Realistic Anatomical Prostate Models for Surgical Skills Workshops Using Ballistic Gelatin for Nerve-Sparing Radical Prostatectomy and Fruit for Simple Prostatectomy
Bibliographic record
Abstract
PURPOSE: Understanding of prostate anatomy has evolved as techniques have been refined and improved for radical prostatectomy (RP), particularly regarding the importance of the neurovascular bundles for erectile function. The objectives of this study were to develop inexpensive and simple but anatomically accurate prostate models not involving human or animal elements to teach the terminology and practical aspects of nerve-sparing RP and simple prostatectomy (SP). MATERIALS AND METHODS: The RP model used a Foley catheter with ballistics gelatin in the balloon and mesh fabric (neurovascular bundles) and balloons (prostatic fascial layers) on either side for the practice of inter- and intrafascial techniques. The SP model required only a ripe clementine, for which the skin represented compressed normal prostate, the pulp represented benign tissue, and the pith mimicked fibrous adhesions. A modification with a balloon through the fruit center acted as a "urethra." RESULTS: Both models were easily created and successfully represented the principles of anatomical nerve-sparing RP and SP. Both models were tested in workshops by urologists and residents of differing levels with positive feedback. CONCLUSIONS: Low-fidelity models for prostate anatomy demonstration and surgical practice are feasible. They are inexpensive and simple to construct. Importantly, these models can be used for education on the practical aspects of nerve-sparing RP and SP. The models will require further validation as educational and competency tools, but as we move to an era in which human donors and animal experiments become less ethical and more difficult to complete, so too will low-fidelity models become more attractive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".