Multicenter validation of automated trajectories for selective laser amygdalohippocampectomy

Vejay N. Vakharia, Rachel Sparks, Kuo Li, Aidan G. O'Keeffe, Fernando Pérez-García, Lucas Gabriel Souza França, Andrew L. Ko, Chengyuan Wu, Joshua P. Aronson, Brett E. Youngerman, Ashwini Sharan, Guy McKhann, Sebastien Ourselin, John S. Duncan

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


Objective: Laser interstitial thermal therapy (LITT) is a novel minimally invasive alternative to open mesial temporal resection in drug-resistant mesial temporal lobe epilepsy (MTLE). The safety and efficacy of the procedure are dependent on the preplanned trajectory and the extent of the planned ablation achieved. Ablation of the mesial hippocampal head has been suggested to be an independent predictor of seizure freedom, whereas sparing of collateral structures is thought to result in improved neuropsychological outcomes. We aim to validate an automated trajectory planning platform against manually planned trajectories to objectively standardize the process. Methods: Using the EpiNav platform, we compare automated trajectory planning parameters derived from expert opinion and machine learning to undertake a multicenter validation against manually planned and implemented trajectories in 95 patients with MTLE. We estimate ablation volumes of regions of interest and quantify the size of the avascular corridor through the use of a risk score as a marker of safety. We also undertake blinded external expert feasibility and preference ratings. Results: Automated trajectory planning employs complex algorithms to maximize ablation of the mesial hippocampal head and amygdala, while sparing the parahippocampal gyrus. Automated trajectories resulted in significantly lower calculated risk scores and greater amygdala ablation percentage, whereas overall hippocampal ablation percentage did not differ significantly. In addition, estimated damage to collateral structures was reduced. Blinded external expert raters were significantly more likely to prefer automated to manually planned trajectories. Significance: Retrospective studies of automated trajectory planning show much promise in improving safety parameters and ablation volumes during LITT for MTLE. Multicenter validation provides evidence that the algorithm is robust, and blinded external expert ratings indicate that the trajectories are clinically feasible. Prospective validation studies are now required to determine if automated trajectories translate into improved seizure freedom rates and reduced neuropsychological deficits.

Original languageEnglish
Publication statusPublished - 1 Sept 2019

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