Quality assurance for mixed electron–photon beam radiation therapy using treatment log files and MapCHECK
Bibliographic record
Abstract
BACKGROUND: Mixed photon-electron beam radiotherapy (MBRT) is a technique that combines the use of both photons and electrons in one single treatment plan to exploit their advantageous and complimentary characteristics. Compared to other photon treatment modalities, it has been shown that the MBRT technique contributes to better target coverage and organ-at-risk (OAR) sparing. However, the use of combined photons and electrons in one delivery makes the technique more complex and a well-established quality assurance (QA) protocol for MBRT is essential. PURPOSE: To investigate the feasibility of using MapCHECK and log file-dose reconstruction for MBRT plan verification and to recommend a patient-specific quality assurance (PSQA) protocol for MBRT. METHODS: MBRT plans were robustly optimized for five soft-tissue sarcoma (STS) patients. Each plan comprised step-and-shoot deliveries of a six MV photon beam and a combination of five electron beam energies at an SAD of 100 cm. The plans were delivered to the MapCHECK device with collapsed gantry angle and the 2D dose distributions at the detector depth were measured. To simulate the expected dose distribution delivered to the MapCHECK, a MapCHECK computational phantom was modeled in EGSnrc based on vendor-supplied blueprint information. The dose to the detectors in the model was scored using the DOSXYZnrc user code. The agreement between the measured and the simulated dose distribution was evaluated using 2D gamma analysis with a gamma criterion of 3%/2 mm and a low dose threshold of 10%. One of the plans was selected and delivered with a rotating gantry angle for trajectory log file collection. To evaluate the potential interlinac and intralinac differences, the plan was delivered repeatedly on three linacs. From the collected log files, delivery parameters were retrieved to recalculate the 3D dose distributions in the patient's anatomy with DOSXYZnrc. The recalculated mean dose to the clinical target volume (CTV) and OARs from all deliveries were computed and compared with the planned dose in terms of percentage difference. To validate the accuracy of log file-based QA, the log file-recalculated dose was also compared with film measurement. RESULTS: The agreement of the total dose distribution between the MapCHECK measurement and simulation showed gamma passing rates of above 97% for all five MBRT plans. In the log file-dose recalculation, the difference between the recalculated and the planned dose to the CTV and OARs was below 1% for all deliveries. No significant inter- or intralinac differences were observed. The log file-dose had a gamma passing rate of 98.6% compared to film measurement. CONCLUSION: Both the MapCHECK measurements and log file-dose recalculations showed excellent agreement with the expected dose distribution. This study demonstrates the potential of using MapCHECK and log files as MBRT QA tools.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".