Semi-autonomous image-guided brain tumour resection using an integrated robotic system: A bench-top study

Area of Science:

• Neurosurgery
• Medical Robotics
• Surgical Oncology

Background:

• Complete brain tumor resection is crucial for patient survival and quality of life.
• Residual tumor tissue after surgery can negatively impact outcomes.
• Current surgical techniques may leave microscopic tumor remnants.

Purpose of the Study:

• To introduce a prototype medical robotic system for automated detection and removal of brain tumor residues.
• To develop an integrated surgical robotic system for image-guided neurosurgery.
• To explore the Behavior Tree framework for coordinating medical subtasks in robotic surgery.

Main Methods:

• Development of an integrated surgical robotic system.
• Utilizing the Behavior Tree framework for cross-platform task coordination.
• Testing the system on a simulated laboratory platform with real-time endoscopic image guidance.

Main Results:

• The system demonstrated feasibility for supervised semi-automation of residual brain tumor ablation.
• Sub-millimetre accuracy was achieved in a simulated surgical cavity.
• The modular control architecture facilitates integration of additional medical devices.

Conclusions:

• The presented work is a semi-automated laboratory setup simulating intraoperative robotic neurosurgery.
• Real-time endoscopic image guidance was employed.
• This provides a foundation for transitioning engineering approaches to clinical practice.