Semi-automatic puncture robotic system based on real-time multi-modal image fusion: preclinical evaluation

Area of Science:

• Medical Robotics
• Surgical Navigation
• Medical Imaging Fusion

Background:

• Traditional surgical robot systems face challenges in abdominal organ puncture due to respiratory-induced target displacement and lack of real-time visualization.
• These limitations reduce puncture accuracy and increase the risk of medical accidents.

Purpose of the Study:

• To develop a semi-automatic surgical robot system for enhanced abdominal organ puncture surgeries.
• To address limitations of traditional systems by integrating real-time ultrasound and CT image fusion with respiratory monitoring.

Main Methods:

• A six-axis force sensor was used to construct a respiratory model for monitoring the patient's respiratory phase and identifying optimal puncture timing.
• Real-time registration and fusion of ultrasound (US) images with preoperative computed tomography (CT) images were employed for accurate puncture guidance.

Main Results:

• Phantom and animal experiments demonstrated an average fusion error between US and CT within 3 mm for liver tissues.
• Puncture accuracy achieved an average error of 1.0 mm in phantom experiments and 2.5 mm in animal experiments.
• The system's image fusion and puncture accuracy were within the 3 mm range, meeting clinical requirements.

Conclusions:

• The developed semi-automatic surgical robot system achieves high image fusion and puncture accuracy (within 3 mm), meeting clinical needs.
• The system automates approximately 70% of surgical operations, significantly reducing reliance on surgeon experience and enhancing safety.