The effect of prone and supine treatment positions for the pre-operative treatment of rectal cancer on organ-at-risk sparing and setup reproducibility using volumetric modulated arc therapy
Bibliographic record
Abstract
To compare organ-at-risk doses and setup reproducibility using the prone and supine orientations in volumetric modulated arc therapy (VMAT) for rectal cancer. Seventeen consecutive rectal cancer patients undergoing preoperative radiation were selected and setup in either the prone ( N = 8) or supine ( N = 9) position. All patients were treated using posteriorly-applied VMAT. Bladder and small bowel dose and cone beam CT (CBCT) reproducibility metrics were retrospectively collected. Dose metrics for bladder and small bowel did not show significant differences between the prone and supine orientations. The prone data had a trend for smaller irradiated volumes than supine for the small bowel at lower doses—V20 (prone: 135 ± 99 cm 3 ; supine: 201 ± 162 cm 3 ) and V30 (prone: 78 ± 71 cm 3 ; supine: 105 ± 106 cm 3 ). At higher doses, the trend reversed as exemplified by the small bowel V50.4 (prone: 20 ± 28 cm 3 ; supine: 10 ± 14 cm 3 ). CBCT data showed that rotational errors in pitch and roll were significantly larger for the prone vs. supine orientation (pitch: 2.0° ± 1.3° vs. 0.8° ± 1.1° p < 0.001; roll: 1.0° ± 0.9° vs. 0.3° ± 0.5°, p < 0.001). Bladder and small bowel doses were not significantly different when comparing VMAT plans developed for the prone and supine orientations. The supine orientation demonstrated improved setup reproducibility.
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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 | 0.001 | 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 | 0.000 | 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 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".