137 An Easily Implemented, Open Access Semiautomated Pipeline for Intracranial Electrode Localization. (1st August 2016) - Dyster, Timothy G.; Pathak, Yagna; Smith, Elliot; Sheth, Sameer A.
Abstract: INTRODUCTION: Patients with medically refractory epilepsy often require intracranial electrode implantation for seizure localization. As the use of these procedures continues to increase, the demand for simpler and more efficient methods of electrode localization methods has grown. We developed a semiautomated pipeline to localize electrode contacts using multimodal neuroimaging data. METHODS: Our pipeline coregisters the preoperative MRI and the postoperative CT for each patient using a rigid body transformation and scaling to align electrodes in patient-specific anatomy. It then extracts a volumetric brain image to create a mask that represents the data space of interest. We wrote customized code to automatically determine image-specific intensity thresholds, distinguish contacts fused by artifact signal, and output contact coordinates. Coordinates are integrated with a sophisticated 3-dimensional model for visualization. This pipeline was initially validated in a sample of 6 patients with 785 intracranial electrodes. We evaluated coordinate accuracy by total contact count and visual inspection of coordinates plotted on the postoperative CT. RESULTS: Coordinates for 780 of 785 (99.4%) contacts were successfully identified. Specificity for contacts was 99.6% because of the detection of 3 anchor bolts in 1 patient that were within the cranial vault and therefore miscategorized as contacts. All extracranial contacts were successfully excluded. We subsequently used our method to successfully visualize the anatomical segregation of various response types during a Stroop-like task across >1500 contacts in 19 patients. CONCLUSION: The method described is an accurate and easily implemented approach to intracranial electrode localization using MATLAB and open access tools. Compared with similar open access methods, our pipeline requires minimal user input and significantly reduces person-hours required for task completion. This method allows for seamless analysis of electrode locations and thus can be widely used in clinical and electrophysiological research.