Efficient anatomy driven automated multiple trajectory planning for intracranial electrode implantation

Abstract

Epilepsy is curable if the epileptogenic zone (EZ) can be identified within the brain and resected. Intracranial depth electrodes help identify the EZ and also map cortical function. In current clinical practice,7–12 electrode trajectories typically needed,and are planned manually,requiring 2–3 h. Automated methods can reduce planning time and improve safety by computing suitable trajectories. We present anatomy driven multiple trajectory planning (ADMTP) to compute safe trajectories from anatomical regions of interest(ROIs). Trajectories are computed by (1) identifying targets within deep ROIs,(2) finding trajectories that traverse superficial ROIs and avoid critical structures (blood vessels,sulci),and (3) determining a feasible configuration of trajectories. ADMTP was evaluated on 20 patients (186 electrodes). Compared to manual planning,ADMTP lowered risk in 78% of trajectories and increased GM sampling in 56% of trajectories. ADMTP is computationally efficient,computing between 7–12 trajectories in 61 (15–279) s.