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Precise path planning for robot-assisted craniotomy: a CT-driven virtual center method.

Li Zhichao1, Wenqing Ren2, Hao Ren1

  • 1Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, People's Republic of China.

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Summary
This summary is machine-generated.

This study introduces a new method for robotic craniotomy path planning using CT images, improving surgical precision and safety. The automated approach enhances efficiency for complex neurosurgeries.

Keywords:
adaptive path planningcomputer-aided surgeryhead CTimage-to-patient registrationrobot-assisted craniotomy

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Area of Science:

  • Neurosurgery
  • Robotics
  • Medical Imaging

Background:

  • Craniotomy is essential for neurosurgery but manual methods are inefficient and risky.
  • Robotic systems offer improved precision, safety, and efficiency in surgical procedures.

Purpose of the Study:

  • To propose a novel path planning method for robotic craniotomy using only computed tomography (CT) images.
  • To automate surgical path generation for enhanced craniotomy procedures.

Main Methods:

  • The craniotomy process involves two stages: drilling and milling.
  • A virtual-center method adaptively computes and optimizes milling paths from drilling data.
  • Paths are optimized for minimal invasiveness and smoothed for robotic execution.

Main Results:

  • The method successfully generated clinically approved outcomes in both phantom and in vivo studies.
  • Validation included 10 skull phantoms and 3 living dogs, demonstrating high success rates.

Conclusions:

  • The proposed path planning method seamlessly integrates with robotic surgical systems.
  • This approach enhances current craniotomy techniques and supports autonomous robotic neurosurgery development.