Evaluation of dosimetric and spatial accuracy of a virtual cone technique for radiosurgery using linac‐integrated CBCT‐based polymer gel dosimetry
Bibliographic record
Abstract
PURPOSE: This study evaluates the dosimetric and geometric precision of a virtual cone technique using CBCT-based polymer gel dosimetry, enabling radiation delivery, and imaging readout within an identical spatial coordinate system. METHODS: We created a C# script for a virtual cone technique that generates a treatment plan with 10 gantry arcs at 0°, 36°, 72°, 288°, and 324° couch angles, with 2 arcs per couch angle using 45° and 135° collimator angles. Two verification plans using Eclipse v15.6 (AcurosXB) were created with 20 Gy at the maximum dose for: (1) a cylindrical gel, with an additional calibration region; (2) a 3D printed anthropomorphic skull phantom with a gel insert. The 50% isodose (10 Gy) width through the central axis of the axial and sagittal planes (SPs) were measured for the gel experiment. The distance between the centers-of-masses of the 10 Gy isodose region of the plan and the gel (skull phantom) were calculated for an end-to-end spatial accuracy test. RESULTS: 0.01 mm for axial (anterior-posterior), axial (left-right), sagittal (superior-inferior) respectively, which were slightly narrower than Eclipse (1.29 mm maximum difference in the SP due to CBCT slice thickness). The center-of-mass distance was 0.66 mm for the gel experiment, and 0.94 mm for complete end-to-end testing with the anthropomorphic phantom, including CBCT setup (kV-MV isocenter uncertainty). CONCLUSION: The 50% isodose width of the gel measurement was 5.15 mm (mean), which was tighter than our Eclipse v15.6 beam model. The end-to-end spatial accuracy test, only achievable with gel dosimetry using CBCT readout, resulted in sub-millimeter accuracy. This study demonstrates the value of gel dosimetry in verifying the dosimetric and spatial accuracy of this high precision, stereotactic technique.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".