A retrospective comparative evaluation of rectal preparation strategies for patients undergoing stereotactic body radiotherapy for prostate cancer
Bibliographic record
Abstract
OBJECTIVES: We performed a retrospective study comparing 2 rectal preparation regimens, Polyethylene Glycol 3350 (PEG) and Fleet Enema (FE), in patients undergoing prostate stereotactic body radiation therapy (SBRT). METHODS: The study included 24 patients receiving prostate SBRT (40 Gy in 5 fractions), for a total of 120 treatment fractions. Patients received either FE (N = 73) or PEG (N = 47) for rectal preparation. Outcomes included: (1) treatment time, measured from the initial setup cone-beam CT (CBCT) to the post-treatment CBCT (including rectal-related interventions, excluding machine delays); (2) intra-fraction motion, defined as the displacement vector between verification and post-treatment CBCTs registered to fiducial markers; and (3) clinical acceptability, determined by blinded review of all setup CBCTs by 3 radiation therapists (RTs), who scored each scan as either "Acceptable" (proceed directly to treatment) or "Need Intervention." Regression analysis was used to compare regimens. RESULTS: Population-averaged median treatment times were 14 minutes (95% CI, 5.8-22.2) for PEG and 11 minutes (95% CI, 9.6-12.3) for FE, with greater time variability in PEG (P < .001). Intra-fraction motion did not differ significantly between regimens. All 3 RTs judged the setup CBCTs as clinically acceptable for treatment 47.7% of the time (95% CI, 31.6%-63.8%) for the PEG regimen and 74.4% of the time (95% CI, 61%-87.8%) for the FE regimen. CONCLUSIONS: Overall, the FE regimen showed greater consistency in all outcome measures. This suggests an operational advantage for using FE since it results in more consistent patient treatment times without negatively impacting treatment quality and precision. ADVANCES IN KNOWLEDGE: Daily FE improves the consistency of prostate SBRT treatment and enhances the clinical workflow by minimizing unplanned disruptions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".