Related Experiment Video
Updated: Jun 26, 2026
06:18
Pioneering Patient-Specific Approaches for Precision Surgery Using Imaging and Virtual Reality
Published on: April 5, 2024
A practical approach to procedural planning for robot-assisted segmentectomy using a lobectomy-based surgical
Keiji Yamanashi1, Ryo Miyata2, Takeshi Kawaguchi2
1Department of Thoracic and Cardiovascular Surgery, Nara Medical University School of Medicine, 840 Shijo-cho, Kashihara, Nara, 634-8522, Japan. jiike6180@kuhp.kyoto-u.ac.jp.
General Thoracic and Cardiovascular Surgery
|June 24, 2026
Summary
This study shows that using a surgical simulator for robot-assisted segmentectomy improves preoperative planning by rehearsing dissection sequences. This approach helps reduce intraoperative uncertainty in lung cancer surgery.
Area of Science:
- Thoracic Surgery
- Surgical Simulation
- Robotic Surgery
Background:
- Accurate preoperative planning for robot-assisted segmentectomy is crucial for understanding complex segmental anatomy and vascular/bronchial division.
- Three-dimensional computed tomography (3D-CT) offers detailed anatomy but cannot predict dynamic intraoperative changes.
- Existing methods lack stepwise prediction of anatomical alterations during surgery.
Purpose of the Study:
- To evaluate the utility of a lobectomy-based da Vinci surgical simulator for preoperative planning of robot-assisted apical-anterior segmentectomy.
- To assess the simulator's ability to rehearse dissection sequences and anticipate post-division anatomical relationships.
- To determine if simulation provides added value beyond conventional imaging for reducing intraoperative uncertainty.
Main Methods:
- Application of a lobectomy-based da Vinci surgical simulator for preoperative planning.
- Focus on rehearsing the sequence of dissection and anticipating anatomical changes.
- Procedure performed on a patient with a pulmonary nodule suspected as stage IA1 non-small cell lung cancer.
Main Results:
- The simulated workflow closely mirrored the actual intraoperative findings.
- The simulation focused on procedural rehearsal and anticipating anatomical shifts.
- The approach demonstrated potential for reducing intraoperative uncertainty.
Conclusions:
- A lobectomy-based surgical simulator can be a practical adjunct to conventional imaging for robot-assisted segmentectomy planning.
- Simulation allows for procedural rehearsal, enhancing understanding of dynamic anatomical changes.
- This method may improve outcomes in selected cases of lung cancer surgery.
