Transperitoneal Laparoscopic Prostatectomy Does Not Increase Small Bowel Within the Target Volume for Postoperative Radiotherapy
Bibliographic record
Abstract
PURPOSE: Laparoscopic or robot assisted laparoscopic radical prostatectomy is often performed via a transperitoneal approach for prostate cancer, in contrast to open retropubic radical prostatectomy. Theoretically transgressing the peritoneum may introduce small bowel loops into the pelvis, increasing the risk of small bowel injury with adjuvant radiotherapy. We compared the incidence of small bowel within the planning target volume for radiotherapy to the prostate bed in patients who underwent open retropubic and laparoscopic radical prostatectomy. MATERIALS AND METHODS: A total of 25 patients recently treated with laparoscopic radical prostatectomy prospectively provided consent to undergo radiotherapy planning computerized tomography simulation to assess the incidence of small bowel within the prostate bed planning target volume. These studies were compared to radiotherapy planning computerized tomography in 50 patients who underwent open retropubic radical prostatectomy and received adjuvant or salvage radiotherapy for prostate cancer. For all computerized tomography images 1 blinded observer delineated the distal small bowel loops and 1 blinded radiation oncologist delineated the superior extent of clinical and planning target volumes. RESULTS: The overlap rate between small bowel and planning target volume was 16% in the laparoscopic and open radical prostatectomy groups (p = 0.579). CONCLUSIONS: There is no difference between transperitoneal laparoscopic and open retropubic radical prostatectomy in the incidence of small bowel within the planning target volume for radiotherapy to the prostate bed. Thus, patients who undergo transperitoneal laparoscopic radical prostatectomy do not face a higher risk of toxicity or compromise due to adjuvant or salvage radiotherapy should they require it.
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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 | 0.000 | 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) | 0.002 | 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".