A magnetic resonance conditional robot for lumbar spinal injection: Development and preliminary validation.

Area of Science:

• Robotics
• Medical Devices
• Neurosurgery

Background:

• Lower back pain is a prevalent condition often treated with targeted injections.
• Accurate needle placement is critical for effective lumbar injections.
• Existing robotic systems may have limitations in MR environments or flexibility.

Purpose of the Study:

• To design and validate a Magnetic Resonance (MR) conditional robot for precise lumbar injections.
• To assess the robot's suitability for lower back pain treatment.
• To evaluate the robot's performance in terms of accuracy and functionality.

Main Methods:

• Developed a 4-degree-of-freedom (DOF) robot with a compact (200 × 230 × 130 mm³) and lightweight (0.8 kg) design.
• Affixed the robot directly to the patient's back for a rigid connection, minimizing movement-induced errors.
• Utilized an electromagnetic (EM) tracking system and a needle with an embedded EM sensor for accuracy validation.

Main Results:

• Achieved a position accuracy of 0.88 ± 0.46 mm in free space evaluation.
• Demonstrated a target position accuracy of 3.62 ± 0.92 mm during phantom mock insertions using a Loop-X CBCT scanner.
• The robot's lightweight and compact design ensures stability and reduces positional errors.

Conclusions:

• The MR-conditional robot offers improved rotation range and flexible needle adjustment.
• Preliminary validation shows promising results for accurate and safe lumbar injections.
• The system's enhanced features suggest broader clinical applications in pain management and interventional procedures.