A framework for integrating real-time MRI with robot control: application to simulated transapical cardiac...

Area of Science:

• Medical Imaging
• Robotics in Surgery
• Interventional Radiology

Background:

• Intraoperative imaging guidance is crucial for robotic surgery.
• Current methods often rely solely on visual perception.
• Real-time image guidance enhances surgical precision and safety.

Purpose of the Study:

• To propose a framework for robot-assisted interventions guided by real-time magnetic resonance imaging (rtMRI).
• To integrate rtMRI data with robot control for enhanced perception and maneuvering.
• To improve the safety and accuracy of robotic surgical procedures.

Main Methods:

• Developed a computational core to process on-the-fly rtMRI data.
• Integrated rtMRI processing with robot control and human-machine interfaces.
• Implemented a visualization and force-feedback system for enhanced operator perception.
• Tested the framework using a simulated Transapical aortic valve implantation with a virtual robotic manipulator.

Main Results:

• The computational core achieved processing speeds of 20 Hz for visualization and 1000 Hz for force feedback.
• The framework significantly reduced procedure duration by half in the simulated task.
• Enhanced safety was observed by reducing collisions with tissue during simulated cardiac and breathing motion.

Conclusions:

• The proposed rtMRI-guided framework enables safe and accurate robotic maneuvering.
• Real-time image guidance significantly improves surgical efficiency and patient safety.
• This technology represents a paradigm shift in image-guided robotic surgery.