A Monte Carlo tool for evaluating VMAT and DIMRT treatment deliveries including planar detectors
Bibliographic record
Abstract
The aim of this work is to describe and validate a new general research tool that performs Monte Carlo (MC) simulations for volumetric modulated arc therapy (VMAT) and dynamic intensity modulated radiation therapy (DIMRT), simultaneously tracking dose deposition in both the patient CT geometry and an arbitrary planar detector system. The tool is generalized to handle either entrance or exit detectors and provides the simulated dose for the individual control-points of the time-dependent VMAT and DIMRT deliveries. The MC simulation tool was developed with the EGSnrc radiation transport. For the individual control point simulation, we rotate the patient/phantom volume only (i.e. independent of the gantry and planar detector geometries) using the gantry angle in the treatment planning system (TPS) DICOM RP file such that each control point has its own unique phantom file. After MC simulation, we obtained the total dose to the phantom by summing dose contributions for all control points. Scored dose to the sensitive layer of the planar detector is available for each control point. To validate the tool, three clinical treatment plans were used including VMAT plans for a prostate case and a head-and-neck case, and a DIMRT plan for a head-and-neck case. An electronic portal imaging device operated in 'movie' mode was used with the VMAT plans delivered to cylindrical and anthropomorphic phantoms to validate the code using an exit detector. The DIMRT plan was delivered to a novel transmission detector, to validate the code using an entrance detector. The total MC 3D absolute doses in patient/phantom were compared with the TPS doses, while 2D MC doses were compared with planar detector doses for all individual control points, using the gamma evaluation test with 3%/3 mm criteria. The MC 3D absolute doses demonstrated excellent agreement with the TPS doses for all the tested plans, with about 95% of voxels having γ <1 for the plans. For planar dosimetry image comparisons, we defined an acceptable pass rate of >90% of percentage pixels with γ <1. We found that over 90% of control points in the plans passed this criterion. In general, our results indicate that the simulation tool is suitable for accurately calculating both patient/phantom doses and planar doses for VMAT dose delivery. The tool will be valuable to check performance and advance the development of in vivo planar detectors for use in measurement-based VMAT dose verification. In addition, the tool can be useful as an independent research tool for VMAT commissioning of the TPS and delivery system.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.010 | 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".