An integral quality monitoring system for real‐time verification of intensity modulated radiation therapy
Bibliographic record
Abstract
PURPOSE: To develop an independent and on-line beam monitoring system, which can validate the accuracy of segment-by-segment energy fluence delivery for each treatment field. The system is also intended to be utilized for pretreatment dosimetric quality assurance of intensity modulated radiation therapy (IMRT), on-line image-guided adaptive radiation therapy, and volumetric modulated arc therapy. METHODS: The system, referred to as the integral quality monitor (IQM), utilizes an area integrating energy fluence monitoring sensor (AIMS) positioned between the final beam shaping device [i.e., multileaf collimator (MLC)] and the patient. The prototype AIMS consists of a novel spatially sensitive large area ionization chamber with a gradient along the direction of the MLC motion. The signal from the AIMS provides a simple output for each beam segment, which is compared in real time to the expected value. The prototype ionization chamber, with a physical area of 22 x 22 cm2, has been constructed out of aluminum with the electrode separations varying linearly from 2 to 20 mm. A calculation method has been developed to predict AIMS signals based on an elementwise integration technique, which takes into account various predetermined factors, including the spatial response function of the chamber, MLC characteristics, beam transmission through the secondary jaws, and field size factors. The influence of the ionization chamber on the beam has been evaluated in terms of transmission, surface dose, beam profiles, and depth dose. The sensitivity of the system was tested by introducing small deviations in leaf positions. A small set of IMRT fields for prostate and head and neck plans was used to evaluate the system. The ionization chamber and the data acquisition software systems were interfaced to two different types of linear accelerators: Elekta Synergy and Varian iX. RESULTS: For a 10 x 10 cm2 field, the chamber attenuates the beam intensity by 7% and 5% for 6 and 18 MV beams, respectively, without significantly changing the depth dose, surface dose, and dose profile characteristics. An MLC bank calibration error of 1 mm causes the IQM signal of a 3 x 3 cm2 aperture to change by 3%. A positioning error in a single 5 mm wide leaf by 3 mm in 3 X 3 cm2 aperture causes a signal difference of 2%. Initial results for prostate and head and neck IMRT fields show an average agreement between calculation and measurement to within 1%, with a maximum deviation for each of the smallest beam segments to within 5%. When the beam segments of a prostate IMRT field were shifted by 3 mm from their original position, along the direction of the MLC motion, the IQM signals varied, on average, by 2.5%. CONCLUSIONS: The prototype IQM system can validate the accuracy of beam delivery in real time by comparing precalculated and measured AIMS signals. The system is capable of capturing errors in MLC leaf calibration or malfunctions in the positioning of an individual leaf. The AIMS does not significantly alter the beam quality and therefore could be implemented without requiring recommissioning measurements.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".