Depths and grids in brain tumors: implantation strategies, techniques, and complications

iEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices

OBJECTIVE

Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms.

METHODS

We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts.

RESULTS

We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations.

SIGNIFICANCE

iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

iEEG-recon: A Fast and Scalable Pipeline for Accurate Reconstruction of Intracranial Electrodes and Implantable Devices

Background

Collaboration between epilepsy centers is essential to integrate multimodal data for epilepsy research. Scalable tools for rapid and reproducible data analysis facilitate multicenter data integration and harmonization. Clinicians use intracranial EEG (iEEG) in conjunction with non-invasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. These tasks are still performed manually in many epilepsy centers. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms.

Methods

We created iEEG-recon, a scalable electrode reconstruction pipeline for semi-automatic iEEG annotation, rapid image registration, and electrode assignment on brain MRIs. Its modular architecture includes three modules: a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon, and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts.

Results

We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography (ECoG) and stereoelectroencephalography (SEEG) cases with a 10 minute running time per case, and ~20 min for semi-automatic electrode labeling. iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and post-implant T1-MRI visual inspections. Our use of ANTsPyNet deep learning approach for brain segmentation and electrode classification was consistent with the widely used Freesurfer segmentation.

Discussion

iEEG-recon is a valuable tool for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting efficient data analysis, and integration into clinical workflows. The tool's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide. Comprehensive documentation is available at https://ieeg-recon.readthedocs.io/en/latest/.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

Presurgical language mapping in bilingual children using transcranial magnetic stimulation: illustrative case

BACKGROUND

Presurgical mapping of eloquent cortex in young patients undergoing neurosurgery is critical but presents challenges unique to the pediatric population, including motion artifact, noncompliance, and sedation requirements. Furthermore, as bilingualism in children increases, functional mapping of more than one language is becoming increasingly critical. Transcranial magnetic stimulation (TMS), a noninvasive brain stimulation technique, is well suited to evaluate language areas in children since it does not require the patient to remain still during mapping.

OBSERVATIONS

A 13-year-old bilingual male with glioblastoma multiforme involving the left parietal lobe and deep occipital white matter underwent preoperative language mapping using magnetic resonance imaging-guided TMS. Language-specific cortices were successfully identified in both hemispheres. TMS findings aided in discussing with the family the risks of postsurgical deficits of tumor resection; postoperatively, the patient had intact bilingual speech and was referred for chemotherapy and radiation.

LESSONS

The authors’ findings add to the evolving case for preoperative dual language mapping in bilingual neurosurgical candidates. The authors illustrate the feasibility and utility of TMS as a noninvasive functional mapping tool in this child. TMS is safe, effective, and can be used for preoperative mapping of language cortex in bilingual children to aid in surgical planning and discussion with families.

Analysis of intraoperative human brain tissue transcriptome reveals putative risk genes and altered molecular pathways in glioma-related seizures

BACKGROUND

The pathogenesis of glioma-related seizures (GRS) is poorly understood. Here in, we aim to identify putative molecular pathways that lead to the development of GRS.

METHODS

We determined brain transcriptome from intraoperative human brain tissue of patients with either GRS, glioma without seizures (non-GRS), or with idiopathic temporal lobe epilepsy (iTLE). We performed transcriptome-wide comparisons between disease groups tissue from non-epileptic controls (non-EC) to identify differentially-expressed genes (DEG). We compared DEGs to identify those that are specific or common to the groups. Through a gene ontology analysis, we identified molecular pathways enriched for genes with a Log-fold change ≥1.5 or ≤-1.5 and p-value <0.05 compared to non-EC.

RESULTS

We identified 110 DEGs that are associated with GRS vs. non-GRS: 80 genes showed high and 30 low expression in GRS. There was significant overexpression of genes involved in cell-to-cell and glutamatergic signaling (CELF4, SLC17A7, and CAMK2A) and down-regulation of genes involved immune-trafficking (CXCL8, H19, and VEGFA). In the iTLE vs GRS analysis, there were 1098 DEGs: 786 genes were overexpressed and 312 genes were underexpressed in the GRS samples. There was significant enrichment for genes considered markers of oncogenesis (GSC, MYBL2, and TOP2A). Further, there was down-regulation of genes involved in the glutamatergic neurotransmission (vesicular glutamate transporter-2) in the GRS vs. iTLE samples.

CONCLUSIONS

We identified a number of altered processes such as cell-to-cell signaling and interaction, inflammation-related, and glutamatergic neurotransmission in the pathogenesis of GRS. Our findings offer a new landscape of targets to further study in the fields of brain tumors and seizures.

Gray Matter Sampling Differences Between Subdural Electrodes and Stereoelectroencephalography Electrodes

Objective: Stereoelectroencephalography (SEEG) has seen a recent increase in popularity in North America; however, concerns regarding the spatial sampling capabilities of SEEG remain. We aimed to quantify and compare the spatial sampling of subdural electrode (SDE) and SEEG implants.

Methods: Patients with drug-resistant epilepsy who underwent invasive monitoring were included in this retrospective case-control study. Ten SEEG cases were compared with ten matched SDE cases based on clinical presentation and pre-implantation hypothesis. To quantify gray matter sampling, MR and CT images were coregistered and a 2.5mm radius sphere was superimposed over the center of each electrode contact. The estimated recording volume of gray matter was defined as the cortical voxels within these spherical models. Paired t-tests were performed to compare volumes and locations of SDE and SEEG recording. A Ripley's K-function analysis was performed to quantify differences in spatial distributions.

Results: The average recording volume of gray matter by each individual contact was similar between the two modalities. SEEG implants sampled an average of 20% more total gray matter, consisted of an average of 17% more electrode contacts, and had 77% more of their contacts covering gray matter within sulci. Insular coverage was only achieved with SEEG. SEEG implants generally consist of discrete areas of dense local coverage scattered across the brain; while SDE implants cover relatively contiguous areas with lower density recording.

Significance: Average recording volumes per electrode contact are similar for SEEG and SDE, but SEEG may allow for greater overall volumes of recording as more electrodes can be routinely implanted. The primary difference lies in the location and distribution of gray matter than can be sampled. The selection between SEEG and SDE implantation depends on sampling needs of the invasive implant.

Biomarkers of Seizure Activity in Patients With Intracranial Metastases and Gliomas: A Wide Range Study of Correlated Regions of Interest

Introduction: Studies quantifying cortical metrics in brain tumor patients who present with seizures are limited. The current investigation assesses morphometric/volumetric differences across a wide range of anatomical regions, including temporal and extra-temporal, in patients with gliomas and intracranial metastases (IMs) presenting with seizures that could serve as a biomarker in the identification of seizure expression and serve as a neuronal target for mitigation.

Methods: In a retrospective design, the MR sequences of ninety-two tumor patients [55% gliomas; 45% IM] and 34 controls were subjected to sophisticated morphometric and volumetric assessments using BrainSuite and MATLAB modules. We examined 103 regions of interests (ROIs) across eight distinct cortical categories of interests (COI) [gray matter, white matter; total volume, CSF; cortical areas: inner, mid, pial; cortical thickness]. The primary endpoint was quantifying and identifying ROIs with significant differences in z-scores based upon the presence of seizures. Feature selection employing neighborhood component analysis (NCA) determined the ROI within each COI having the highest significance/weight in the differentiation of seizure vs. non-seizure patients harboring brain tumor.

Results: Overall, the mean age of the cohort was 58.0 ± 12.8 years, and 45% were women. The prevalence of seizures in tumor patients was 28%. Forty-two ROIs across the eight pre-defined COIs had significant differences in z-scores between tumor patients presenting with and without seizures. The NCA feature selection noted the volume of pars-orbitalis and right middle temporal gyrus to have the highest weight in differentiating tumor patients based on seizures for three distinct COIs [GM, total volume, and CSF volume] and white matter, respectively. Left-sided transverse temporal gyrus, left precuneus, left transverse temporal, and left supramarginal gyrus were associated with having the highest weight in the differentiation of seizure vs. non-seizure in tumor patients for morphometrics relating to cortical areas in the pial, inner and mid regions and cortical thickness, respectively.

Conclusion: Our study elucidates potential biomarkers for seizure targeting in patients with gliomas and IMs based upon morphometric and volumetric assessments. Amongst the widespread brain regions examined in our cohort, pars orbitalis, supramarginal and temporal gyrus (middle, transverse), and the pre-cuneus contribute a maximal potential for differentiation of seizure patients from non-seizure.

Surgical treatment of low-grade brain tumors associated with epilepsy

OBJECTIVE

To explore the strategy of surgical treatment of low-grade brain tumors associated with epilepsy.

METHODS

Clinical data of 158 patients with low-grade brain tumors were collected from January 2011 to December 2017 in Guangdong Sanjiu brain hospital. All patients received Preoperative evaluation. Lesion site: 18 cases were located in multiple cerebral lobes, 10 cases were in the functional zones, 130 cases were in the non-functional zones (including 74 cases were in the medial of temporal lobe). The surgical strategy included subtotal resection, gross-total resection and enlarged resection. Postoperative effects were evaluated by Engel classification.

RESULTS

A total of 158 patients underwent surgical treatment, among these patients, only 1 patient underwent intracranial electrode implantation. Surgical methods: 34 cases of subtotal resection, 3 cases of gross-total resection, 119 cases of enlarged resection (including Anterior temporal lobectomy in 74 cases) and 2 case of Selective hippocampal amygdalectomy. The final pathology suggested that there are 74 cases of ganglionglioma, 25 cases of dysembryoplastic neuroepithelial tumors, 9 cases of pilocytic astrocytoma, 16 cases of oligodendroglioma, 10 cases of pleomorphic xanthoastrocytoma, 4 case of diffuse astrocytoma, 9 cases of unclassified astrocytoma, 11 case of oligoastrocytoma. The follow-up time was between 1 and 7 years, with an average of 3.44±1.77 years. Postoperative recovery: 147 patients had an Engel Class I outcome, 10 patients were in Engel Class II, 1 patient was in Class IV.

CONCLUSION

The strategy of surgical treatment of low-grade brain tumors associated with epilepsy should pay more attention to the preoperative assessment of the epileptogenic zone. The tumor is not exactly the same as the epileptogenic zone, and the strategy of surgical treatment depends on the tumor feature as well as whether it was located in temporal lobe or involved in functional areas.

iEEGview: an open-source multifunction GUI-based Matlab toolbox for localization and visualization of human intracranial electrodes

OBJECTIVE

The precise localization of intracranial electrodes is a fundamental step relevant to the analysis of intracranial electroencephalography (iEEG) recordings in various fields. With the increasing development of iEEG studies in human neuroscience, higher requirements have been posed on the localization process, resulting in urgent demand for more integrated, easy-operation and versatile tools for electrode localization and visualization. With the aim of addressing this need, we develop an easy-to-use and multifunction toolbox called iEEGview, which can be used for the localization and visualization of human intracranial electrodes.

APPROACH

iEEGview is written in Matlab scripts and implemented with a GUI. From the GUI, by taking only pre-implant MRI and post-implant CT images as input, users can directly run the full localization pipeline including brain segmentation, image co-registration, electrode reconstruction, anatomical information identification, activation map generation and electrode projection from native brain space into common brain space for group analysis. Additionally, iEEGview implements methods for brain shift correction, visual location inspection on MRI slices and computation of certainty index in anatomical label assignment.

MAIN RESULTS

All the introduced functions of iEEGview work reliably and successfully, and are tested by images from 28 human subjects implanted with depth and/or subdural electrodes.

SIGNIFICANCE

iEEGview is the first public Matlab GUI-based software for intracranial electrode localization and visualization that holds integrated capabilities together within one pipeline. iEEGview promotes convenience and efficiency for the localization process, provides rich localization information for further analysis and offers solutions for addressing raised technical challenges. Therefore, it can serve as a useful tool in facilitating iEEG studies.

Integrated analysis of anatomical and electrophysiological human intracranial data

Human intracranial electroencephalography (iEEG) recordings provide data with much greater spatiotemporal precision than is possible from data obtained using scalp EEG, magnetoencephalography (MEG), or functional MRI. Until recently, the fusion of anatomical data (MRI and computed tomography (CT) images) with electrophysiological data and their subsequent analysis have required the use of technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that enables complex raw human iEEG data to be converted into more readily comprehensible illustrative representations. The protocol uses an open-source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and used by a large research community. In this protocol, we describe how to analyze complex iEEG datasets by providing an intuitive and rapid approach that can handle both neuroanatomical information and large electrophysiological datasets. We provide a worked example using an example dataset. We also explain how to automate the protocol and adjust the settings to enable analysis of iEEG datasets with other characteristics. The protocol can be implemented by a graduate student or postdoctoral fellow with minimal MATLAB experience and takes approximately an hour to execute, excluding the automated cortical surface extraction.

Safety and Utility of Hybrid Depth Electrodes for Seizure Localization and Single-Unit Neuronal Recording

BACKGROUND

Invasive electrode monitoring provides more precise localization of epileptogenic foci in patients with medically refractory epilepsy. The use of hybrid depth electrodes that include microwires for simultaneous single-neuron monitoring is becoming more widespread.

OBJECTIVE

To determine the safety and utility of hybrid depth electrodes for intracranial monitoring of medically refractory epilepsy.

METHODS

We reviewed the medical charts of 53 cases of medically refractory epilepsy operated on from 2006 to 2017, where both non-hybrid and hybrid microwire depth electrodes were used for intracranial monitoring. We assessed the localization accuracy and complications that arose to assess the relative safety and utility of hybrid depth electrodes compared with standard electrodes.

RESULTS

A total of 555 electrodes were implanted in 52 patients. The overall per-electrode complication rate was 2.3%, with a per-case complication rate of 20.8%. There were no infections or deaths. Serious or hemorrhagic complications occurred in 2 patients (0.4% per-electrode risk). Complications did not correlate with the use of any particular electrode type, and hybrids were equally as reliable as standard electrodes in localizing seizure onset zones.

CONCLUSIONS

Hybrid depth electrodes appear to be as safe and effective as standard depth electrodes for intracranial monitoring and provide unique opportunities to study the human brain at single-neuron resolution.

iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data

BACKGROUND

Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain.

RESULTS

It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive.

CONCLUSIONS

iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg.

Usage of SWI (susceptibility weighted imaging) acquired at 7T for qualitative evaluation of temporal lobe epilepsy patients with histopathological and clinical correlation: An initial pilot study

OBJECTIVES

Ultra high field MRI at 7T is able to provide much improved spatial and contrast resolution which may aid in the diagnosis of hippocampal abnormalities. This paper presents a preliminary experience on qualitative evaluation of 7T MRI in temporal lobe epilepsy patients with a focus on comparison to histopathology.

METHODS

7T ultra high field MRI data, using T1-weighted, T2*-weighted and susceptibility-weighted images (SWI), were acquired for 13 patients with drug resistant temporal lobe epilepsy (TLE) during evaluation for potential epilepsy surgery. Qualitative evaluation of the imaging data for scan quality and presence of hippocampal and temporal lobe abnormalities were scored while blinded to the clinical data. Correlation of imaging findings with the clinical data was performed. Blinded evaluation of 1.5T scans was also performed.

RESULTS

On the 7T MRI findings, eight out of 13 cases demonstrated concordance with the clinically suspected TLE. Among these concordant cases, three exhibited supportive abnormal 7T MRI findings which were not detected by the clinical 1.5T MRI. Of the ten cases that progressed to epilepsy surgery, seven showed concordance between 7T MRI findings and histopathology; of these, four cases had hippocampal sclerosis. SWI had the highest concordance with the clinical and histopathological findings. Similar clinical and histopathological concordance was found with 1.5T MRI.

CONCLUSIONS

There was moderate and high concordance between the 7T imaging findings with the clinical data and histopathology respectively.

Epilepsy and brain tumors

Seizures are common in patients with brain tumors, and epilepsy can significantly impact patient quality of life. Therefore, a thorough understanding of rates and predictors of seizures, and the likelihood of seizure freedom after resection, is critical in the treatment of brain tumors. Among all tumor types, seizures are most common with glioneuronal tumors (70-80%), particularly in patients with frontotemporal or insular lesions. Seizures are also common in individuals with glioma, with the highest rates of epilepsy (60-75%) observed in patients with low-grade gliomas located in superficial cortical or insular regions. Approximately 20-50% of patients with meningioma and 20-35% of those with brain metastases also suffer from seizures. After tumor resection, approximately 60-90% are rendered seizure-free, with most favorable seizure outcomes seen in individuals with glioneuronal tumors. Gross total resection, earlier surgical therapy, and a lack of generalized seizures are common predictors of a favorable seizure outcome. With regard to anticonvulsant medication selection, evidence-based guidelines for the treatment of focal epilepsy should be followed, and individual patient factors should also be considered, including patient age, sex, organ dysfunction, comorbidity, or cotherapy. As concomitant chemotherapy commonly forms an essential part of glioma treatment, enzyme-inducing anticonvulsants should be avoided when possible. Seizure freedom is the ultimate goal in the treatment of brain tumor patients with epilepsy, given the adverse effects of seizures on quality of life.

Intracranial EEG analysis in tumor-related epilepsy: Evidence of distant epileptic abnormalities

OBJECTIVE

In patients with tumor-related epilepsy (TRE), surgery traditionally focuses on tumor resection; but identification and removal of associated epileptogenic zone may improve seizure outcome. Here, we study spatial relationship of tumor and seizure onset and early spread zone (SOSz). We also perform quantitative analysis of interictal epileptiform activities in patients with both TRE and non-lesional epilepsy in order to better understand the electrophysiological basis of epileptogenesis.

METHODS

Twenty-five patients (11 with TRE and 14 with non-lesional epilepsy) underwent staged surgery using intracranial electrodes. Tumors were outlined on MRI and images were coregistered with post-implantation CT images. For each electrode, distance to the nearest tumor margin was measured. Electrodes were categorized based on distance from tumor and involvement in seizure. Quantitative EEG analysis studying frequency, amplitude, power, duration and slope of interictal spikes was performed.

RESULTS

At least part of the SOSz was located beyond 1.5 cm from the tumor margin in 10/11 patients. Interictally, spike frequency and power were higher in the SOSz and spikes near tumor were smaller and less sharp. Interestingly, peritumoral electrodes had the highest spike frequencies and sharpest spikes, indicating greatest degree of epileptic synchrony. A complete resection of the SOSz resulted in excellent seizure outcome.

CONCLUSIONS

Seizure onset and early spread often involves brain areas distant from the tumor.

SIGNIFICANCE

Utilization of epilepsy surgery approach for TRE may provide better seizure outcome and study of the intracranial EEG may provide insight into pathophysiology of TRE.

Seizure management in patients with gliomas

Seizures represent a major cause of morbidity in patients diagnosed with brain tumors. Seizures in patients with gliomas are disruptive, impact on quality of life; autonomy; the capacity to operate motor vehicles and opportunities for work. The management of seizures in patients with brain tumors is complex and ideally managed in a multidisciplinary fashion. In addition to antiepileptic drugs, surgery, chemotherapy and radiotherapy have potential roles in the management of a glioma patient with intractable epilepsy. The successful management of seizures in patients with brain tumors is possible, it provides considerable benefits in terms of quality of life and should remain a central goal in patient management.

Tumor-related epilepsy and epilepsy surgery

Tumor-related epilepsy (TRE) is a major etiologic category of epilepsy. TRE is heterogeneous, and the epidemiology, pathology, pathophysiology, clinical features, treatment, and outcomes vary accordingly. In addition, treatment imperatives vary between almost purely epilepsy considerations and those that are primarily oncologic. Often, there is no clear separation of imperatives, and there is a relatively scant evidence base that underpins management decisions in such cases. Given a diverse molecular as well as clinical landscape and the rapid pace with which new knowledge accrues, there are relatively few recent literature resources on TRE that provide neurologists, neurosurgeons, epileptologists, and oncologists with an up-to-date, state-of-the-art review of the field in all of its important aspects. The proceedings of the Sixth International Epilepsy Colloquium in Cleveland in Ohio, U.S.A., in May 2013 on Tumoral Epilepsy and Epilepsy Surgery address, at least in part, several TRE aspects crucial to modern epilepsy and oncology practice.