SU‐D‐BRA‐03: Gantry Angle Sensitivity for IMRT Plan Delivery
Bibliographic record
Abstract
Purpose: Intensity Modulated Radiation Therapy (IMRT) is currently the modality of choice for optimum dose conformability for head and neck (H&N) patients. We have quantified the sensitivity of H&N treatment delivery to errors in the gantry angle (GA) using EPIDose[1], an IMRT QA tool used in our centre. Methods: EPIDose was modified to read in the planned GA for each field, add an ‘error’ term, and continue with analysis. Systematic errors (shifting all fieldsˈ GA together by same value) and a subset of random errors (using different values for each field) up to 5 degrees were studied. Analysis consisted of recreating the dose based on the captured images (including the modified GAs), and creating Chi distributions (using 3% dose‐difference, 3mm distance‐to‐agreement parameters) between planned and reconstructed doses for two dose ranges: dose above 80% of prescription dose, for primary tumour volume, and the region with 40% to 80% of prescription dose, focusing on organ‐at‐risk. For the planned and reconstructed dose to be considered clinically equivalent at least 90% of the data‐points being compared in either region needed to have a Chi value between −1 and +1. Results: Based on 20 plans, the average systematic error that can be introduced into H&N IMRT plans without having the planned and reconstructed dose considered clinically different, via the metric discussed above, is 2.4±0.5 degrees. Random error affected 13 of these plans, with the average error being 4.4±0.8 degrees. Conclusion: During delivery of H&N treatments, discrepancies in the GA less than approximately 1 degree (3 standard deviations from average systematic error) are not flagged as clinically relevant by our QA procedure, suggesting no accuracy impact to IMRT plan delivery. Fortunately, this is greater than 0.5 degrees standard tolerance set by CAPCA (Canadian Association of Provincial Cancer Agencies). Medical Physics 33 (2006) 3369‐3382 W.Ansbacher
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".