ArticleJournal of robotic surgery2024
A novel low-cost high-fidelity porcine model of liver metastases for simulation training in robotic parenchyma-preserving liver resection.
Article in Journal of robotic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Development and use of a Porcine Liver Model (PLM) for robotic liver surgery training.Journal of robotic surgery · 2026Article
- Pre-Procedural Robotic Surgery Curricula: A Systematic Review and Thematic Meta-Synthesis.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026Review
- Simulation-based training and education in laparoscopic hepatobiliary and pancreatic surgery.Frontiers in surgery · 2026Review
- A swine model for surgical training in various types of robotic liver resection with surgical videos.Journal of robotic surgery · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the era of minimally invasive surgery (MIS), parenchyma-preserving liver resections are gaining prominence with the potential to offer improved perioperative outcomes without compromising oncological safety. The surgeon learning curve remains challenging, and simulation plays a key role in surgical training. Existing simulation models can be limited by suboptimal fidelity and high cost. We describe a novel, reproducible, high-fidelity, low-cost liver metastases model using porcine livers from adult Landrace pigs, with porcine perinephric fat used to simulate subcapsular metastases. This model was then utilised in a training session for surgical trainees performing robotic parenchyma-preserving surgery (PPS) under the guidance of expert robotic surgeons, with feedback being recorded. Trainees rated the model highly on its fidelity to human liver simulation (median score 9), tissue handling (median score 8), and overall usefulness (median score 9). Tissue handling was felt to simulate in vivo liver resection closely, while suggestions for improvement included adding simulated blood flow. This is a novel, low-cost, high-fidelity simulation model of liver metastases with high acceptability to surgical trainees, which could be readily adopted by other training centres.
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Registered trials
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