Automated Steerable Path Planning for Deep Brain Stimulation Safeguarding Fiber Tracts and Deep Gray Matter Nuclei.

Area of Science:

• Neurosurgery and Robotics
• Medical Imaging and Image Analysis
• Computational Neuroscience

Background:

• Deep Brain Stimulation (DBS) currently relies on manual, rectilinear trajectories for electrode placement, lacking automated planning for optimal targeting and safety.
• Existing methods struggle to accurately target deep brain nuclei like the subthalamic nucleus (STN) while avoiding critical surrounding structures.
• A need exists for advanced neuroimaging-guided, robotically-assisted surgical planning to enhance DBS procedure safety and efficacy.

Purpose of the Study:

• To present a novel algorithm for automatically planning curvilinear trajectories (CTs) for Deep Brain Stimulation (DBS).
• To enhance the safety and precision of DBS electrode implantation by avoiding patient-specific anatomical obstacles.
• To compare the efficacy and safety of CTs against traditional rectilinear trajectories (RTs) for targeting the subthalamic nucleus (STN).

Main Methods:

• Developed an automated path planner to estimate DBS curvilinear trajectories (CTs) targeting deep brain structures.
• Utilized advanced neuroimaging, including 3T MRI (T1-weighted, TOF-MRA) and diffusion MR tractography, to identify target nuclei and surrounding obstacles (vessels, deep gray matter).
• Compared CTs with surgeon-defined rectilinear trajectories (RTs) in ten healthy controls, evaluating distance from obstacles, target accuracy (center of mass), and entry angles.

Main Results:

• The automated planner successfully generated CTs, demonstrating superior performance in maximizing minimal distance from critical structures compared to RTs.
• CTs showed improved accuracy in reaching the center of mass (COM) of the subthalamic nucleus (STN).
• Curvilinear trajectories optimized the entry angle into the STN and the skull surface, indicating enhanced precision and potentially reduced invasiveness.

Conclusions:

• The developed algorithm represents a breakthrough in microsurgical robotics, enabling automatic computation of DBS trajectory plans.
• Patient-specific CTs, guided by advanced neuroimaging, offer a significant safety improvement over standard rectilinear approaches for DBS surgery.
• This automated planning approach holds promise for increasing the safety and efficacy of targeting deep brain nuclei, particularly the STN.