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Kananen J, Järvelä M, Korhonen V, Tuovinen T, Huotari N, Raitamaa L, Helakari H, Väyrynen T, Raatikainen V, Nedergaard M, Ansakorpi H, Jacobs J, LeVan P, Kiviniemi V. Increased interictal synchronicity of respiratory related brain pulsations in epilepsy. J Cereb Blood Flow Metab 2022; 42:1840-1853. [PMID: 35570730 PMCID: PMC9536129 DOI: 10.1177/0271678x221099703] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Respiratory brain pulsations have recently been shown to drive electrophysiological brain activity in patients with epilepsy. Furthermore, functional neuroimaging indicates that respiratory brain pulsations have increased variability and amplitude in patients with epilepsy compared to healthy individuals. To determine whether the respiratory drive is altered in epilepsy, we compared respiratory brain pulsation synchronicity between healthy controls and patients. Whole brain fast functional magnetic resonance imaging was performed on 40 medicated patients with focal epilepsy, 20 drug-naïve patients and 102 healthy controls. Cerebrospinal fluid associated respiratory pulsations were used to generate individual whole brain respiratory synchronization maps, which were compared between groups. Finally, we analyzed the seizure frequency effect and diagnostic accuracy of the respiratory synchronization defect in epilepsy. Respiratory brain pulsations related to the verified fourth ventricle pulsations were significantly more synchronous in patients in frontal, periventricular and mid-temporal regions, while the seizure frequency correlated positively with synchronicity. The respiratory brain synchronicity had a good diagnostic accuracy (ROCAUC = 0.75) in discriminating controls from medicated patients. The elevated respiratory brain synchronicity in focal epilepsy suggests altered physiological effect of cerebrospinal fluid pulsations possibly linked to regional brain water dynamics involved with interictal brain physiology.
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Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Tommi Väyrynen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, USA.,Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu, Finland.,Research Unit of Neuroscience, Neurology, University of Oulu, Oulu, Finland.,Department of Neurology, Oulu University Hospital, Oulu, Finland
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
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Dowdle LT, Ghose G, Chen CCC, Ugurbil K, Yacoub E, Vizioli L. Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI. Prog Neurobiol 2021; 207:102171. [PMID: 34492308 DOI: 10.1016/j.pneurobio.2021.102171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 08/09/2021] [Accepted: 09/02/2021] [Indexed: 01/25/2023]
Abstract
Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States
| | - Clark C C Chen
- Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States.
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Sadjadi SM, Ebrahimzadeh E, Shams M, Seraji M, Soltanian-Zadeh H. Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data. Front Neurol 2021; 12:645594. [PMID: 33986718 PMCID: PMC8110922 DOI: 10.3389/fneur.2021.645594] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/11/2021] [Indexed: 02/01/2023] Open
Abstract
Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.
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Affiliation(s)
- Seyyed Mostafa Sadjadi
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Elias Ebrahimzadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mohammad Shams
- Neural Engineering Laboratory, Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States
| | - Masoud Seraji
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, United States.,Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, NJ, United States
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.,Medical Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
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Tehrani N, Wilson W, Pittman DJ, Mosher V, Peedicail JS, Aghakhani Y, Beers CA, Gaxiola-Valdez I, Singh S, Goodyear BG, Federico P. Localization of interictal discharge origin: A simultaneous intracranial electroencephalographic-functional magnetic resonance imaging study. Epilepsia 2021; 62:1105-1118. [PMID: 33782964 DOI: 10.1111/epi.16887] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/07/2021] [Accepted: 03/08/2021] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Scalp electroencephalographic (EEG)-functional magnetic resonance imaging (fMRI) studies suggest that the maximum blood oxygen level-dependent (BOLD) response to an interictal epileptiform discharge (IED) identifies the area of IED generation. However, the maximum BOLD response has also been reported in distant, seemingly irrelevant areas. Given the poor postoperative outcomes associated with extra-temporal lobe epilepsy, we hypothesized this finding is more common when analyzing extratemporal IEDs as compared to temporal IEDs. We further hypothesized that a subjective, holistic assessment of other significant BOLD clusters to identify the most clinically relevant cluster could be used to overcome this limitation and therefore better identify the likely origin of an IED. Specifically, we also considered the second maximum cluster and the cluster closest to the electrode contacts where the IED was observed. METHODS Maps of significant IED-related BOLD activation were generated for 48 different IEDs recorded from 33 patients who underwent intracranial EEG-fMRI. The locations of the maximum, second maximum, and closest clusters were identified for each IED. An epileptologist, blinded to these cluster assignments, selected the most clinically relevant BOLD cluster, taking into account all available clinical information. The distances between these BOLD clusters and their corresponding IEDs were then measured. RESULTS The most clinically relevant cluster was the maximum cluster for 56% (27/48) of IEDs, the second maximum cluster for 13% (6/48) of IEDs, and the closest cluster for 31% (15/48) of IEDs. The maximum clusters were closer to IED contacts for temporal than for extratemporal IEDs (p = .022), whereas the most clinically relevant clusters were not significantly different (p = .056). SIGNIFICANCE The maximum BOLD response to IEDs may not always be the most indicative of IED origin. We propose that available clinical information should be used in conjunction with EEG-fMRI data to identify a BOLD cluster representative of the IED origin.
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Affiliation(s)
- Negar Tehrani
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - William Wilson
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Daniel J Pittman
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Victoria Mosher
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joseph S Peedicail
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Yahya Aghakhani
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Craig A Beers
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Ismael Gaxiola-Valdez
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shaily Singh
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Bradley G Goodyear
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Paolo Federico
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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5
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Chatzistefanidis D, Huang D, Dümpelmann M, Jacobs J, Schulze-Bonhage A, LeVan P. Topography-Related EEG-fMRI in Surgically Confirmed Epileptic Foci: A Comparison to Spike-Related EEG-fMRI in Clinical Practice. Brain Topogr 2021; 34:373-383. [PMID: 33730357 DOI: 10.1007/s10548-021-00832-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 03/09/2021] [Indexed: 11/30/2022]
Abstract
EEG-fMRI has gained increasing importance in epilepsy pre-surgical diagnosis. However, 40-70% of EEG-fMRI recordings in patients lack interictal epileptiform discharges (IEDs) during the scan, which could be overcome by detecting matching topography maps. We tried to validate this method in clinical settings taking various electroclinical factors into consideration. Eleven patients who had undergone EEG-fMRI during pre-surgical evaluation for drug-resistant epilepsy and who had had clinical long-term video-EEG were studied. Spike-related blood oxygen level-dependent (BOLD) maps were created using IEDs occurring during the EEG-fMRI scan. Separate maps were then generated from IEDs marked on the clinical long-term EEG recordings, which were averaged to produce topographical IED maps and correlated with the EEGs recorded inside the scanner yielding a correlation coefficient time course. Epileptogenic zones were defined by an expert panel during pre-surgical evaluation and validated by an epilepsy surgery resulting in a good outcome. Both techniques' performance was evaluated according to factors including arousal during IED recording, IED topography and lateralization, lesion type, and localization. Topography-related EEG-fMRI yielded more specific results compared to the spike-related method. Superficial lesion location and ipsilateral IED seem to result in a higher concordance of BOLD maps. The polarity of BOLD responses may be lesion-dependent, and both positive and negative BOLD changes may be associated with the irritative zone. Topography-related EEG-fMRI may show improved specificity especially for superficial lesions producing ipsilateral spikes. This method can be used as an alternative either in the absence of spikes during the simultaneous EEG-fMRI acquisition or to sharpen a diffusely activated BOLD-map.
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Affiliation(s)
| | - Dengfeng Huang
- Department Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias Dümpelmann
- Epilepsy Center, Department Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Julia Jacobs
- Department Neuropediatrics and Muscular Diseases, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Department Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Pierre LeVan
- Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Departments of Radiology and Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Canada
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Hennig J, Kiviniemi V, Riemenschneider B, Barghoorn A, Akin B, Wang F, LeVan P. 15 Years MR-encephalography. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 34:85-108. [PMID: 33079327 PMCID: PMC7910380 DOI: 10.1007/s10334-020-00891-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 09/02/2020] [Accepted: 09/29/2020] [Indexed: 02/07/2023]
Abstract
Objective This review article gives an account of the development of the MR-encephalography (MREG) method, which started as a mere ‘Gedankenexperiment’ in 2005 and gradually developed into a method for ultrafast measurement of physiological activities in the brain. After going through different approaches covering k-space with radial, rosette, and concentric shell trajectories we have settled on a stack-of-spiral trajectory, which allows full brain coverage with (nominal) 3 mm isotropic resolution in 100 ms. The very high acceleration factor is facilitated by the near-isotropic k-space coverage, which allows high acceleration in all three spatial dimensions. Methods The methodological section covers the basic sequence design as well as recent advances in image reconstruction including the targeted reconstruction, which allows real-time feedback applications, and—most recently—the time-domain principal component reconstruction (tPCR), which applies a principal component analysis of the acquired time domain data as a sparsifying transformation to improve reconstruction speed as well as quality. Applications Although the BOLD-response is rather slow, the high speed acquisition of MREG allows separation of BOLD-effects from cardiac and breathing related pulsatility. The increased sensitivity enables direct detection of the dynamic variability of resting state networks as well as localization of single interictal events in epilepsy patients. A separate and highly intriguing application is aimed at the investigation of the glymphatic system by assessment of the spatiotemporal patterns of cardiac and breathing related pulsatility. Discussion MREG has been developed to push the speed limits of fMRI. Compared to multiband-EPI this allows considerably faster acquisition at the cost of reduced image quality and spatial resolution.
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Affiliation(s)
- Juergen Hennig
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany. .,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Bruno Riemenschneider
- Department of Radiology, Center for Biomedical Imaging, New York University Grossman School of Medicine, New York, NY, USA
| | - Antonia Barghoorn
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Burak Akin
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Fei Wang
- Department of Radiology, Medical Physics, Faculty of Medicine, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Pierre LeVan
- Departments of Radiology and Paediatrics, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
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Zhang S, Hennig J, LeVan P. Direct modelling of gradient artifacts for EEG-fMRI denoising and motion tracking. J Neural Eng 2019; 16:056010. [PMID: 31216524 DOI: 10.1088/1741-2552/ab2b21] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Simultaneous electroencephalography and functional magnetic resonance imaging recording (EEG-fMRI) has been widely used in neuroscientific and clinical research. The artifacts in the recorded EEG resulting from rapidly switching magnetic field gradients are usually corrected by average-artifact subtraction (AAS) due to their repetitive nature. But the performance of AAS is often disrupted by altered artifact waveforms across epochs, notably due to head motion. APPROACH Here, a method is proposed to make use of the known MR sequence gradient waveforms for a direct modelling of gradient artifacts. After accounting for filtering effects on the gradient artifacts, a continuous modulation of the gradient waveforms superimposed on the EEG signal is obtained. MAIN RESULTS Although a moving AAS template can adjust to slow drifts in gradient artifact variation, it fails to adapt to abrupt motion, resulting in residual noise. We demonstrate how this modelling approach can reduce motion-affected gradient artifacts without distorting the underlying neuronal signals. Moreover, the method provides useful head motion information highly correlated with motion tracked by an optical camera. SIGNIFICANCE Our work provides a novel way to improve gradient artifact removal in EEG-fMRI, and shows a potential to detect head motion without requiring additional hardware.
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Affiliation(s)
- Shuoyue Zhang
- Department of Radiology - Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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8
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Ebrahimzadeh E, Shams M, Fayaz F, Rajabion L, Mirbagheri M, Nadjar Araabi B, Soltanian-Zadeh H. Quantitative determination of concordance in localizing epileptic focus by component-based EEG-fMRI. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 177:231-241. [PMID: 31319952 DOI: 10.1016/j.cmpb.2019.06.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 05/07/2019] [Accepted: 06/04/2019] [Indexed: 02/01/2023]
Abstract
BACKGROUND AND OBJECTIVE Accurate seizure onset zone (SOZ) localization is an essential step in pre-surgical assessment of patients with refractory focal epilepsy. Complex pathophysiology of epileptic cerebral structures, seizure types and frequencies have not been considered as influential features for accurate identification of SOZ using EEG-fMRI. There is a crucial need to quantitatively measure concordance between presumed SOZ and IED-related BOLD response in different brain regions to improve SOZ delineation. METHODS A novel component-based EEG-fMRI approach is proposed to measure physical distance between BOLD clusters and selected component dipole location using patient-specific high resolution anatomical images. The method is applied on 18 patients with refractory focal epilepsy to localize epileptic focus and determine concordance quantitatively and compare between maximum BOLD cluster with identified component dipole. To measure concordance, distance from a voxel with maximal z-score of maximum BOLD to center of extracted component dipole is measured. RESULTS BOLD clusters to spikes distances for concordant (<25 mm), partially concordant (25-50 mm), and discordant (>50 mm) groups were significantly different (p < 0.0001). The results showed full concordance in 17 IED types (17.85 ± 4.69 mm), partial concordance in 4 (36.47 ± 8.84 mm), and nodiscordance, which is a significant rise compared to the existing literature. The proposed method is premised on the cross-correlation between the spike template outside the scanner and the highly-ranked extracted components. It successfully surpasses the limitations of conventional EEG-fMRI studies which are largely dependent on inside-scanner spikes. More significantly, the proposed method improves localization accuracy to 97% which marks a dramatic rise compared to conventional works. CONCLUSIONS This study demonstrated that BOLD changes were related to epileptic spikes in different brain regions in patients with refractory focal epilepsy. In a systematic quantitative approach, concordance levels based on the distance between center of maximum BOLD cluster and dipole were determined by component-based EEG-fMRI method. Therefore, component-based EEG-fMRI can be considered as a reliable predictor of SOZ in patients with focal epilepsy and included as part of clinical evaluation for patients with medically resistant epilepsy.
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Affiliation(s)
- Elias Ebrahimzadeh
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; Seaman Family MR Research Centre, University of Calgary, Calgary, Alberta, Canada.
| | - Mohammad Shams
- Department of Biomedical Engineering, George Washington University, Washington D.C., USA
| | - Farahnaz Fayaz
- Biomedical Engineering Department, School of Electrical Engineering, Payame Noor University of North Tehran, Tehran, Iran
| | - Lila Rajabion
- Department of IT, College of Business, University of South Florida Sarasota-Manatee, USA
| | - Mahya Mirbagheri
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Babak Nadjar Araabi
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Hamid Soltanian-Zadeh
- CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; Image Analysis Laboratory, Department of Radiology, Henry Ford Hospital, Detroit, MI, USA
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Kogias E, Schmeiser B, Doostkam S, Brandt A, Hammen T, Zentner J, Ramantani G. Multilobar Resections for 3T MRI-Negative Epilepsy: Worth the Trouble? World Neurosurg 2018; 123:e338-e347. [PMID: 30502474 DOI: 10.1016/j.wneu.2018.11.170] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 11/12/2018] [Accepted: 11/19/2018] [Indexed: 12/01/2022]
Abstract
OBJECTIVE Multilobar resection in magnetic resonance imaging (MRI)-negative drug-resistant epilepsy warrants attention because they account for up to one third of MRI-negative epilepsy surgery. Despite their high prevalence, data are sparse, and the risk/benefit ratio continues to be debated. The present study investigated the postoperative seizure outcomes in this especially challenging subgroup. METHODS We retrospectively analyzed the data of 4 consecutive patients with 3T MRI-negative findings and drug-resistant focal epilepsy who had undergone multilobar epilepsy surgery at our institution. RESULTS The mean age at first surgery was 28.5 years (range, 14-48); 1 patient required 2 consecutive reoperations. The final resection was in the frontotemporal and temporo-parieto-occipital regions in 2 patients each. Histopathological examination revealed mild malformations of cortical development in 2 patients and focal cortical dysplasia type Ia and type IIa in 1 patient each. At the last follow-up examination (median, 3.3 years; range, 1-11), 2 patients were completely seizure free (Engel class Ia), 1 patient had experienced some disabling seizures after surgery but had been free of disabling seizures for 2 years at the last follow-up examination (Engel class Ic), and 1 patient had experienced worthwhile improvement (Engel class IIb) and had been seizure free for 1 year at the last follow-up examination. No surgical complications developed. CONCLUSIONS Our results have demonstrated that multilobar epilepsy surgery is effective for lasting seizure control for selected 3T MRI-negative candidates, leading to favorable outcomes for all 4 of our patients. Comprehensive multimodal preoperative evaluation is a prerequisite for postoperative success. Reevaluation should be considered for patients with seizure recurrence, because reoperation could be especially beneficial for selected patients who have not responded to an initially limited resection.
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Affiliation(s)
- Evangelos Kogias
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Barbara Schmeiser
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Soroush Doostkam
- Institute of Neuropathology, Medical Center - University of Freiburg, Freiburg, Germany
| | - Armin Brandt
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Thilo Hammen
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Josef Zentner
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Georgia Ramantani
- Epilepsy Center, Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neuropediatrics, University Children's Hospital Zurich, Zurich, Switzerland.
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10
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Fast imaging for mapping dynamic networks. Neuroimage 2018; 180:547-558. [DOI: 10.1016/j.neuroimage.2017.08.029] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Revised: 07/21/2017] [Accepted: 08/09/2017] [Indexed: 01/22/2023] Open
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11
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Keinänen T, Rytky S, Korhonen V, Huotari N, Nikkinen J, Tervonen O, Palva JM, Kiviniemi V. Fluctuations of the EEG-fMRI correlation reflect intrinsic strength of functional connectivity in default mode network. J Neurosci Res 2018; 96:1689-1698. [PMID: 29761531 DOI: 10.1002/jnr.24257] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 04/20/2018] [Accepted: 04/23/2018] [Indexed: 01/14/2023]
Abstract
Both functional magnetic resonance imaging (fMRI) and electrophysiological recordings have revealed that resting-state functional connectivity is temporally variable in human brain. Combined full-band electroencephalography-fMRI (fbEEG-fMRI) studies have shown that infraslow (<.1 Hz) fluctuations in EEG scalp potential are correlated with the blood-oxygen-level-dependent (BOLD) fMRI signals and that also this correlation appears variable over time. Here, we used simultaneous fbEEG-fMRI to test the hypothesis that correlation dynamics between BOLD and fbEEG signals could be explained by fluctuations in the activation properties of resting-state networks (RSNs) such as the extent or strength of their activation. We used ultrafast magnetic resonance encephalography (MREG) fMRI to enable temporally accurate and statistically robust short-time-window comparisons of infra-slow fbEEG and BOLD signals. We found that the temporal fluctuations in the fbEEG-BOLD correlation were dependent on RSN connectivity strength, but not on the mean signal level or magnitude of RSN activation or motion during scanning. Moreover, the EEG-fMRI correlations were strongest when the intrinsic RSN connectivity was strong and close to the pial surface. Conversely, weak fbEEG-BOLD correlations were attributable to periods of less coherent or spatially more scattered intrinsic RSN connectivity, or RSN activation in deeper cerebral structures. The results thus show that the on-average low correlations between infra-slow EEG and BOLD signals are, in fact, governed by the momentary coherence and depth of the underlying RSN activation, and may reach systematically high values with appropriate source activities. These findings further consolidate the notion of slow scalp potentials being directly coupled to hemodynamic fluctuations.
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Affiliation(s)
- Tuija Keinänen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Department of Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Seppo Rytky
- Department of Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Juha Nikkinen
- Department of Oncology and Radiotherapy, Oulu University Hospital, Oulu, Finland
| | - Osmo Tervonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - J Matias Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
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12
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Walz JM, Pedersen M, Omidvarnia A, Semmelroch M, Jackson GD. Spatiotemporal mapping of epileptic spikes using simultaneous EEG-functional MRI. Brain 2017; 140:998-1010. [PMID: 28334998 DOI: 10.1093/brain/awx007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 12/06/2016] [Indexed: 11/14/2022] Open
Abstract
Epileptic spikes occur on the sub-second timescale and are known to involve not only epileptic foci but also large-scale distributed brain networks. There is likely to be a sequence of neural activity in multiple brain regions that occurs within the duration of a single spike, but standard electroencephalography-functional magnetic resonance imaging analyses, which use only the timing of the spikes to model the functional magnetic resonance imaging data, cannot determine the sequence of these activations. Our aim in this study is to temporally resolve these spatial activations to observe the spatiotemporal dynamics of the spike-related neural activity at a sub-second timescale. We studied eight focal epilepsy patients (age 11-42 years, six female) and used amplitude features of the electroencephalogram specific to different spike components (early and late peaks and troughs) to encode temporal information into our functional magnetic resonance imaging models. This enables us to associate each activation with a specific model of each of the spike components to infer the temporal order of these spike-related spatial activations. In seven of eight patients the distributed networks were associated with the late spike component. The focal activations were more variably coupled with time epochs, but tended to precede the distributed network effects. We also found that incorporating electroencephalogram features into the models increased sensitivity and in six patients revealed additional regions unseen in the standard analysis result. This included strong bilateral thalamus activation in two patients. We demonstrate the clinical utility of this approach in a patient who recently underwent a successful surgical resection of the region where we saw enhanced activation using electroencephalogram amplitude information specific to the early spike component. This focal cluster of activation was larger and more precisely tracked the anatomy compared to what was seen using the standard timing-based analysis. Our novel electroencephalography-functional magnetic resonance imaging data fusion approach, which utilizes information based on the single spike variability across all electroencephalogram channels, has the potential to help us better understand epileptic networks and aid in the interpretation of functional magnetic resonance imaging activation maps during treatment planning.
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Affiliation(s)
- Jennifer M Walz
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia
| | - Mangor Pedersen
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia.,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Amir Omidvarnia
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia
| | - Mira Semmelroch
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia
| | - Graeme D Jackson
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Melbourne, VIC, Australia.,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, Austin Health, Melbourne, VIC, Australia
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13
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Abstract
Ever since the implementation of invasive EEG recordings in the clinical setting, it has been perceived that a considerable proportion of epileptic discharges present at a cortical level are missed by routine scalp EEG recordings. Several in vitro, in vivo, and simulation studies have been performed in the past decades aiming to clarify the interrelations of cortical sources with their scalp and invasive EEG correlates. The amplitude ratio of cortical potentials to their scalp EEG correlates, the extent of the cortical area involved in the discharge, as well as the localization of the cortical source and its geometry have been each independently linked to the recording of the cortical discharge with scalp electrodes. The need to elucidate these interrelations has been particularly imperative in the field of epilepsy surgery with its rapidly growing EEG-based localization technologies. Simultaneous multiscale EEG recordings with scalp, subdural and/or depth electrodes, applied in presurgical epilepsy workup, offer an excellent opportunity to shed some light to this fundamental issue. Whereas past studies have considered predominantly neocortical sources in the context of temporal lobe epilepsy, current investigations have included deep sources, as in mesial temporal epilepsy, as well as extratemporal sources. Novel computational tools may serve to provide surrogates for the shortcomings of EEG recording methodology and facilitate further developments in modern electrophysiology.
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