BrainQuake: An Open-Source Python Toolbox for the Stereoelectroencephalography Spatiotemporal Analysis

SEEG4D: a tool for 4D visualization of stereoelectroencephalography data

Epilepsy is a prevalent and serious neurological condition which impacts millions of people worldwide. Stereoelectroencephalography (sEEG) is used in cases of drug resistant epilepsy to aid in surgical resection planning due to its high spatial resolution and ability to visualize seizure onset zones. For accurate localization of the seizure focus, sEEG studies combine pre-implantation magnetic resonance imaging, post-implant computed tomography to visualize electrodes, and temporally recorded sEEG electrophysiological data. Many tools exist to assist in merging multimodal spatial information; however, few allow for an integrated spatiotemporal view of the electrical activity. In the current work, we present SEEG4D, an automated tool to merge spatial and temporal data into a complete, four-dimensional virtual reality (VR) object with temporal electrophysiology that enables the simultaneous viewing of anatomy and seizure activity for seizure localization and presurgical planning. We developed an automated, containerized pipeline to segment tissues and electrode contacts. Contacts are aligned with electrical activity and then animated based on relative power. SEEG4D generates models which can be loaded into VR platforms for viewing and planning with the surgical team. Automated contact segmentation locations are within 1 mm of trained raters and models generated show signal propagation along electrodes. Critically, spatial-temporal information communicated through our models in a VR space have potential to enhance sEEG pre-surgical planning.

An Improved Neurosurgical Planning Method for Focal Epileptic Seizure Surgery using Stereo-EEG-Based Source Localization and Multimodal Imaging

Refractory Focal Epilepsy can be treated by the surgical resection of the Seizure Onset Zone (SOZ), the region in the brain from which seizures originate. To remove the SOZ, precise localization must be performed to identify this region, and to minimize the risk of removing eloquent cortex. StereoEEG is a valuable method to localize the SOZ, by recording the propagation of epileptic signals using a series of implanted depth electrodes. This allows the origin of the seizure signals to be determined based on the time at which they are detected at known electrode contact coordinates along the implanted electrodes. The automation of the localization of the SOZ using stereo-EEG, CT and MRI data is becoming increasingly relevant in the neurosurgical literature, as it offers an opportunity for increased accuracy and efficiency. This study proposes a novel method to localize the SOZ by using multimodal image processing. The method allows a statistical representation of the SOZ to be constructed on the cortical surface model, by using a series of spatial transformations. In a clinical case of MRI-positive focal epilepsy, the proposed pipeline was able to correctly identify the SOZ whilst using electrophysiological input from distant electrodes with 80-90% of the pipeline's result being within the resection cavity. In an MRI-negative patient's result, 60-75% of the SOZ determination was also within the resective cavity. In both cases, the pipeline showed greater than 50% reduction in SOZ volume determination. Such precise localization may allow for smaller resection volumes to achieve seizure freedom and reduce neurological complications. This method may therefore offer a more accurate solution to SOZ localization with a reduced clinical workload.

Recent developments in stereo electroencephalography monitoring for epilepsy surgery

Recently the utilization of the stereo electroencephalography (SEEG) method has exploded globally. It is now the preferred method of intracranial monitoring for epilepsy. Since its inception, the basic tenet of the SEEG method remains the same: strategic implantation of intracerebral electrodes based on a hypothesis grounded on anatomo-electroclinical correlation, interpretation of interictal and ictal abnormalities, and formation of a surgical plan based on these data. However, there are recent advancements in all these domains-electrodes implantations, data interpretation, and therapeutic strategy- that can make the SEEG a more accessible and effective approach. In this narrative review, these newer developments are discussed and summarized. Regarding implantation, efficient commercial robotic systems are now increasingly available, which are also more accurate in implanting electrodes. In terms of ictal and interictal abnormalities, newer studies focused on correlating these abnormalities with pathological substrates and surgical outcomes and analyzing high-frequency oscillations and cortical-subcortical connectivity. These abnormalities can now be further quantified using advanced tools (spectrum, spatiotemporal, connectivity analysis, and machine learning algorithms) for objective and efficient interpretation. Another aspect of recent development is renewed interest in SEEG-based electrical stimulation mapping (ESM). The SEEG-ESM has been used in defining epileptogenic networks, mapping eloquent cortex (primarily language), and analyzing cortico-cortical evoked potential. Regarding SEEG-guided direct therapeutic strategy, several clinical studies evaluated the use of radiofrequency thermocoagulation. As the emerging SEEG-based diagnosis and therapeutics are better evolved, treatments aimed at specific epileptogenic networks without compromising the eloquent cortex will become more easily accessible to improve the lives of individuals with drug-resistant epilepsy (DRE).

Previous, current, and future stereotactic EEG techniques for localising epileptic foci

INTRODUCTION

Drug-resistant focal epilepsy presents a significant morbidity burden globally, and epilepsy surgery has been shown to be an effective treatment modality. Therefore, accurate identification of the epileptogenic zone for surgery is crucial, and in those with unclear noninvasive data, stereoencephalography is required.

AREAS COVERED

This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally.

EXPERT OPINION

We provide a perspective on the future directions in the field, reviewing improvements in predicting electrode bending, image acquisition, machine learning and artificial intelligence, advances in surgical planning and visualization software and hardware. We also see the development of EEG analysis tools based on machine learning algorithms that are likely to work synergistically with neurophysiology experts and improve the efficiency of EEG and SEEG analysis and 3D visualization. Improving computer-assisted planning to minimize manual input from the surgeon, and seamless integration into an ergonomic and adaptive operating theater, incorporating hybrid microscopes, virtual and augmented reality is likely to be a significant area of improvement in the near future.