A customizable, open-source Winston-Lutz system for multi-target, single isocentre radiotherapy
Bibliographic record
Abstract
Abstract Objective . To present and share an open-source system (phantom and software) for verifying the targeting accuracy of linac-based, single-isocenter, multi-target radiotherapy. This quality assurance test extends the traditional Winston-Lutz test, which considers a single target located at isocentre. Approach . Plans for a 3D-printed phantom are provided, which can be customized to accommodate various target (BB) positions. Given BB positions and gantry/collimator/couch combinations, the software generates multi-leaf collimator positions to facilitate multi-target Winston-Lutz (MTWL) plan creation. The software determines deviations between detected and expected BB positions on MV images resulting from MTWL plan delivery. BBs are located using a Hough circle detection algorithm, which is modified to favour the detection of circles: (1) having a reasonable size, (2) that are contained within the radiation field, and (3) having reasonable pixel intensities. Validation was performed in two ways: (1) using synthetic data with zero targeting errors and (2) by measuring real linac targeting errors and comparing against results obtained using a commercial system. Main results . Validation using the synthetic data yielded a mean (maximum) absolute discrepancy of 0.11 mm (0.21 mm), which is comparable to the synthetic phantom resolution (0.2 mm). The mean (maximum) absolute discrepancy compared to the commercial system is 0.13 mm (0.43 mm). These values are similar to results obtained with repeated deliveries of the same MTWL plan with the same phantom setup. Both validation tests yield reasonable results and are therefore considered successful. The MTWL test was performed independently by three physicists on two linacs to investigate repeatability, resulting in a mean (maximum) absolute discrepancy of 0.14 mm (0.51 mm) among the various attempts. Significance . Successful completion of this quality assurance test, using our customizable and open-source system, provides confidence that multi-target, single isocentre radiotherapy treatments can be delivered with sufficient geometric accuracy according to the chosen tolerance level.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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".