Learning Curve in Laparoscopic Liver Resection, Educational Value of Simulation and Training Programmes: A Systematic...

Area of Science:

• Minimally Invasive Surgery
• Surgical Education
• Hepatobiliary Surgery

Background:

• Laparoscopic liver resection (LLR) is a preferred surgical approach for abdominal procedures.
• The adoption of LLR has been hindered by a steep learning curve (LC).
• Limited research exists on advanced training methodologies for LLR.

Purpose of the Study:

• To systematically review the literature on the learning curve (LC) and training strategies for laparoscopic liver resection (LLR).

Main Methods:

• A systematic literature search was conducted using MEDLINE and EMBASE databases.
• Keywords included 'learning curve', 'teaching', 'training', 'simulation', 'education', 'liver', 'hepatic', 'laparoscopic', and 'laparoscopy'.
• Exclusions comprised robotic-assisted, hand-assisted, and hybrid LLR techniques.

Main Results:

• Nineteen studies were analyzed, predominantly with low evidence levels.
• The LC for minor LLR was approximately 60 cases, with 15 for left lateral sectionectomy.
• For major LLR (MLLR), the LC ranged from 15-50 cases, with recent studies suggesting 15-20 cases for progressive implementation in select patients.
• Six studies indicated that simulation and training programs could potentially shorten the LC.
• A minimum of 60 minor LLRs was suggested before undertaking MLLR.

Conclusions:

• The learning curve (LC) for laparoscopic liver resection (LLR) is extensive.
• Major LLR (MLLR) should be introduced gradually under expert supervision.
• Off-site, simulation-based training may effectively mitigate the real-world learning curve (LC).