Non-contact artificial intelligence-assisted intraoperative 3D navigation technology prospective application study in...

Area of Science:

• Thoracic Surgery
• Surgical Navigation Technologies
• Medical Imaging and Reconstruction

Background:

• Minimally invasive lung cancer surgery relies on 3D reconstruction navigation.
• Conventional navigation requires an assistant, limiting real-time performance and surgeon autonomy.
• Limitations in current navigation necessitate improved surgeon-controlled systems.

Purpose of the Study:

• To develop a surgeon-autonomous, non-contact intraoperative 3D navigation system.
• To evaluate the clinical application value of this novel system in lung cancer surgery.
• To compare the non-contact system against traditional assistive displays.

Main Methods:

• A prospective study involving 62 early-stage lung cancer patients undergoing pulmonary segmentectomy.
• Patients were randomized into an experimental group (non-contact 3D navigation) and a control group (assistive display).
• Key outcome measures included blood loss, surgical success rate, operation time, navigation time, and operator satisfaction.

Main Results:

• The non-contact navigation group showed significantly shorter navigation times (50-107s vs. 120-234s) and faster operation times (84.23±13.18 min vs. 101.84±11.01 min).
• Surgical success rates were higher in the experimental group (96.77% vs. 93.55%), with significantly greater surgeon satisfaction (96.9±0.34 vs. 89.7±0.54).
• No significant difference in blood loss was observed between the groups.

Conclusions:

• The surgeon-autonomous non-contact intraoperative 3D navigation system significantly improves navigation efficiency.
• This technology enhances surgeon satisfaction and autonomy during lung cancer surgery.
• The system demonstrates considerable clinical value for early-stage lung cancer treatment.