A Brief Insight on Magnetic Resonance Conditional Neurosurgery Robots

Area of Science:

• Neurosurgery
• Medical Robotics
• Biomedical Engineering

Background:

• Neurosurgery demands high precision, but developing surgical robots is complex.
• Existing neurosurgery robots are few, costly, and limit widespread adoption.
• Brain-related diseases necessitate advanced, accessible neurosurgical solutions.

Purpose of the Study:

• To provide a historical perspective and literature review of magnetic resonance conditional stereotactic neurosurgery robots.
• To analyze robots currently in clinical use, those in research, and future prospects.
• To explore the advantages of magnetic resonance imaging (MRI) and conditional robots in neurosurgery.

Main Methods:

• Literature review of magnetic resonance conditional stereotactic neurosurgery robots.
• Analysis of robots in clinical use versus research and development.
• Examination of image compatibility test data and accuracy results.
• Comparison of actuation, control technologies, materials, and degrees of freedom.

Main Results:

• Identified a limited number of neurosurgery robots in clinical practice due to high costs.
• Highlighted the advantages of MRI-compatible robots for enhanced surgical precision.
• Discussed differences in actuation, control, materials, and degrees of freedom among systems.
• Evaluated image compatibility and accuracy data for clinical system performance.

Conclusions:

• Magnetic resonance conditional stereotactic neurosurgery robots offer significant advantages for precision surgery.
• Cost remains a barrier to widespread clinical adoption of advanced neurosurgical robots.
• Future challenges lie in further automation and integration of these advanced systems.