SU‐E‐J‐21: Setup Variability of Colorectal Cancer Patients Treated in the Prone Position and Dosimetric Comparison with the Supine Position
Bibliographic record
Abstract
Purpose: Many cancer centers treat colorectal patients in the prone position on a belly board to minimize dose to the small bowel. That may potentially Result in patient setup instability with corresponding impact on dose delivery accuracy for highly conformal techniques such as IMRT/VMAT. Two aims of this work are 1) to investigate setup accuracy of rectum patients treated in the prone position on a belly board using CBCT and 2) to evaluate dosimetric impact on bladder and small bowel of treating rectum patients in supine vs. prone position. Methods: For the setup accuracy study, 10 patients were selected. Weekly CBCTs were acquired and matched to bone. The CBCT‐determined shifts were recorded. For the dosimetric study, 7 prone‐setup patients and 7 supine‐setup patients were randomly selected from our clinical database. Various clinically relevant dose volume histogram values were recorded for the small bowel and bladder. Results: The CBCT‐determined rotational shifts had a wide variation. For the dataset acquired at the time of this writing, the ranges of rotational setup errors for pitch, roll, and yaw were [−3.6° 4.7°], [−4.3° 3.2°], and [−1.4° 1.4°]. For the dosimetric study: the small bowel V(45Gy) and mean dose for the prone position was 5.6±12.1% and 18.4±6.2Gy (ranges indicate standard deviations); for the supine position the corresponding dose values were 12.9±15.8% and 24.7±8.8Gy. For the bladder, the V(30Gy) and mean dose for prone position were 68.7±12.7% and 38.4±3.3Gy; for supine position these dose values were 77.1±13.7% and 40.7±3.1Gy. Conclusion: There is evidence of significant rotational instability in the prone position. The OAR dosimetry study indicates that there are some patients that may still benefit from the prone position, though many patients can be safely treated supine.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".