Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation

• Type of Material: Article
• Authors: Vejay N. Vakharia, University College London; Rachel E. Sparks, Kings College London; Sjoerd B. Vos, University College London; Yarema Bezchlibnyk, University of South Florida; Ashesh D. Mehta, Northwell Health Neuroscience Institute; Jon Willie, Emory University; Chengyuan Wu, Thomas Jefferson University; Ashwini Sharan, Thomas Jefferson University; Sebastian Ourselin, Kings College London; John S. Duncan, University College London
• Language: English
• Date: 2020-01-01
• Publisher: Elsevier: Creative Commons
• Publication Version: Final Published Version
• Copyright Statement: © 2020 The Authors
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.nicl.2020.102174
• Title of Journal or Parent Work: NeuroImage: Clinical
• ISSN: 2213-1582
• Volume: 25
• Start Page: 102174
• End Page: 102174
• Grant/Funding Information: NIHR UCLH/UCL Biomedical Research Centre, senior investigator schemes and Wellcome Trust (WT106882) / Wellcome/EPSRC (203145Z/16/Z).
• Keywords: Neuroimaging; Laser interstitial thermal therapy; Computer-assisted planning; TRAJECTORIES; Science & Technology; EPILEPSY; Corpus Callosotomy; STIMULATION; Neurosciences & Neurology; Life Sciences & Biomedicine; ELECTRODES; OUTCOMES
• Research Categories: Biology, Neuroscience; Health Sciences, Radiology

Abstract

Background: Anterior two-thirds corpus callosotomy is an effective palliative neurosurgical procedure for drug-refractory epilepsy that is most commonly used to treat drop-attacks. Laser interstitial thermal therapy is a novel stereotactic ablative technique that has been utilised as a minimally invasive alternative to resective and disconnective open neurosurgery. Case series have reported success in performing laser anterior two-thirds corpus callosotomy. Computer-assisted planning algorithms may help to automate and optimise multi-trajectory planning for this procedure. Objective: To undertake a simulation-based feasibility study of computer-assisted corpus callostomy planning in comparison with expert manual plans in the same patients. Methods: Ten patients were selected from a prospectively maintained database. Patients had previously undergone diffusion-weighted imaging and digital subtraction angiography as part of routine SEEG care. Computer-assisted planning was performed using the EpiNav™ platform and compared to manually planned trajectories from two independent blinded experts. Estimated ablation cavities were used in conjunction with probabilistic tractography to simulate the expected extent of interhemispheric disconnection. Results: Computer-assisted planning resulted in significantly improved trajectory safety metrics (risk score and minimum distance to vasculature) compared to blinded external expert manual plans. Probabilistic tractography revealed residual interhemispheric connectivity in 1/10 cases following computer-assisted planning compared to 4/10 and 2/10 cases with manual planning. Conclusion: Computer-assisted planning successfully generates multi-trajectory plans capable of LITT anterior two-thirds corpus callosotomy. Computer-assisted planning may provide a means of standardising trajectory planning and serves as a potential new tool for optimising trajectories. A prospective validation study is now required to determine if this translates into improved patient outcomes.