Training robotic hepatectomy: the Hong Kong experience and perspective

Area of Science:

• Hepatobiliary Surgery
• Minimally Invasive Surgery
• Robotic Surgery

Background:

• Robotic surgical systems are transforming minimally invasive surgery (MIS).
• Data on robotic hepatectomy is limited, but initial findings suggest comparable outcomes to laparoscopic approaches regarding blood loss, morbidity, mortality, and hospital stay.
• The learning curve for robotic liver surgery remains largely unevaluated.

Purpose of the Study:

• To evaluate the learning curve and training requirements for robotic hepatectomy.
• To provide insights into the necessary experience and team preparedness for adopting robotic liver surgery.

Main Methods:

• Systematic literature search of MEDLINE and PubMed databases (January 2001 - May 2016).
• Keywords used: "laparoscopic hepatectomy", "robotic hepatectomy", and "learning curve".
• Analysis based on existing data from laparoscopic hepatectomy learning curve studies.

Main Results:

• The learning curve for robotic hepatectomy must be informed by laparoscopic hepatectomy experience.
• Estimated cases to overcome learning curve: 22-64 for minor and 45-75 for major laparoscopic hepatectomies.
• Left lateral sectionectomy is a suitable starting point for MIS liver surgery training.

Conclusions:

• Robotic hepatectomy training is heavily reliant on surgeons' prior open, laparoscopic, and robotic surgery experience, as well as team proficiency and disease complexity.
• Performance of robotic hepatectomy is discouraged for unprepared teams or occasional patients outside specialized centers.
• Fundamental surgical knowledge and practical skills are paramount and cannot be superseded by advanced robotic technology.