file from this treatment was acquired and used to create 10 VMAT subplans (one for each portion of the breathing cycle). Motion for each subplan was simulated by moving the beam isocentre in the superior/inferior direction in the Treatment Planning System on the static CT scan. The 10 plans were calculated (both dose to medium and dose to water) and summed for 1) the original HU values from the static CT scan and 2) the correct physical material assignment in the CT dataset. To acquire a breathing phase synchronized film measurements the trajectory log was used to create a VMAT delivery plan which includes dynamic couch motion using the Developer Mode. Three different treatment start phases were investigated (mid inhalation, full inhalation and full exhalation). Results: For each scenario the coronal dose distributions were measured using Gafchromic film and compared to the corresponding calculation with Film QA Pro Software using a Gamma test with a 3%/3mm distance to agreement criteria. Good agreement was found between calculation and measurement. No statistically significant difference in agreement was found between calculations to original HU values vs calculations to over‐written (material‐assigned) HU values. Conclusion: The investigated 4D dose calculation method agrees well with measurement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".