Dataset Information

Feasibility of multimodal 3D neuroimaging to guide implantation of intracranial EEG electrodes.

ABSTRACT:

Background

Since intracranial electrode implantation has limited spatial sampling and carries significant risk, placement has to be effective and efficient. Structural and functional imaging of several different modalities contributes to localising the seizure onset zone (SoZ) and eloquent cortex. There is a need to summarise and present this information throughout the pre/intra/post-surgical course.

Methods

We developed and implemented a multimodal 3D neuroimaging (M3N) pipeline to guide implantation of intracranial EEG (icEEG) electrodes. We report the implementation of the pipeline for operative planning and a description of its use in clinical decision-making.

Results

The results of intraoperative application of the M3N pipeline demonstrated clinical benefits in all 15 implantation surgeries assessed. The M3N software was used to simulate placement of intracranial electrodes in 2 cases. The key benefits of using the M3N pipeline are illustrated in 3 representative case reports.

Conclusion

We have demonstrated feasibility of the developed intraoperative M3N pipeline which serves as a prototype for clinical implementation. Further validity studies with larger sample groups are required to determine the utility of M3N in routine surgical practice.

SUBMITTER: Rodionov R

PROVIDER: S-EPMC3830177 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Feasibility of multimodal 3D neuroimaging to guide implantation of intracranial EEG electrodes.

Rodionov Roman R Vollmar Christian C Nowell Mark M Miserocchi Anna A Wehner Tim T Micallef Caroline C Zombori Gergely G Ourselin Sebastien S Diehl Beate B McEvoy Andrew W AW Duncan John S JS

Epilepsy research 20130814 1-2

<h4>Background</h4>Since intracranial electrode implantation has limited spatial sampling and carries significant risk, placement has to be effective and efficient. Structural and functional imaging of several different modalities contributes to localising the seizure onset zone (SoZ) and eloquent cortex. There is a need to summarise and present this information throughout the pre/intra/post-surgical course.<h4>Methods</h4>We developed and implemented a multimodal 3D neuroimaging (M3N) pipeline ...[more]

PMID: 24029810

Similar Datasets

Project description:OBJECTIVE:Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. APPROACH:Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient's recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. MAIN RESULTS:A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. SIGNIFICANCE:These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring.

Project description:IntroductionAlthough deep brain stimulation is nowadays performed worldwide, the biomechanical aspects of electrode implantation received little attention, mainly as physicians focused on the medical aspects, such as the optimal indication of the surgical procedure, the positive and adverse effects, and the long-term follow-up. We aimed to describe electrode deformations and brain shift immediately after implantation, as it may highlight our comprehension of intracranial and intracerebral mechanics.Materials and methodsSixty electrodes of 30 patients suffering from severe symptoms of Parkinson's disease and essential tremor were studied. They consisted of 30 non-directional electrodes and 30 directional electrodes, implanted 42 times in the subthalamus and 18 times in the ventrolateral thalamus. We computed the x (transversal), y (anteroposterior), z (depth), torsion, and curvature deformations, along the electrodes from the entrance point in the braincase. The electrodes were modelized from the immediate postoperative CT scan using automatic voxel thresholding segmentation, manual subtraction of artifacts, and automatic skeletonization. The deformation parameters were computed from the curve of electrodes using a third-order polynomial regression. We studied these deformations according to the type of electrodes, the clinical parameters, the surgical-related accuracy, the brain shift, the hemisphere and three tissue layers, the gyration layer, the white matter stem layer, and the deep brain layer (type I error set at 5%).ResultsWe found that the implanted first hemisphere coupled to the brain shift and the stiffness of the type of electrode impacted on the electrode deformations. The deformations were also different according to the tissue layers, to the electrode type, and to the first-hemisphere-brain-shift effect.ConclusionOur findings provide information on the intracranial and brain biomechanics and should help further developments on intracerebral electrode design and surgical issues.

Project description:Recent advances in dry electrodes technology have facilitated the recording of EEG in situations not previously possible, thanks to the relatively swift electrode preparation and avoidance of applying gel to subject's hair. However, to become a true alternative, these systems should be compared to state-of-the-art wet EEG systems commonly used in clinical or research applications. In our study, we conducted a systematic comparison of electrodes application speed, subject comfort, and most critically electrophysiological signal quality between the conventional and wired Biosemi EEG system using wet active electrodes and the compact and wireless F1 EEG system consisting of dry passive electrodes. All subjects (n = 27) participated in two recording sessions on separate days, one with the wet EEG system and one with the dry EEG system, in which the session order was counterbalanced across subjects. In each session, we recorded their EEG during separate rest periods with eyes open and closed followed by two versions of a serial visual presentation target detection task. Each task component allows for a neural measure reflecting different characteristics of the data, including spectral power in canonical low frequency bands, event-related potential components (specifically, the P3b), and single trial classification based on machine learning. The performance across the two systems was similar in most measures, including the P3b amplitude and topography, as well as low frequency (theta, alpha, and beta) spectral power at rest. Both EEG systems performed well above chance in the classification analysis, with a marginal advantage of the wet system over the dry. Critically, all aforementioned electrophysiological metrics showed significant positive correlations (r = 0.54-0.89) between the two EEG systems. This multitude of measures provides a comprehensive comparison that captures different aspects of EEG data, including temporal precision, frequency domain as well as multivariate patterns of activity. Taken together, our results indicate that the dry EEG system used in this experiment can effectively record electrophysiological measures commonly used across the research and clinical contexts with comparable quality to the conventional wet EEG system.

Dataset Information

Feasibility of multimodal 3D neuroimaging to guide implantation of intracranial EEG electrodes.

Background

Methods

Results

Conclusion

Publications

Feasibility of multimodal 3D neuroimaging to guide implantation of intracranial EEG electrodes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets