Operational assessment of tattooless breast radiotherapy using AlignRT surface guidance
Bibliographic record
Abstract
Background and purpose: Surface guided radiation therapy (SGRT) is a new approach for patient setup that can replace tattoo-based positioning. The permanent body markings that come with this long-standing standard of care can have a lasting negative emotional impact on cancer survivors. This study evaluates surface guidance as an alternative positioning modality, comparing speed, accuracy, and cost of the two techniques. Methods: Setup time and positional accuracy prior to radiographic localization for patients receiving radiation therapy for breast cancer were compared between two linear accelerators, one with and one without surface guidance technology. A Wilcoxon rank sum test was used to determine statistically significant differences in setup time and positional shifts. Cost projections per fraction and per patient for both modalities were conducted. Results: SGRT positional accuracy and setup time were equivalent to or better than tattoo-based setup. SGRT setup was faster for all photon treatments by 11 s. Deep inspiration breath hold setup times were equivalent for both positioning modalities, but SGRT was faster by 23 s for free breathing setups. There were no statistically significant differences in the magnitude of positional shifts on pre-treatment imaging. SGRT costs are broken down into item costs and staffing costs, with final estimates dependent on a center's capacity for treatments per day. Conclusions: Surface guided patient positioning for breast radiotherapy is fiscally feasible and non-inferior to permanent tattoos in terms of set up time and accuracy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".