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

Sweet, Jennifer A.; Hdeib, Alia; Sloan, Andrew E.; Miller, Jonathan P.

doi:10.1111/epi.12447

Cited by 23 publications

(20 citation statements)

References 21 publications

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“…The majority of ECoG recordings of tumoral epilepsy are performed intraoperatively interic-tally (Sugano et al, 2007; Duffau, 2013), although some groups have also advocated for extraoperative ictal ECoG with subdural grid and strip electrodes in tumor-related epilepsy surgery (Sweet et al, 2013). While extraoperative ictal recordings are critical in many cases of nonlesional focal epilepsy to localize the epileptogenic zone de novo , the site of seizure onset in tumor-associated epilepsy is presumed a priori to be in the peritumoral region.…”

Section: Surgicaltherapymentioning

confidence: 99%

Epilepsy and brain tumors

Englot

Chang

Vecht

2016

Handbook of Clinical Neurology

173

138

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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.

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Section: Surgicaltherapymentioning

confidence: 99%

Epilepsy and brain tumors

Englot

Chang

Vecht

2016

Handbook of Clinical Neurology

173

138

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“…Following fusion of the pre-and postoperative anatomical images, electrodes that have been surgically placed on the cortical surface occasionally appear "buried" within the cortical tissue, sometimes more than a centimeter deep [38][39][40][41][42][43] . This electrode displacement is typically due to "brain shift", the inward sinking of the brain post-implant most commonly observed with electrocorticographic surface grid electrodes.…”

Section: Human Intracranial Datamentioning

confidence: 99%

Integrated analysis of anatomical and electrophysiological human intracranial data

Stolk

Griffin

Meij

et al. 2017

Preprint

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The exquisite spatiotemporal precision of human intracranial EEG recordings (iEEG) permits characterizing neural processing with a level of detail that is inaccessible to scalp-EEG, MEG, or fMRI. However, the same qualities that make iEEG an exceptionally powerful tool also present unique challenges. Until now, the fusion of anatomical data (MRI and CT images) with the electrophysiological data and its subsequent analysis has relied on technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that addresses the complexities associated with human iEEG, providing complete transparency and flexibility in the evolution of raw data into illustrative representations. The protocol is directly integrated with 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 employed by a large research community. We demonstrate the protocol for an example complex iEEG data set to provide an intuitive and rapid approach to dealing with both neuroanatomical information and large electrophysiological data sets. We explain how the protocol can be largely automated, taking under an hour to complete, and readily adjusted to iEEG data sets with other characteristics.

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“…the hippocampus) that are minimally affected by brain shift, this is likely not a serious shortcoming. Moreover, depth-only implants (i.e., stereotactic EEG) generally produce negligible brain shift as a craniotomy is not performed (Gonzalez-Martinez et al, 2014;Sweet, Hdeib, Sloan, & Miller, 2013).…”

Section: Electrode Localizationmentioning

confidence: 99%

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

Groppe

Bickel

Dykstra

et al. 2016

Preprint

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BackgroundIntracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, much of the value of such data is unrealized as many labs lack tools for precisely localizing electrodes relative to anatomy and to other functional measures. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. New MethodThe iELVis pipeline extends existing tools (BioImage Suite, FSL, and FreeSurfer) for localizing electrode locations in CT or MR scans. Once electrode locations are identified in postimplant neuroimaging, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy. iELVis then supports interactive visualization on 3D surfaces or in 2D slices alongside functional neuroimaging data. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. ResultsIt takes 30-60 minutes of user time and 12-24 hours of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's co-registered visualization functionality by overlaying concordant results from three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and fMRI). Comparison with Existing MethodsiELVis standardizes existing approaches within a common pipeline, while advancing and combining the state of the art techniques in (i) brain-shift correction, (ii) atlas functionality, and (iii) multimodal visualization for human intracranial data. ConclusionsiELVis promises to speed 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

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

Cited by 23 publications

References 21 publications

Epilepsy and brain tumors

Epilepsy and brain tumors

Integrated analysis of anatomical and electrophysiological human intracranial data

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

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