Anatomical Fundamentals and Current Surgical Knowledge of Prostate Anatomy Related to Functional and Oncological Outcomes for Robotic-Assisted Radical Prostatectomy
Bibliographic record
Abstract
Context: Meticulous knowledge about the anatomy of the prostate and surrounding tissue represents a crucial and mandatory requirement during radical prostatectomy for reliable oncological and excellent replicable, functional outcomes. Since its introduction two decades ago, robotic-assisted laparoscopic radical prostatectomy (RALP) has evolved to become the predominant surgical approach in many industrialized countries. Objective: To provide and highlight currently available literature regarding prostate anatomy and to help in improving oncological and functional outcomes in RALP. Methods/Evidence Acquiring: PubMed database was searched using the following keywords: "robotic-assisted radical prostatectomy," "anatomy," "neurovascular bundle," "nerve," "periprostatic fascia," "pelvis," "sphincter," "urethra," "urinary incontinence," and "erectile dysfunction." Relevant articles and book chapters were critically reviewed and if eligible, they were included in this review. Results: New evidence in regards to prostatic anatomy and surgical approaches in RALP has been reported in recent years. Besides detailed anatomical studies investigating the meticulous structure of the fascial structures surrounding the prostate and neurovascular bundle preservation, debate about the optimal RALP approach is still ongoing, inspired by recent publications presenting promising functional outcomes following modifications in surgical approaches. Conclusions: This review provides a detailed overview of the current knowledge of prostate anatomy, its surrounding tissue, and its influence on key surgical step development for RALP.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".