Early seizure spread and epilepsy surgery: A systematic review

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.

Disrupting the epileptogenic network with stereoelectroencephalography-guided radiofrequency thermocoagulation

Stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) is a treatment option for focal drug-resistant epilepsy. In previous studies, this technique has shown seizure reduction by ≥50% in 50% of patients at 1 year. However, the relationship between the location of the ablation within the epileptogenic network and clinical outcomes remains poorly understood. Seizure outcomes were analyzed for patients who underwent SEEG-guided RF-TC and across subgroups depending on the location of the ablation within the epileptogenic network, defined as SEEG sites involved in seizure generation and spread. Eighteen patients who had SEEG-guided RF-TC were included. SEEG-guided seizure-onset zone ablation (SEEG-guided SOZA) was performed in 12 patients, and SEEG-guided partial seizure-onset zone ablation (SEEG-guided P-SOZA) in 6 patients. The early spread was ablated in three SEEG-guided SOZA patients. Five patients had ablation of a lesion. The seizure freedom rate in the cohort ranged between 22% and 50%, and the responder rate between 67% and 85%. SEEG-guided SOZA demonstrated superior results for both outcomes compared to SEEG-guided P-SOZA at 6 months (seizure freedom p = .294, responder rate p = .014). Adding the early spread ablation to SEEG-guided SOZA did not increase seizure freedom rates but exhibited comparable effectiveness regarding responder rates, indicating a potential network disruption.

Materials for Implantable Surface Electrode Arrays: Current Status and Future Directions

Surface electrode arrays are mainly fabricated from rigid or elastic materials, and precisely manipulated ductile metal films, which offer limited stretchability. However, the living tissues to which they are applied are nonlinear viscoelastic materials, which can undergo significant mechanical deformation in dynamic biological environments. Further, the same arrays and compositions are often repurposed for vastly different tissues rather than optimizing the materials and mechanical properties of the implant for the target application. By first characterizing the desired biological environment, and then designing a technology for a particular organ, surface electrode arrays may be more conformable, and offer better interfaces to tissues while causing less damage. Here, the various materials used in each component of a surface electrode array are first reviewed, and then electrically active implants in three specific biological systems, the nervous system, the muscular system, and skin, are described. Finally, the fabrication of next-generation surface arrays that overcome current limitations is discussed.

Radiomic features as a risk factor for early postoperative seizure in patients with meningioma

PURPOSE

This study aim to identify the clinical risk factors of and to develop a radiomics-based predictive model for early postoperative seizure.

METHODS

We retrospectively assessed 322 operative patients with meningioma who met the inclusion criteria from January 2014 to December 2016 at The First Affiliated Hospital of Wenzhou Medical University. Univariate and multivariate analyses were performed to determine the predictive value of clinical variables. Magnetic resonance imaging (MRI) was performed to obtain the radiomic score (Rscore) for early postoperative seizure. Radiological features were evaluated using the AK software. The minimal redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods were used to assess for radiomic features, and the Rscore was obtained based on radiomic characteristics using a specific formula.

RESULTS

In total, 260 patients who met the inclusion criteria were finally enrolled in this study. Among them, 20 experienced early postoperative seizure. Logistic regression analysis showed that Rscore was associated with a significantly high risk of seizure (p<0.000). Receiver operating characteristic (ROC) curve analysis revealed that the area under the ROC curve of the Rscore was 0.92 (95% confidence interval: 0.853-0.987). The model had a high accuracy for predicting early postoperative seizure.

CONCLUSIONS

The Rscore was found to be associated with a high risk of early postoperative seizures. Thus, a higher Rscore (>-1.644) can identify high-risk patients requiring intensive care.

Long-term brain network reorganization predicts responsive neurostimulation outcomes for focal epilepsy

Responsive neurostimulation (RNS) devices, able to detect imminent seizures and to rapidly deliver electrical stimulation to the brain, are effective in reducing seizures in some patients with focal epilepsy. However, therapeutic response to RNS is often slow, is highly variable, and defies prognostication based on clinical factors. A prevailing view holds that RNS efficacy is primarily mediated by acute seizure termination; yet, stimulations greatly outnumber seizures and occur mostly in the interictal state, suggesting chronic modulation of brain networks that generate seizures. Here, using years-long intracranial neural recordings collected during RNS therapy, we found that patients with the greatest therapeutic benefit undergo progressive, frequency-dependent reorganization of interictal functional connectivity. The extent of this reorganization scales directly with seizure reduction and emerges within the first year of RNS treatment, enabling potential early prediction of therapeutic response. Our findings reveal a mechanism for RNS that involves network plasticity and may inform development of next-generation devices for epilepsy.

Accuracy of omni-planar and surface casting of epileptiform activity for intracranial seizure localization

OBJECTIVE

Intracranial electroencephalography (ICEEG) recordings are performed for seizure localization in medically refractory epilepsy. Signal quantifications such as frequency power can be projected as heatmaps on personalized three-dimensional (3D) reconstructed cortical surfaces to distill these complex recordings into intuitive cinematic visualizations. However, simultaneously reconciling deep recording locations and reliably tracking evolving ictal patterns remain significant challenges.

METHODS

We fused oblique magnetic resonance imaging (MRI) slices along depth probe trajectories with cortical surface reconstructions and projected dynamic heatmaps using a simple mathematical metric of epileptiform activity (line-length). This omni-planar and surface casting of epileptiform activity approach (OPSCEA) thus illustrated seizure onset and spread among both deep and superficial locations simultaneously with minimal need for signal processing supervision. We utilized the approach on 41 patients at our center implanted with grid, strip, and/or depth electrodes for localizing medically refractory seizures. Peri-ictal data were converted into OPSCEA videos with multiple 3D brain views illustrating all electrode locations. Five people of varying expertise in epilepsy (medical student through epilepsy attending level) attempted to localize the seizure-onset zones.

RESULTS

We retrospectively compared this approach with the original ICEEG study reports for validation. Accuracy ranged from 73.2% to 97.6% for complete or overlapping onset lobe(s), respectively, and ~56.1% to 95.1% for the specific focus (or foci). Higher answer certainty for a given case predicted better accuracy, and scorers had similar accuracy across different training levels.

SIGNIFICANCE

In an era of increasing stereo-EEG use, cinematic visualizations fusing omni-planar and surface functional projections appear to provide a useful adjunct for interpreting complex intracranial recordings and subsequent surgery planning.