SU‐E‐T‐262: Quality Assurance on Field Size Shaped by Iris Collimator of the CyberKnife
Bibliographic record
Abstract
Purpose: To develop a simple method to measure the x‐ray beam field size shaped by the iris collimator of the CyberKnife. Methods: The profile of the 12‐sided polygonal beam shaped by iris collimator of the Cyberknife (Accuray) was obtained using a single array beam profiler (Sun Nuclear, Model: 1170, spatial resolution = 5 mm). To improve the resolution of the profile, we moved the x‐ray beam along the array of diodes on the profiler and obtained beam profiles for every 1 mm. The beam profiles were then shifted according to their positions relative to the starting position and created an integrated beam profile. Since there are 6 different axes on the 12‐sided polygonal beam, we can obtain the beam profiles on the other five axes in a similar fashion, by simply rotating the head of the CyberKnife. This method was also examined by replacing the beam profiler with an IˈmRT MatriXX (IBA Dosimetry). Results: By using the beam profiler, we measured the field sizes of different iris collimator setting (from 10 to 60 mm). We found that the measured field sizes are within +/− 0.4 mm compared to the expected field size. Also, we found that the variation of measured field sizes is within +/− 0.2 mm between measurements. By using the IˈmRT MatriXX, we found that the uncertainty of the measured field size now increases to +/− 1 mm. Conclusions: The method of using the beam profiler is a feasible and easy way to check the consistency of the field size shaped by the iris collimator, and reduces the reliance on using radiochromic film and water phantom. We are also investigating the feasibility of using dose area product (DAP) measured by parallel plate chamber to verify field sizes in daily QA.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".