BOLD mapping of human epileptic spikes recorded during simultaneous intracranial EEG-fMRI: The impact of automated spike classification

Abstract

ObjectivesSimultaneous intracranial EEG and functional MRI (icEEG-fMRI) can be used to map the haemodynamic (BOLD) changes associated with the generation of IEDs. Unlike scalp EEG-fMRI, in most patients who undergo icEEG-fMRI, IEDs recorded intracranially are numerous and show variability in terms of field amplitude and morphology. Therefore, visual marking can be highly subjective and time consuming. In this study, we applied an automated spike classification algorithm, Wave_clus (WC), to IEDs marked visually on icEEG data acquired during simultaneous fMRI acquisition. The motivation of this work is to determine whether using a potentially more consistent and unbiased automated approach can produce more biologically meaningful BOLD patterns compared to the BOLD patterns obtained based on the conventional, visual classification.MethodsWe analysed simultaneous icEEG-fMRI data from eight patients with severe drug resistant epilepsy, and who subsequently underwent resective surgery that resulted in a good outcome: confirmed epileptogenic zone (EZ). For each patient two fMRI analyses were performed: one based on the conventional visual IED classification and the other based on the automated classification. We used the concordance of the IED-related BOLD maps with the confirmed EZ as an indication of their biological meaning, which we compared for the automated and visual classifications for all IED originating in the EZ.ResultsAcross the group, the visual and automated classifications resulted in 32 and 24 EZ IED classes respectively, for which 75% vs 83% of the corresponding BOLD maps were concordant. At the single-subject level, the BOLD maps for the automated approach had greater concordance in four patients, and less concordance in one patient, compared to those obtained using the conventional visual classification, and equal concordance for three remaining patients. These differences did not reach statistical significance.ConclusionWe found automated IED classification on icEEG data recorded during fMRI to be feasible and to result in IED-related BOLD maps that may contain similar or greater biological meaning compared to the conventional approach in the majority of the cases studied. We anticipate that this approach will help to gain significant new insights into the brain networks associated with IEDs and in relation to postsurgical outcome.

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

“…Previous studies using icEEG-fMRI have shown BOLD changes related to IEDs and seizures (32,33,40,52,53). Comparison of visual and automated IED classification on icEEG (53) presented a more objective interpretation of icEEG, but there was no statistically significant difference in concordance of the BOLD maps for two IED classification techniques.…”

“…Previous studies using icEEG-fMRI have shown BOLD changes related to IEDs and seizures ( 32 , 33 , 40 , 52 , 53 ). Comparison of visual and automated IED classification on icEEG ( 53 ) presented a more objective interpretation of icEEG, but there was no statistically significant difference in concordance of the BOLD maps for two IED classification techniques. The relationship of BOLD clusters in surgical resection volume and in remote brain areas for different IED classes has not been explored in previous studies.…”

Temperature Measurements in the Vicinity of Human Intracranial EEG Electrodes Exposed to Body-Coil RF for MRI at 1.5T

“…We performed experiments to quantify the amount of heating induced in the immediate vicinity of a set of intracranial EEG electrodes by exposure to RF generated by a body transmit coil in a 1.5T MRI scanner. This work builds directly on our experience of acquiring concurrent icEEG-fMRI data using a quadrature head RF transmit coil in the MRI scanner (Vulliemoz et al, 2011;Chaudhary et al, 2016;Murta et al, 2016Murta et al, , 2017Ridley et al, 2017;Sharma et al, 2019) and in particular the safety tests that made it possible (Carmichael et al, 2008) and associated scanning protocol (Carmichael et al, 2012). This protocol contains prescriptions on the choice of RF transmit coil, MR sequence, and the type, connection and positioning of the EEG wires and equipment, and relies to a large degree on the use of a scanner bore foam insert on which the EEG system can be placed precisely and consistently.…”

“…Intracranial electroencephalography during functional magnetic resonance imaging (IcEEG-fMRI) has been used to map epileptic activities (Vulliemoz et al, 2011;Boucousis et al, 2012;Carmichael et al, 2012) with much greater sensitivity enabling more detailed, quantitative studies of interictal, preictal and ictal epileptogenic networks (Vulliemoz et al, 2011;Cunningham et al, 2012;Aghakhani et al, 2015;Beers et al, 2015;Chaudhary et al, 2016;Ridley et al, 2017;Sharma et al, 2019) and of neuronal events more generally (Murta et al, 2016(Murta et al, , 2017Saignavongs et al, 2016).…”

Localization of interictal discharge origin: A simultaneous intracranial electroencephalographic–functional magnetic resonance imaging study

“…11 Intracranial EEG (iEEG) provides greater sensitivity to and spatial discrimination of IED sources, but relies heavily on the choice of location for electrode implantation. 12 Further, despite the potential for simultaneous iEEG-fMRI to provide a more reliable localization of IEDrelated BOLD changes, studies performed to date [13][14][15][16][17][18][19][20][21][22][23] have revealed instances of complex patterns that are difficult to interpret and require qualitative consolidation with the other relevant clinical information (eg, ictal iEEG recordings) and their clinical relevance.…”