Electroencephalography can provide advance warning of technical errors during laparoscopic surgery

Area of Science:

• Neuroscience
• Surgical Technology
• Medical Engineering

Background:

• Increasing intraoperative adverse events necessitate improved patient safety measures.
• Existing early warning systems (EWSs) primarily focus on patient deterioration, not surgical performance.
• Prior research explored electroencephalography (EEG) for predicting motor errors in non-surgical contexts.

Purpose of the Study:

• To investigate the potential of EEG in predicting technical errors during surgery.
• To establish a proof-of-concept for an EEG-based system for surgical error detection.

Main Methods:

• A cohort study involving three surgical fellows performing 12 elective laparoscopic general surgeries.
• Simultaneous recording of audiovisual operating room data and surgeon's neural activity (EEG).
• Coding of technical errors and good surgical performance, with neural activity analysis preceding events.

Main Results:

• Distinct neural signatures associated with error monitoring and motor uncertainty were identified.
• These neural signatures were detected significantly earlier (17 seconds) before technical errors occurred.
• No such predictive neural activity was observed prior to epochs of good surgical performance.

Conclusions:

• Specific neural patterns can predict impending technical errors in laparoscopic surgery.
• An EEG-based EWS could enhance surgical training by identifying potential errors before patient harm.
• Further research is needed to validate findings and minimize false alarm rates.