Long‐term performance monitoring of a‐Si 1200 electronic portal imaging device for dosimetric applications
Bibliographic record
Abstract
PURPOSE: Recently, dosimetri applications of the electronic portal imaging device (EPID) in radiotherapy have gained popularity. Confidence in the robust and reliable dosimetric performance of EPID detectors is essential for their clinical use. This study aimed to evaluate the dosimetric performance of the a-Si 1200 EPID and assess the long-term stability of its response. METHODS: Weekly measurements were performed on two clinically used TrueBeam linear accelerators (linacs) equipped with a-Si 1200 EPID detectors over a 2-year period. They included dark and flood calibration fields, and EPID response to an open field corrected for the long-term machine output drift measured with the secondary absolute dosimeters: an ion chamber and an ion chamber array. All measurements were performed using five photon beam energies and two imaging modes: continuous and dosimetry. The measurements were analyzed for constancy and the presence of long-term trends. Comparisons were made between the two linacs for each beam energy. Pixel sensitivity matrices (PSM) were determined semi-annually and analyzed for long-term constancy for both treatment machines. RESULTS: The long-term variation of the dark and flood field signals, integrated across the EPID plane, over the entire observation period did not exceed 0.17% and 0.79%, respectively. The output-corrected EPID response showed long-term variation from 0.28% to 0.36%, depending on beam energy, while the short-term variation was 0.04%-0.07% for EPID and 0.02%-0.06% for secondary dosimeters. The long-term variation of secondary dosimeters was 0.2%-0.3%. PSMs were found to be stable to within 1% for 97.8% of pixels and 2% for 100% of pixels. CONCLUSION: Techniques to monitor and assess the long-term performance of the a-Si 1200 EPID as a dosimeter were developed and implemented using two TrueBeam linacs. The long-term variation of the EPID response was within clinical tolerance indicated in AAPM TG-142 report, and the detector was shown to be stable and reproducible for routine clinical dosimetry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".