The role of high-frequency oscillations in epilepsy surgery planning

Gloss, David; Nevitt, Sarah J; Staba, Richard J.

doi:10.1002/14651858.cd010235.pub3

Cited by 32 publications

(25 citation statements)

References 76 publications

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“…Similar inconclusive results hold in completed prospective studies of HFOs. In 2017, an updated Cochrane review by Gloss et al [108] investigated the clinical value of HFOs regarding decision making in epilepsy surgery. They identified only two prospective studies at the time and concluded that there is not enough evidence so far to allow for any reliable conclusions regarding the clinical value of HFOs as a marker for the SOZ.…”

Section: Discussionmentioning

confidence: 99%

Neural Fragility as an EEG Marker of the Seizure Onset Zone

Huynh

Fitzgerald

et al. 2019

Preprint

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Epilepsy is a global epidemic and 30% of the 60 million patients do not respond to medication treatment. The only treatment options for patients with medically refractory epilepsy are surgical removal or electrical stimulation of the epileptogenic zone (EZ) i.e. the source of their seizures. Despite extensive evaluations with neuroimaging, visual EEG analysis and clinical testing, surgical success rates vary between 30-70%. Currently, no computational methods have been translated into the clinic to assist in localizing the EZ. Here, we applied a dynamical network model that quantifies the fragility of nodes within a patient's intracranial EEG (iEEG) brain network. Fragility is quantified as the minimal amount of perturbation that must to be applied to a node's influence on a "balanced" network to cause imbalance. Here, a balanced network is one in which the connectivity between excitatory and inhibitory nodes render a stable system, and an imbalanced network is unstable and hence can generate seizures. Using iEEG data from 91 patients treated across 5 epilepsy centers (44 successes, 47 failures), we demonstrated that nodal fragility is greater in electrodes within the EZ. In addition, we compared fragility of iEEG nodes to 7 frequency-based and 14 graph theoretic features of the EZ in both seizure (n=91) and non-seizure data (n=54). We calculated a confidence statistic, defined as the ratio of the value of a given feature averaged across electrodes in the clinically annotated seizure onset zone to its average across all other electrodes. Fragility has a significantly greater effect size difference between surgical outcomes when compared to other features. This novel feature, outperformed the most popular iEEG features when comparing across surgical outcomes, possibly defining a superior network-based EEG fingerprint for the EZ.1 Also reachable at adam2392 at gmail dot com. For more information, visit the NCSL website: https://sarmalab.icm.jhu.edu/.

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Section: Discussionmentioning

confidence: 99%

Neural Fragility as an EEG Marker of the Seizure Onset Zone

Huynh

Fitzgerald

et al. 2019

Preprint

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“…High frequency Oscillations (HFOs) are believed as a potential marker for detection of epileptogenicity and predictive factor for epilepsy surgery outcome. However, a meta-analysis was able to show the significant but small relation between removal of HFO-generating brain region and outcome [62][63][64].…”

Section: Recent Advance In Epilepsy Surgerymentioning

confidence: 99%

Presurgical Evaluation of Epilepsy Surgery

Poon¹

2021

Epilepsy - Update on Classification, Etiologies, Instrumental Diagnosis and Treatment

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Drug-resistant epilepsy (DRE) is defined as failure of two adequate trials of appropriately chosen and administered antiepileptic drugs. Approximately about 30% of epilepsy patients are drug resistant. Accountable reasons to treatment failure including failure to recognize epilepsy syndrome, poor drug compliance, lifestyle factors, etc. In modern era of medicine, DRE patient should be encouraged to have early referral to tertiary epilepsy centre for presurgical evaluation. Comprehensive neurophysiology, structural neuroimaging, and neuropsychological and psychiatric assessment are regarded as essential elements. Invasive electroencephalography (EEG) monitoring in terms of subdural electrodes, depth electrodes, foramen ovale electrodes, and more advanced technique using stereoelectroencephalography (SEEG) are strong armamentarium for epilepsy surgeon. Epilepsy surgery in terms of resection, disconnection, or neuro-modulation should be recommended after a multi-disciplinary agreement.

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“…Other studies have not found a predictive value in the removal of these regions 84,88 and two meta-analyses of existing studies concluded that the evidence of HFOs as a predictor of surgical outcome is weak. 85,97 Furthermore, several studies have also questioned the reproducibility and reliability of HFOs as a marker. 46,87,88,98,99 First, no consensus has been reached on the exact features used to describe HFOs, because the exact underlying cellular mechanism by which they are generated remains unknown, 87 which gives rise to variability in the features chosen to define HFOs among current studies.…”

Section: Why the Source-sink Algorithm May Agree With Clinicians In Failure Patientsmentioning

confidence: 99%

Source-sink connectivity: A novel interictal EEG marker for seizure localization

Gunnarsdottir

Smith

et al. 2021

Preprint

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Over 15 million epilepsy patients worldwide have medically refractory epilepsy (MRE), i.e., they do not respond to anti-epileptic drugs. Successful surgery is a hopeful alternative for seizure freedom but can only be achieved through complete resection or disconnection of the epileptogenic zone (EZ), the brain region(s) where seizures originate. Unfortunately, surgical success rates vary between 30%-70% because no clinically validated biological markers of the EZ exist. Localizing the EZ has thus become a costly and time-consuming process during which a team of clinicians obtain non-invasive neuroimaging data, which is often followed by invasive monitoring involving days-to-weeks of EEG recordings captured intracranially (iEEG). Clinicians visually inspect iEEG data, looking for abnormal activity (e.g., low-voltage high frequency activity) on individual channels occurring immediately before seizures. They also look for abnormal spikes that occur on iEEG between seizures ("resting-state"). In the end, clinicians use <1% of the iEEG data captured to assist in EZ localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored data to better diagnose and treat patients. Intracranial EEG offers a unique opportunity to observe rich epileptic cortical network dynamics but waiting for seizures to occur increases patient risks associated invasive monitoring. In this study, we aim to leverage iEEG data in between seizures by developing a new networked-based resting-state iEEG marker of the EZ. We hypothesize that when a patient is not seizing, it is because the EZ is inhibited by neighboring nodes. We develop an algorithm that identifies two groups of nodes from the resting-state iEEG network: those that are continuously inhibiting a set of neighboring nodes ("sources") and the inhibited nodes themselves ("sinks"). Specifically, patient-specific dynamical network models (DNMs) are estimated from minutes of iEEG and their connectivity properties reveal top sources and sinks in the network, with each node being quantified by a source-sink index (SSI). We validate the SSI index in a retrospective analysis of 65 patients by using the SSI of the annotated EZ as a metric to predict surgical outcomes. SSI predicts with an accuracy of 79%, compared to the accuracy of clinicians being 43% (successful outcomes). In failed outcomes, we identify regions of the brain with high SSIs that were untreated. When compared to high frequency oscillations, the most common resting-state iEEG feature proposed for EZ localization, SSI outperformed in predictive power (by a factor of 1.2) suggesting SSI as a resting-state EEG fingerprint of the EZ.

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The role of high-frequency oscillations in epilepsy surgery planning

Cited by 32 publications

References 76 publications

Neural Fragility as an EEG Marker of the Seizure Onset Zone

Neural Fragility as an EEG Marker of the Seizure Onset Zone

Presurgical Evaluation of Epilepsy Surgery

Source-sink connectivity: A novel interictal EEG marker for seizure localization

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