MO‐G‐213AB‐03: Simulations of Real‐Time Geometric and Dosimetic Verification System Using EPID
Bibliographic record
Abstract
Purpose: To demonstrate a new method for real‐time geometric and dosimetric verification of IMRT and VMAT using synchronization between predicted and measured EPID images. Methods: Predicted EPID images were calculated using a comprehensive physics‐based model. Each predicted image represents the integrated signal expected from the delivery between control points. The measured images are acquired in cine mode and compared to the set of predicted images in real‐time. The system performs geometric verification prior to dosimetric verification. When the measured image is acquired, the algorithm automatically detects the MLC leaf positions. A comparison between the leaf positions of the measured image and control points in the MLC file is made using the cosine similarity technique. The similarity index(SI) provides geometric MLC verification and synchronization between the measured and predicted images, as a uniform dose‐rate cannot be assumed for IMRT or VMAT deliveries. The SI threshold was based on a series of experiments including 21 dynamic‐IMRT fields defining pass/fail boundary(5 brain, 8 H&N, and 8 prostate cases).If geometric verification is successful, dosimetic verification is performed with the Gamma comparison(3%,3mm).The system reports the verification Result in real‐time. Results: The system was simulated by MATLAB/SIMULINK and detected geometric and dosimetric errors during delivery. Both artificially introduced errors and clinical data were used for testing and analysis of the system performance. For a tested prostate field, the cumulative dose comparisons showed the minimum and maximum number of points with Gamma index<1 as 93.5% and 98.5%, respectively. For individual dose comparisons on the same field, the values were 87% and 97%, respectively. Conclusion: This method includes automatic MLC leaf positioning, synchronization, and dosimetric verification. The pass/fail boundary of geometry was calculated based on the experiments. This system is a useful approach to detect unexpected possible errors occurring in the clinical setting and to prevent patient overdoses during radiotherapy especially in complex deliveries such as arc‐IMRT.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".