A novel robotic system for vascular intervention: principles, performances, and applications

Area of Science:

• Robotics in Medicine
• Medical Imaging
• Vascular Surgery

Background:

• Minimally invasive vascular interventions (VI) require precise instrument manipulation.
• Surgeons performing VI are often exposed to harmful X-ray radiation.
• Existing robotic systems may have limitations in real-time control and feedback.

Purpose of the Study:

• To design, develop, and evaluate a novel image-guided master-slave robotic system for vascular intervention.
• To assess the system's performance in terms of speed, accuracy, and real-time control.
• To validate the system's feasibility and efficiency through in vivo trials.

Main Methods:

• The system utilizes a peer-to-peer (P2P) communication, kinetics analysis, and a sliding-mode neural network control model.
• Master-slave architecture enables remote operation, shielding surgeons from radiation.
• Performance evaluation included speed, position tracking, and accuracy tests, alongside in vivo swine trials.

Main Results:

• The robotic system achieved high accuracy in translational (error ≤ 0.45%) and rotational (error ≤ 2.6%) movements.
• Contrast agent injection accuracy was within 0.2 ml.
• Successful stent revascularization and four in vivo trials demonstrated system efficacy and haptic feedback correlation.

Conclusions:

• The image-guided master-slave robotic system is feasible and efficient for vascular interventions.
• Performance evaluations and successful in vivo trials validate the system's potential.
• This robotic system offers a promising avenue for future research in image-guided surgery.