Automatic trajectory planning of DBS neurosurgery from multi-modal MRI datasets

  • Authors:
  • Silvain Bériault;Fahd Al Subaie;Kelvin Mok;Abbas F. Sadikot;G. Bruce Pike

  • Affiliations:
  • McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada;McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada;McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada;McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada;McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada

  • Venue:
  • MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose an automated method for preoperative trajectory planning of deep brain stimulation image-guided neurosurgery. Our framework integrates multi-modal MRI analysis (T1w, SWI, TOF-MRA) to determine an optimal trajectory to DBS targets (subthalamic nuclei and globus pallidus interna) while avoiding critical brain structures for prevention of hemorrhages, loss of function and other complications. Results show that our method is well suited to aggregate many surgical constraints and allows the analysis of thousands of trajectories in less than 1/10th of the time for manual planning. Finally, a qualitative evaluation of computed trajectories resulted in the identification of potential new constraints, which are not addressed in the current literature, to better mimic the decision-making of the neurosurgeon during DBS planning.