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Sun Y, Shen A, Sun J, Du C, Chen X, Wang Y, Pei W, Gao X. Minimally Invasive Local-Skull Electrophysiological Modification With Piezoelectric Drill. IEEE Trans Neural Syst Rehabil Eng 2022; 30:2042-2051. [PMID: 35857723 DOI: 10.1109/tnsre.2022.3192543] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The research on non-invasive BCI is nowadays hitting the bottleneck due to the humble quality of scalp EEG signals. Whereas invasive solutions that offer higher signal quality in contrast are suffocated in their spreading because of the potential surgical complication and health risks caused by electrode implantation. Therefore, it puts forward a necessity to explore a scheme that could both collect high-quality EEG signals and guarantee high-level operation safety.This study proposed a Minimally Invasive Local-skull Electrophysiological Modification method to improve scalp EEG signals qualities at specific brain regions. Six eight-month-old SD rats were used for in vivo verification experiment. A hole with a diameter of about 500 micrometers was drilled in the skull above the visual cortex of rats. Significant changes in rsEEG and SSVEP signals before and after modification were observed. After modification, the skull impedance of rats decreases by about 84 %, the average maximum bandwidth of rsEEG increase by 57 %, and the broadband SNR of SSVEP is increased by 5.13 dB. The time of piezoelectric drilling operation is strictly controlled under 30 seconds for each rat to prevent possible brain damage from overheating. Compared with traditional invasive procedures such as ECoG, Minimally Invasive Local-skull Electrophysiological Modification operation time is shorter and no electrode implantation is needed while it remarkably boosts the scalp EEG signal quality. This technical solution has the potential to replace the use of ECoG in certain application scenarios and further invigorate studies in the field of scalp EEG in the future.
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Rossi Sebastiano D, Varotto G, Sattin D, Franceschetti S. EEG Assessment in Patients With Disorders of Consciousness: Aims, Advantages, Limits, and Pitfalls. Front Neurol 2021; 12:649849. [PMID: 33868153 PMCID: PMC8047055 DOI: 10.3389/fneur.2021.649849] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 02/19/2021] [Indexed: 11/13/2022] Open
Abstract
This study presents a brief review of literature exploring simple EEG-polygraphic examinations and procedures that can be carried out at a patient's bedside. These include EEG with a common electrode array and sleep evaluation. The review briefly discusses more complex analytical techniques, such as the application of advanced EEG signal processing methods developed by our research group, to define what type of consistent markers are suitable for clinical use or to better understand complex patient conditions. These advanced analytical techniques aim to detect relevant EEG-based markers that could be useful in evaluating patients and predicting outcomes. These data could contribute to future developments in research.
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Affiliation(s)
- Davide Rossi Sebastiano
- Department of Neurophysiopathology, Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta, Milan, Italy
| | - Giulia Varotto
- Department of Neurophysiopathology, Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta, Milan, Italy
- Epilepsy Unit, Bioengineering Group, Fondazione I.R.C.C.S. istituto Neurologico Carlo Besta, Milan, Italy
| | - Davide Sattin
- Department of Neurology, Public Health and Disability, Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta, Milan, Italy
| | - Silvana Franceschetti
- Department of Neurophysiopathology, Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta, Milan, Italy
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Lew S, Hämäläinen MS, Ahlfors SP, Okada Y. Influence of unfused cranial bones on magnetoencephalography signals in human infants. Clin Neurophysiol 2020; 132:708-719. [PMID: 33571879 DOI: 10.1016/j.clinph.2020.11.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 11/12/2020] [Accepted: 11/17/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To clarify the effects of unfused cranial bones on magnetoencephalography (MEG) signals during early development. METHODS In a simulation study, we compared the MEG signals over a spherical head model with a circular hole mimicking the anterior fontanel to those over the same head model without the fontanel for different head and fontanel sizes with varying skull thickness and conductivity. RESULTS The fontanel had small effects according to three indices. The sum of differences in signal over a sensor array due to a fontanel, for example, was < 6% of the sum without the fontanel. However, the fontanel effects were extensive for dipole sources deep in the brain or outside the fontanel for larger fontanels. The effects were comparable in magnitude for tangential and radial sources. Skull thickness significantly increased the effect, while skull conductivity had minor effects. CONCLUSION MEG signal is weakly affected by a fontanel. However, the effects can be extensive and significant for radial sources, thicker skull and large fontanels. The fontanel effects can be intuitively explained by the concept of secondary sources at the fontanel wall. SIGNIFICANCE The minor influence of unfused cranial bones simplifies MEG analysis, but it should be considered for quantitative analysis.
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Affiliation(s)
- Seok Lew
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Matti S Hämäläinen
- Harvard Medical School, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Seppo P Ahlfors
- Harvard Medical School, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Yoshio Okada
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA.
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Piastra MC, Nüßing A, Vorwerk J, Bornfleth H, Oostenveld R, Engwer C, Wolters CH. The Discontinuous Galerkin Finite Element Method for Solving the MEG and the Combined MEG/EEG Forward Problem. Front Neurosci 2018; 12:30. [PMID: 29456487 PMCID: PMC5801436 DOI: 10.3389/fnins.2018.00030] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 01/15/2018] [Indexed: 11/17/2022] Open
Abstract
In Electro- (EEG) and Magnetoencephalography (MEG), one important requirement of source reconstruction is the forward model. The continuous Galerkin finite element method (CG-FEM) has become one of the dominant approaches for solving the forward problem over the last decades. Recently, a discontinuous Galerkin FEM (DG-FEM) EEG forward approach has been proposed as an alternative to CG-FEM (Engwer et al., 2017). It was shown that DG-FEM preserves the property of conservation of charge and that it can, in certain situations such as the so-called skull leakages, be superior to the standard CG-FEM approach. In this paper, we developed, implemented, and evaluated two DG-FEM approaches for the MEG forward problem, namely a conservative and a non-conservative one. The subtraction approach was used as source model. The validation and evaluation work was done in statistical investigations in multi-layer homogeneous sphere models, where an analytic solution exists, and in a six-compartment realistically shaped head volume conductor model. In agreement with the theory, the conservative DG-FEM approach was found to be superior to the non-conservative DG-FEM implementation. This approach also showed convergence with increasing resolution of the hexahedral meshes. While in the EEG case, in presence of skull leakages, DG-FEM outperformed CG-FEM, in MEG, DG-FEM achieved similar numerical errors as the CG-FEM approach, i.e., skull leakages do not play a role for the MEG modality. In particular, for the finest mesh resolution of 1 mm sources with a distance of 1.59 mm from the brain-CSF surface, DG-FEM yielded mean topographical errors (relative difference measure, RDM%) of 1.5% and mean magnitude errors (MAG%) of 0.1% for the magnetic field. However, if the goal is a combined source analysis of EEG and MEG data, then it is highly desirable to employ the same forward model for both EEG and MEG data. Based on these results, we conclude that the newly presented conservative DG-FEM can at least complement and in some scenarios even outperform the established CG-FEM approaches in EEG or combined MEG/EEG source analysis scenarios, which motivates a further evaluation of DG-FEM for applications in bioelectromagnetism.
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Affiliation(s)
- Maria Carla Piastra
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany.,Institute for Computational and Applied Mathematics, University of Münster, Münster, Germany
| | - Andreas Nüßing
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany.,Institute for Computational and Applied Mathematics, University of Münster, Münster, Germany
| | - Johannes Vorwerk
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
| | | | - Robert Oostenveld
- Donders Institute, Radboud University, Nijmegen, Netherlands.,NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Christian Engwer
- Institute for Computational and Applied Mathematics, University of Münster, Münster, Germany.,Cluster of Excellence EXC 1003, Cells in Motion, CiM, University of Münster, Münster, Germany
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
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Okada Y, Hämäläinen M, Pratt K, Mascarenas A, Miller P, Han M, Robles J, Cavallini A, Power B, Sieng K, Sun L, Lew S, Doshi C, Ahtam B, Dinh C, Esch L, Grant E, Nummenmaa A, Paulson D. BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2016; 87:094301. [PMID: 27782541 DOI: 10.1063/1.4962020] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ∼15 mm coil-to-coil spacing) in the inner layer, (2) thirty-five three-axis magnetometers (20 mm × 20 mm) in the outer layer 4 cm away from the inner layer. Additionally, there are three three-axis reference magnetometers. With the help of a remotely operated position adjustment mechanism, the sensor array can be positioned to provide a uniform short spacing (mean 8.5 mm) between the sensor array and room temperature surface of the dewar. The sensors are connected to superconducting quantum interference devices (SQUIDs) operating at 4.2 K with median sensitivity levels of 7.5 fT/√Hz for the inner and 4 fT/√Hz for the outer layer sensors. SQUID outputs are digitized by a 24-bit acquisition system. A closed-cycle helium recycler provides maintenance-free continuous operation, eliminating the need for helium, with no interruption needed during MEG measurements. BabyMEG with the recycler has been fully operational from March, 2015. Ongoing spontaneous brain activity can be monitored in real time without interference from external magnetic noise sources including the recycler, using a combination of a lightly shielded two-layer magnetically shielded room, an external active shielding, a signal-space projection method, and a synthetic gradiometer approach. Evoked responses in the cortex can be clearly detected without averaging. These new design features and capabilities represent several advances in MEG, increasing the utility of this technique in basic neuroscience as well as in clinical research and patient studies.
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Affiliation(s)
- Yoshio Okada
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA
| | - Matti Hämäläinen
- Department of Radiology, A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
| | - Kevin Pratt
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Anthony Mascarenas
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Paul Miller
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Menglai Han
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Jose Robles
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Anders Cavallini
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Bill Power
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Kosal Sieng
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
| | - Limin Sun
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA
| | - Seok Lew
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA
| | - Chiran Doshi
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA
| | - Banu Ahtam
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA
| | - Christoph Dinh
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Gustav-Kirchhoff-Str. 2, 98693 Ilmenau, Germany
| | - Lorenz Esch
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Gustav-Kirchhoff-Str. 2, 98693 Ilmenau, Germany
| | - Ellen Grant
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA
| | - Aapo Nummenmaa
- Department of Radiology, A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
| | - Douglas Paulson
- Tristan Technologies, Inc., 6191 Cornerstone Court East, Suite 107, San Diego, California 92121, USA
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Lau S, Güllmar D, Flemming L, Grayden DB, Cook MJ, Wolters CH, Haueisen J. Skull Defects in Finite Element Head Models for Source Reconstruction from Magnetoencephalography Signals. Front Neurosci 2016; 10:141. [PMID: 27092044 PMCID: PMC4823312 DOI: 10.3389/fnins.2016.00141] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Accepted: 03/18/2016] [Indexed: 11/24/2022] Open
Abstract
Magnetoencephalography (MEG) signals are influenced by skull defects. However, there is a lack of evidence of this influence during source reconstruction. Our objectives are to characterize errors in source reconstruction from MEG signals due to ignoring skull defects and to assess the ability of an exact finite element head model to eliminate such errors. A detailed finite element model of the head of a rabbit used in a physical experiment was constructed from magnetic resonance and co-registered computer tomography imaging that differentiated nine tissue types. Sources of the MEG measurements above intact skull and above skull defects respectively were reconstructed using a finite element model with the intact skull and one incorporating the skull defects. The forward simulation of the MEG signals reproduced the experimentally observed characteristic magnitude and topography changes due to skull defects. Sources reconstructed from measured MEG signals above intact skull matched the known physical locations and orientations. Ignoring skull defects in the head model during reconstruction displaced sources under a skull defect away from that defect. Sources next to a defect were reoriented. When skull defects, with their physical conductivity, were incorporated in the head model, the location and orientation errors were mostly eliminated. The conductivity of the skull defect material non-uniformly modulated the influence on MEG signals. We propose concrete guidelines for taking into account conducting skull defects during MEG coil placement and modeling. Exact finite element head models can improve localization of brain function, specifically after surgery.
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Affiliation(s)
- Stephan Lau
- Institute of Biomedical Engineering and Informatics, Technical University IlmenauIlmenau, Germany; Department of Neurology, Biomagnetic Center, University Hospital JenaJena, Germany; NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of MelbourneParkville, VIC, Australia; Centre for Neural Engineering, University of MelbourneParkville, VIC, Australia; Department of Medicine - St. Vincent's Hospital, University of MelbourneFitzroy, VIC, Australia
| | - Daniel Güllmar
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, University Hospital Jena Jena, Germany
| | - Lars Flemming
- Department of Neurology, Biomagnetic Center, University Hospital Jena Jena, Germany
| | - David B Grayden
- NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of MelbourneParkville, VIC, Australia; Centre for Neural Engineering, University of MelbourneParkville, VIC, Australia
| | - Mark J Cook
- Department of Medicine - St. Vincent's Hospital, University of Melbourne Fitzroy, VIC, Australia
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster Münster, Germany
| | - Jens Haueisen
- Institute of Biomedical Engineering and Informatics, Technical University Ilmenau Ilmenau, Germany
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7
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Montes-Restrepo V, Carrette E, Strobbe G, Gadeyne S, Vandenberghe S, Boon P, Vonck K, Mierlo PV. The Role of Skull Modeling in EEG Source Imaging for Patients with Refractory Temporal Lobe Epilepsy. Brain Topogr 2016; 29:572-89. [PMID: 26936594 DOI: 10.1007/s10548-016-0482-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2015] [Accepted: 02/19/2016] [Indexed: 11/26/2022]
Abstract
We investigated the influence of different skull modeling approaches on EEG source imaging (ESI), using data of six patients with refractory temporal lobe epilepsy who later underwent successful epilepsy surgery. Four realistic head models with different skull compartments, based on finite difference methods, were constructed for each patient: (i) Three models had skulls with compact and spongy bone compartments as well as air-filled cavities, segmented from either computed tomography (CT), magnetic resonance imaging (MRI) or a CT-template and (ii) one model included a MRI-based skull with a single compact bone compartment. In all patients we performed ESI of single and averaged spikes marked in the clinical 27-channel EEG by the epileptologist. To analyze at which time point the dipole estimations were closer to the resected zone, ESI was performed at two time instants: the half-rising phase and peak of the spike. The estimated sources for each model were validated against the resected area, as indicated by the postoperative MRI. Our results showed that single spike analysis was highly influenced by the signal-to-noise ratio (SNR), yielding estimations with smaller distances to the resected volume at the peak of the spike. Although averaging reduced the SNR effects, it did not always result in dipole estimations lying closer to the resection. The proposed skull modeling approaches did not lead to significant differences in the localization of the irritative zone from clinical EEG data with low spatial sampling density. Furthermore, we showed that a simple skull model (MRI-based) resulted in similar accuracy in dipole estimation compared to more complex head models (based on CT- or CT-template). Therefore, all the considered head models can be used in the presurgical evaluation of patients with temporal lobe epilepsy to localize the irritative zone from low-density clinical EEG recordings.
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Affiliation(s)
- Victoria Montes-Restrepo
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium.
| | - Evelien Carrette
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Gregor Strobbe
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium
| | - Stefanie Gadeyne
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Stefaan Vandenberghe
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium
| | - Paul Boon
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Kristl Vonck
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium
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8
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Fiederer LDJ, Vorwerk J, Lucka F, Dannhauer M, Yang S, Dümpelmann M, Schulze-Bonhage A, Aertsen A, Speck O, Wolters CH, Ball T. The role of blood vessels in high-resolution volume conductor head modeling of EEG. Neuroimage 2016; 128:193-208. [PMID: 26747748 PMCID: PMC5225375 DOI: 10.1016/j.neuroimage.2015.12.041] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Revised: 11/27/2015] [Accepted: 12/22/2015] [Indexed: 12/18/2022] Open
Abstract
Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.
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Affiliation(s)
- L D J Fiederer
- Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany.
| | - J Vorwerk
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany
| | - F Lucka
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany; Institute for Computational and Applied Mathematics, University of Münster, Germany; Department of Computer Science, University College London, WC1E 6BT London, UK
| | - M Dannhauer
- Scientific Computing and Imaging Institute, 72 So. Central Campus Drive, Salt Lake City, Utah 84112, USA; Center for Integrative Biomedical Computing, University of Utah, 72 S. Central Campus Drive, 84112, Salt Lake City, UT, USA
| | - S Yang
- Dept. of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany
| | - M Dümpelmann
- Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany
| | - A Schulze-Bonhage
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany
| | - A Aertsen
- Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany
| | - O Speck
- Dept. of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - C H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany
| | - T Ball
- Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany
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9
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Strobbe G, Carrette E, López JD, Montes Restrepo V, Van Roost D, Meurs A, Vonck K, Boon P, Vandenberghe S, van Mierlo P. Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization. NEUROIMAGE-CLINICAL 2016; 11:252-263. [PMID: 26958464 PMCID: PMC4773507 DOI: 10.1016/j.nicl.2016.01.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2015] [Revised: 10/09/2015] [Accepted: 01/17/2016] [Indexed: 11/07/2022]
Abstract
Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP) approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i) an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii) an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time epochs were in the same range as the LORETA and ECD techniques. We found distances smaller than 23 mm, with robust results for all the patients. For the finite difference models, we found that the distances to the resection border for the MSVP inversions of the full spike time epochs were generally smaller compared to the MSVP inversions of the time epochs before the spike peak. The results also suggest that the inversions using the finite difference models resulted in slightly smaller distances to the resection border compared to the spherical models. The results we obtained are promising because the MSVP approach allows to study the network of the estimated source-intensities and allows to characterize the spatial extent of the underlying sources. A Bayesian ESI technique is evaluated to localize interictal spike activity. Averaged spikes in six patients were used that were seizure free after surgery. We compared the technique with the LORETA an ECD technique. We evaluated both spherical and 5-layered finite difference forward models. Our approach is potentially useful to delineate the irritative zone.
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Affiliation(s)
- Gregor Strobbe
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium.
| | - Evelien Carrette
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - José David López
- SISTEMIC, Department of Electronic Engineering, Universidad de Antioquia UDEA, Calle 70 No. 52-21,Medellín, Colombia.
| | - Victoria Montes Restrepo
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium
| | - Dirk Van Roost
- Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium.
| | - Alfred Meurs
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - Kristl Vonck
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - Paul Boon
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - Stefaan Vandenberghe
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium.
| | - Pieter van Mierlo
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium.
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Burnos S, Fedele T, Schmid O, Krayenbühl N, Sarnthein J. Detectability of the somatosensory evoked high frequency oscillation (HFO) co-recorded by scalp EEG and ECoG under propofol. NEUROIMAGE-CLINICAL 2015; 10:318-25. [PMID: 26900572 PMCID: PMC4723731 DOI: 10.1016/j.nicl.2015.11.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 11/25/2015] [Accepted: 11/26/2015] [Indexed: 11/17/2022]
Abstract
Objective The somatosensory evoked potential (SEP) elicited by median nerve stimulation consists of the N20 peak together with the concurrent high frequency oscillation (HFO, > 500 Hz). We describe the conditions for HFO detection in ECoG and scalp EEG in intraoperative recordings. Methods During neurosurgical interventions in six patients under propofol anesthesia, the SEP was recorded from subdural electrode strips (15 recordings) and from scalp electrodes (10/15 recordings). We quantified the spatial attenuation of the Signal-to-Noise Ratio (SNR) of N20 and HFO along the contacts of the electrode strip. We then compared the SNR of ECoG and simultaneous scalp EEG in a biophysical framework. Results HFO detection under propofol anesthesia was demonstrated. Visual inspection of strip cortical recordings revealed phase reversal for N20 in 14/15 recordings and for HFO in 10/15 recordings. N20 had higher maximal SNR (median 33.5 dB) than HFO (median 23 dB). The SNR of N20 attenuated with a larger spatial extent (median 7.2 dB/cm) than the SNR of HFO (median 12.3 dB/cm). We found significant correlations between the maximum SNR (rho = 0.58, p = 0.025) and the spatial attenuation (rho = 0.86, p < 0.001) of N20 and HFO. In 3/10 recordings we found HFO in scalp EEG. Based on the spatial attenuation and SNR in the ECoG, we estimated the scalp EEG amplitude ratio N20/HFO and found significant correlation with recorded values (rho = 0.65, p = 0.049). Conclusions We proved possible the intraoperative SEP HFO detection under propofol anesthesia. The spatial attenuation along ECoG contacts represents a good estimator of the area contributing to scalp EEG. The SNR and the spatial attenuation in ECoG recordings provide further insights for the prediction of HFO detectability in scalp EEG. The results obtained in this context may not be limited to SEP HFO, but could be generalized to biological signatures lying in the same SNR and frequency range. Somatosensory evoked HFOs can be recorded in ECoG and scalp EEG intraoperatively under propofol anesthesia. The HFO amplitude in ECoG attenuated to noise level over a smaller spatial scale than the N20 amplitude. The spatial attenuation of the cortical SNR directly relates to the noise level and to the scalp EEG amplitude. Parameters extracted from ECoG allowed estimating the ratio of N20/HFO amplitude in scalp EEG.
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Affiliation(s)
- Sergey Burnos
- Neurosurgery Department, University Hospital Zurich, Zurich, Switzerland; University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, ETH Zurich, Zurich, Switzerland
| | - Tommaso Fedele
- Neurosurgery Department, University Hospital Zurich, Zurich, Switzerland; University of Zurich, Zurich, Switzerland
| | - Olivier Schmid
- Neurosurgery Department, University Hospital Zurich, Zurich, Switzerland
| | - Niklaus Krayenbühl
- Neurosurgery Department, University Hospital Zurich, Zurich, Switzerland; University of Zurich, Zurich, Switzerland
| | - Johannes Sarnthein
- Neurosurgery Department, University Hospital Zurich, Zurich, Switzerland; University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, ETH Zurich, Zurich, Switzerland
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Ictal Magnetic Source Imaging in Presurgical Assessment. Brain Topogr 2015; 29:182-92. [PMID: 26264375 DOI: 10.1007/s10548-015-0445-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Accepted: 08/06/2015] [Indexed: 10/23/2022]
Abstract
Ictal MEG recordings constitute rare data. The objective of this study was to evaluate ictal magnetic source localization (MSI), using two algorithms: linearly constrained minimum variance (LCMV), a beamforming technique and equivalent current dipole (ECD). Ictal MSI was studied in six patients. Three of them were undergoing post-operative re-evaluation. For all patients, results were validated by the stereoelectroencephalographic (SEEG) definition of the epileptogenic zone (EZ). EZ was quantified using the epileptogenicity index (EI) method, which accounts for both the propensity of a brain area to generate rapid discharges and the time for this area to become involved in the seizure. EI values range from 0 (no epileptogenicity) to 1 (maximal epileptogenicity). Levels of concordance between ictal MSI and EZ were determined as follows: A: ictal MSI localized the site whose value EI = 1, B: MSI localized a part of the EZ (not corresponding to the maximal value of EI = 1), C: a region could be identified on ictal MSI but not on SEEG, D: a region could be identified on SEEG but not on MSI, E: different regions were localized on MSI and SEEG. Ictal MEG pattern consisted of rhythmic activities between 10 and 20 Hz for all patients. For LCMV (first maxima), levels of concordance were A (two cases), B (two cases) and E (two cases). For ECD fitted on each time point separately (location characterized by the best goodness-of-fit value), levels of concordance were A (one case), B (one case), D (three cases) and E (one case). For ECD calculated for the whole time window, levels of concordance were A (two cases) and D (four cases). Source localization methods performed on rhythmic patterns can localize the EZ as validated by SEEG. In terms of concordance, LCMV was superior to ECD. In some cases, LCMV allows extraction of several maxima that could reflect ictal dynamics. In a medial temporal lobe epilepsy case, ictal MSI indicated an area of delayed propagation and was non-contributory to the presurgical assessment.
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Magnetic Source Imaging in Posterior Cortex Epilepsies. Brain Topogr 2014; 28:162-71. [DOI: 10.1007/s10548-014-0412-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 10/20/2014] [Indexed: 11/27/2022]
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