Localization of epileptogenic zone based on graph analysis of stereo-EEG

Li, Yonghua; Ye, Xiaolai; Liu, Qiangqiang; Mao, Jun-Wei; Liang, Pei-Ji; Xu, Junjie; Zhang, Pu-Ming

doi:10.1016/j.eplepsyres.2016.10.021

Cited by 50 publications

(52 citation statements)

References 53 publications

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“…Other studies only reported an increase in the betweenness centrality in the gamma band (Varotto, Tassi, Franceschetti, Spreafico, & Panzica, 2012; Wilke et al, 2011), or in a few seconds prior to seizure onset (Li et al, 2016). Geier, Bialonski, Elger, and Lehnertz (2015) found that the betweenness centrality in pre‐ictal ECoG (using cross‐correlation) was highest in brain regions neighboring the SOZ.…”

Section: Discussionmentioning

confidence: 98%

Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation

Blooijs

Leijten

Rijen

et al. 2018

Human Brain Mapping

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We investigated effective networks constructed from single pulse electrical stimulation (SPES) in epilepsy patients who underwent intracranial electrocorticography. Using graph analysis, we compared network characteristics of tissue within and outside the epileptogenic area. In 21 patients with subdural electrode grids (1 cm interelectrode distance), we constructed a binary, directional network derived from SPES early responses (<100 ms). We calculated in‐degree, out‐degree, betweenness centrality, the percentage of bidirectional, receiving and activating connections, and the percentage of connections toward the (non‐)epileptogenic tissue for each node in the network. We analyzed whether these network measures were significantly different in seizure onset zone (SOZ)‐electrodes compared to non‐SOZ electrodes, in resected area (RA)‐electrodes compared to non‐RA electrodes, and in seizure free compared to not seizure‐free patients. Electrodes in the SOZ/RA showed significantly higher values for in‐degree and out‐degree, both at group level, and at patient level, and more so in seizure‐free patients. These differences were not observed for betweenness centrality. There were also more bidirectional and fewer receiving connections in the SOZ/RA in seizure‐free patients. It appears that the SOZ/RA is densely connected with itself, with only little input arriving from non‐SOZ/non‐RA electrodes. These results suggest that meso‐scale effective network measures are different in epileptogenic compared to normal brain tissue. Local connections within the SOZ/RA are increased and the SOZ/RA is relatively isolated from the surrounding cortex. This offers the prospect of enhanced prediction of epilepsy‐prone brain areas using SPES.

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Section: Discussionmentioning

confidence: 98%

Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation

Blooijs

Leijten

Rijen

et al. 2018

Human Brain Mapping

View full text Add to dashboard Cite

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“…Another algorithm implementing the concept of Granger causality in the frequency domain is partial directed coherence (PDC). PDC was recently applied to the localization of the epileptogenic zone . However, all these methods are based on linear assumptions for the relationship between signals estimated by multivariate autoregressive (MVAR) models.…”

Section: Methods For Recording and Analyzing Epileptogenic Networkmentioning

confidence: 99%

“…PDC was recently applied to the localization of the epileptogenic zone. 56 However, all these methods are based on linear assumptions for the relationship between signals estimated by multivariate autoregressive (MVAR) models. It is also possible to estimate directed connectivity based on nonlinear measures, in particular non-linear regression.…”

Section: Causality Analysismentioning

confidence: 99%

Defining epileptogenic networks: Contribution of SEEG and signal analysis

et al. 2017

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SUMMARYEpileptogenic networks are defined by the brain regions involved in the production and propagation of epileptic activities. In this review we describe the historical, methodologic, and conceptual bases of this model in the analysis of electrophysiologic intracerebral recordings. In the context of epilepsy surgery, the determination of cerebral regions producing seizures (i.e., the "epileptogenic zone") is a crucial objective. In contrast with a traditional focal vision of focal drug-resistant epilepsies, the concept of epileptogenic networks has been progressively introduced as a model better able to describe the complexity of seizure dynamics and realistically describe the distribution of epileptogenic anomalies in the brain. The concept of epileptogenic networks is historically linked to the development of the stereoelectroencephalography (SEEG) method and subsequent introduction of means of quantifying the recorded signals. Seizures, and preictal and interictal discharges produce clear patterns on SEEG. These patterns can be analyzed utilizing signal analysis methods that quantify high-frequency oscillations or changes in functional connectivity. Dramatic changes in SEEG brain connectivity can be described during seizure genesis and propagation within cortical and subcortical regions, associated with the production of different patterns of seizure semiology. The interictal state is characterized by networks generating abnormal activities (interictal spikes) and also by modified functional properties. The introduction of novel approaches to large-scale modeling of these networks offers new methods in the goal of better predicting the effects of epilepsy surgery. The epileptogenic network concept is a key factor in identifying the anatomic distribution of the epileptogenic process, which is particularly important in the context of epilepsy surgery.

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“…There were 12 studies 15-26 that reported on epilepsy duration, with no significant difference between SEEG patients (mean = 126.8 months ± 65.0, median = 121.8) and SDE patients (mean = 62.4 months ± 51.1, median = 51.4; Table 2). Among the SEEG patients, the etiology was identified as a temporal epileptogenic focus in 42.2% of patients, 15,22,23,[26][27][28][29] tumor in 6.7% of patients, 22,23,27,28,30 FCD1 in 39.2% of patients, 16,23,27,28,[31][32][33] FCD2 in 10.7% of patients, 23,28,31 and lesional in 41.5% of patients. [15][16][17]22,23,[28][29][30][31]34 Among the SDE patients, the etiology was identified as a temporal epileptogenic focus in 40.9% of patients, 18,21,25,[35][36][37][38][39][40][41][42][43][44][45...…”

Section: Cohort Descriptionmentioning

confidence: 99%

“…Among 490 SEEG-informed patients who underwent resective surgery from nine studies, 310 patients (61.0%, 95% CI = 60.5-61.4%) were seizure-free. 15,16,22,23,27,28,32,33,49 Of the 953 SDE-informed patients who underwent resective surgery from 21 studies, 564 patients (56.4%, 95% CI = 55.7-57.1%) were seizurefree. 18,20,21,24,25,[35][36][37][38][39][40][41][42][43][44][45]47,48,[50][51][52] Therefore, SEEG-informed surgical resections have associations that suggest better seizure freedom outcomes than SDE-informed surgical resections (WMD = +5.8%, 95% CI = 4.7-6.9%, P = .001).…”

Section: Epileptic Surgery and Outcomesmentioning

confidence: 99%

Method of invasive monitoring in epilepsy surgery and seizure freedom and morbidity: A systematic review

et al. 2019

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Objective Invasive monitoring is sometimes necessary to guide resective surgery in epilepsy patients, but the ideal method is unknown. In this systematic review, we assess the association of postresection seizure freedom and adverse events in stereoelectroencephalography (SEEG) and subdural electrodes (SDE). Methods We searched three electronic databases (MEDLINE, Embase, and CENTRAL [Cochrane Central Register of Controlled Trials]) from their inception to January 2018 with the keywords “electroencephalography,” “intracranial grid,” and “epilepsy.” Studies that presented primary quantitative patient data for postresection seizure freedom with at least 1 year of follow‐up or complication rates of SEEG‐ or SDE‐monitored patients were included. Two trained investigators independently collected data from eligible studies. Weighted mean differences (WMDs) with 95% confidence interval (CIs) were used as a measure of the association of SEEG or SDE with seizure freedom and with adverse event outcomes. Results Of 11 462 screened records, 48 studies met inclusion criteria. These studies reported on 1973 SEEG patients and 2036 SDE patients. Our systematic review revealed SEEG was associated with 61.0% and SDE was associated with 56.4% seizure freedom after resection (WMD = +5.8%, 95% CI = 4.7‐6.9%, P = .001). Furthermore, SEEG was associated with 4.8% and SDE was associated with 15.5% morbidity (WMD = −10.6%, 95% CI = −11.6 to −9.6%, P = .001). SEEG was associated with 0.2% mortality and SDE was associated with 0.4% mortality (WMD = −0.2%, 95% CI = −0.3 to −0.1%, P = .001). Significance In this systematic review of SEEG and SDE invasive monitoring techniques, SEEG was associated with fewer surgical resections yet better seizure freedom outcomes in those undergoing resections. SEEG was also associated with lower mortality and morbidity than SDE. Clinical studies directly comparing these modalities are necessary to understand the relative rates of seizure freedom, morbidity, and mortality associated with these techniques.

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Localization of epileptogenic zone based on graph analysis of stereo-EEG

Cited by 50 publications

References 53 publications

Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation

Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation

Defining epileptogenic networks: Contribution of SEEG and signal analysis

Method of invasive monitoring in epilepsy surgery and seizure freedom and morbidity: A systematic review

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