Localization of the epileptogenic zone based on ictal stereo-electroencephalogram: Brain network and single-channel signal feature analysis

Accurate localization of the epileptogenic zone (EZ) is crucial for refractory focal epilepsy patients to achieve freedom from seizures following epilepsy surgery. In this study, ictal stereo-electroencephalography data from 35 patients with refractory focal epilepsy were analyzed. Effective networks based on partial directed coherence were analyzed, and a gray level co-occurrence matrix was applied to extract the time-varying features of the in-degree. These features, combined with the single-channel signal time-frequency features, including approximate entropy and line length, were used to localize the EZ based on a cluster algorithm. For all seizure-free patients (n = 23), the proposed method was effective in identifying the clinical-EZ-contacts and clinical-EZ-blocks, with an F1-score of 62.47 % and 72.18 %, respectively. The sensitivity was 96.00 % for the clinical-EZ-block identification, which provided the information for the decision-making of clinicians, prompting clinicians to focus on the identified EZ-blocks and their nearby contacts. The agreement between the EZ identified by the proposed method and the clinical-EZ was worse for non-seizure-free patients (n = 12) than for seizure-free patients. Furthermore, our method provided better results than using only brain network or single-channel signal features. This suggests that combining these complementary features can facilitate more accurate localization of the EZ.

[1]  S. Nolan,et al.  Surgery for epilepsy: a systematic review of current evidence. , 2016, Epileptic disorders : international epilepsy journal with videotape.

[2]  Sandy Rihana,et al.  Effective connectivity analysis of iEEG and accurate localization of the epileptogenic focus at the onset of operculo-insular seizures , 2019, Epilepsy Research.

[3]  Laura Tassi,et al.  Epileptogenic networks of type II focal cortical dysplasia: A stereo-EEG study , 2012, NeuroImage.

[4]  Mostefa Mesbah,et al.  Range Entropy: A Bridge between Signal Complexity and Self-Similarity , 2018, Entropy.

[5]  Fabrice Bartolomei,et al.  Seizure‐onset patterns in focal cortical dysplasia and neurodevelopmental tumors: Relationship with surgical prognosis and neuropathologic subtypes , 2016, Epilepsia.

[6]  Philippe Kahane,et al.  Commentary: Understanding Stereoelectroencephalography: What's Next? , 2018, Neurosurgery.

[7]  V. Srinivasan,et al.  Approximate Entropy-Based Epileptic EEG Detection Using Artificial Neural Networks , 2007, IEEE Transactions on Information Technology in Biomedicine.

[8]  Taylor J. Abel,et al.  Stereoelectroencephalography Versus Subdural Electrodes for Localization of the Epileptogenic Zone: What Is the Evidence? , 2019, Neurotherapeutics.

[9]  S M Pincus,et al.  Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[10]  U. Rajendra Acharya,et al.  Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals , 2015, Entropy.

[11]  Lojini Logesparan,et al.  Optimal features for online seizure detection , 2012, Medical & Biological Engineering & Computing.

[12]  Pieter van Mierlo,et al.  Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG , 2018, Brain topography.

[13]  Yanchun Zhang,et al.  Multi-category EEG signal classification developing time-frequency texture features based Fisher Vector encoding method , 2016, Neurocomputing.

[14]  Sandipan Pati,et al.  Spectral organization of focal seizures within the thalamotemporal network , 2019, Annals of clinical and translational neurology.

[15]  Angela Marchi,et al.  Occipital and occipital “plus” epilepsies: A study of involved epileptogenic networks through SEEG quantification , 2016, Epilepsy & Behavior.

[16]  Petr Klimes,et al.  Multi-feature localization of epileptic foci from interictal, intracranial EEG , 2019, Clinical Neurophysiology.

[17]  Joachim Gross,et al.  The effect of filtering on Granger causality based multivariate causality measures , 2010, NeuroImage.

[18]  Shuang Wang,et al.  Ripple classification helps to localize the seizure‐onset zone in neocortical epilepsy , 2013, Epilepsia.

[19]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[20]  Hitten P. Zaveri,et al.  The spatial and signal characteristics of physiologic high frequency oscillations , 2014, Epilepsia.

[21]  Lara Jehi,et al.  The Epileptogenic Zone: Concept and Definition , 2018, Epilepsy currents.

[22]  Hans Hallez,et al.  Ictal‐onset localization through connectivity analysis of intracranial EEG signals in patients with refractory epilepsy , 2013, Epilepsia.

[23]  Feng Zhai,et al.  Localization of Epileptogenic Zone With the Correction of Pathological Networks , 2018, Front. Neurol..

[24]  Pei-Ji Liang,et al.  Dynamic Network Connectivity Analysis to Identify Epileptogenic Zones Based on Stereo-Electroencephalography , 2016, Front. Comput. Neurosci..

[25]  Jiaqing Yan,et al.  Determining the Quantitative Threshold of High-Frequency Oscillation Distribution to Delineate the Epileptogenic Zone by Automated Detection , 2018, Front. Neurol..

[26]  Lino Nobili,et al.  Biomarkers of epileptogenic zone defined by quantified stereo‐EEG analysis , 2014, Epilepsia.

[27]  G. Worrell,et al.  Interictal high-frequency oscillations in focal human epilepsy. , 2016, Current opinion in neurology.

[28]  Lorella Minotti,et al.  French guidelines on stereoelectroencephalography (SEEG) , 2017, Neurophysiologie Clinique.

[29]  F. Cendes,et al.  The consequences of refractory epilepsy and its treatment , 2014, Epilepsy & Behavior.

[30]  N. Ince,et al.  Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy , 2018, Brain : a journal of neurology.

[31]  Fabrice Wendling,et al.  Defining epileptogenic networks: Contribution of SEEG and signal analysis , 2017, Epilepsia.

[32]  Mark R. Bower,et al.  Spatiotemporal neuronal correlates of seizure generation in focal epilepsy , 2012, Epilepsia.

[33]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[34]  Sasha Dionisio,et al.  Automatic detection of the epileptogenic zone: An application of the fingerprint of epilepsy , 2019, Journal of Neuroscience Methods.

[35]  Scott B Patten,et al.  Prevalence and incidence of epilepsy , 2017, Neurology.

[36]  Junjie Chen,et al.  The detection of epileptic seizure signals based on fuzzy entropy , 2015, Journal of Neuroscience Methods.

[37]  P. Chauvel,et al.  Epileptogenicity of brain structures in human temporal lobe epilepsy: a quantified study from intracerebral EEG. , 2008, Brain : a journal of neurology.

[38]  Birmohan Singh,et al.  Grasshopper optimization algorithm–based approach for the optimization of ensemble classifier and feature selection to classify epileptic EEG signals , 2019, Medical & Biological Engineering & Computing.

[39]  Daniel Rivero,et al.  Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks , 2010, Journal of Neuroscience Methods.

[40]  Mengyang Wang,et al.  Identification of the epileptogenic zone of temporal lobe epilepsy from stereo-electroencephalography signals: A phase transfer entropy and graph theory approach , 2017, NeuroImage: Clinical.

[41]  Jorge Gonzalez-Martinez,et al.  Is SEEG safe? A systematic review and meta‐analysis of stereo‐electroencephalography–related complications , 2016, Epilepsia.

[42]  Sridevi V. Sarma,et al.  Computing network-based features from intracranial EEG time series data: Application to seizure focus localization , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[43]  Roberto Spreafico,et al.  Identification of the Epileptogenic Zone from Stereo-EEG Signals: A Connectivity-Graph Theory Approach , 2013, Front. Neurol..

[44]  Fabrice Bartolomei,et al.  The repertoire of seizure onset patterns in human focal epilepsies: Determinants and prognostic values , 2018, Epilepsia.

[45]  G. Bergey,et al.  Characterization of early partial seizure onset: Frequency, complexity and entropy , 2012, Clinical Neurophysiology.

[46]  Yong-Hua Li,et al.  Localization of epileptogenic zone based on graph analysis of stereo-EEG , 2016, Epilepsy Research.

[47]  Jorge Gonzalez-Martinez,et al.  Learning to define an electrical biomarker of the epileptogenic zone , 2019, Human brain mapping.

[48]  P. Konrad,et al.  Regional and global connectivity disturbances in focal epilepsy, related neurocognitive sequelae, and potential mechanistic underpinnings , 2016, Epilepsia.

[49]  Arun Ross,et al.  Score normalization in multimodal biometric systems , 2005, Pattern Recognit..

[50]  Ayako Ochi,et al.  Low entropy of interictal gamma oscillations is a biomarker of the seizure onset zone in focal cortical dysplasia type II , 2019, Epilepsy & Behavior.

[51]  H. Lüders,et al.  Presurgical evaluation of epilepsy. , 2001, Brain : a journal of neurology.

[52]  Su Liu,et al.  Exploring the time–frequency content of high frequency oscillations for automated identification of seizure onset zone in epilepsy , 2016, Journal of neural engineering.

[53]  R. Esteller,et al.  Comparison of line length feature before and after brain electrical stimulation in epileptic patients , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[54]  Jorge Gonzalez-Martinez,et al.  A fingerprint of the epileptogenic zone in human epilepsies , 2017, Brain : a journal of neurology.

[55]  Syed Muhammad Usman,et al.  Using scalp EEG and intracranial EEG signals for predicting epileptic seizures: Review of available methodologies , 2019, Seizure.

[56]  Felix Rosenow,et al.  The history of invasive EEG evaluation in epilepsy patients , 2016, Seizure.