Development of a precision multimodal surgical navigation system for lung robotic segmentectomy

Area of Science:

• Thoracic Surgery
• Surgical Oncology
• Medical Imaging

Background:

• Minimally invasive sublobar anatomical resection is increasingly utilized for early lung lesions.
• Robotic-assisted thoracic surgery (RATS) offers unique advantages in integrating advanced imaging.
• Current techniques aim to improve precision and outcomes in lung cancer surgery.

Purpose of the Study:

• To describe the application of 3D imaging in RATS for lung lesion resection.
• To evaluate the integration of preoperative planning, intraoperative assistance, and complementary investigations.
• To assess the impact of 3D imaging on surgical safety and accuracy.

Main Methods:

• Utilized the DaVinci System for robotic segmentectomies.
• Employed Visible Patient™ for 3D modelization and Tile Pro for image integration.
• Included preoperative planning, intraoperative guidance, radial endobronchial ultrasound (R-EBUS), and virtual bronchoscopy.

Main Results:

• Experience based on 114 robotic segmentectomies.
• A multimodal system with 3D imaging demonstrated perfect operative anatomic accuracy in over 40 patients.
• The use of an anatomic model improved procedure safety and reliability.

Conclusions:

• Integrated 3D imaging in RATS significantly enhances safety and reliability for lung lesion resection.
• This multimodal approach transforms surgical decision-making and improves operative accuracy.
• Future developments include virtual reality integration for an enhanced surgical experience.