[Paper Review] A library of quantitative markers of seizure severity

Sarah J. Gascoigne, Leonard Waldmann+17 more|arXiv (Cornell University)|Jun 30, 2022

EEG and Brain-Computer Interfaces4 citations

TL;DR

This paper introduces a library of 16 quantitative EEG markers to objectively assess seizure severity using intracranial EEG data from 63 patients and 1,009 seizures. The markers capture signal magnitude, spread, duration, and post-ictal suppression, and they successfully distinguish focal from subclinical seizures and reveal circadian and long-term fluctuations in severity across individuals.

ABSTRACT

Purpose: Understanding fluctuations of seizure severity within individuals is important for defining treatment outcomes and response to therapy, as well as developing novel treatments for epilepsy. Current methods for grading seizure severity rely on qualitative interpretations from patients and clinicians. Quantitative measures of seizure severity would complement existing approaches, for EEG monitoring, outcome monitoring, and seizure prediction. Therefore, we developed a library of quantitative electroencephalographic (EEG) markers that assess the spread and intensity of abnormal electrical activity during and after seizures. Methods: We analysed intracranial EEG (iEEG) recordings of 1056 seizures from 63 patients. For each seizure, we computed 16 markers of seizure severity that capture the signal magnitude, spread, duration, and post-ictal suppression of seizures. Results: Quantitative EEG markers of seizure severity distinguished focal vs. subclinical and focal vs. FTBTC seizures across patients. In individual patients, 71% had a moderate to large difference (ranksum r > 0.3) between focal and subclinical seizures in three or more markers. Circadian and longer-term changes in severity were found for 67% and 53% of patients, respectively. Conclusion: We demonstrate the feasibility of using quantitative iEEG markers to measure seizure severity. Our quantitative markers distinguish between seizure types and are therefore sensitive to established qualitative differences in seizure severity. Our results also suggest that seizure severity is modulated over different timescales. We envisage that our proposed seizure severity library will be expanded and updated in collaboration with the epilepsy research community to include more measures and modalities.

Motivation & Objective

• To address the lack of objective, quantitative measures for seizure severity in epilepsy, which currently rely on subjective patient or clinician reports.
• To develop a library of interpretable, EEG-based markers that capture key features of seizure dynamics such as spread, intensity, duration, and post-ictal suppression.
• To validate whether these quantitative markers can distinguish clinically distinct seizure types, particularly focal versus subclinical seizures.
• To investigate whether seizure severity fluctuates over circadian and longer-term timescales in individual patients.
• To establish a foundation for an expandable, community-driven library of seizure severity markers for use in clinical monitoring, treatment evaluation, and seizure prediction.

Proposed method

• The study analyzed intracranial EEG (iEEG) recordings from 1,009 seizures across 63 epilepsy patients, collected in a clinical monitoring setting.
• Sixteen quantitative markers were computed per seizure, including measures of signal magnitude (e.g., peak amplitude, energy), spatial spread (e.g., line length, channel count), duration, and post-ictal suppression (e.g., major suppression duration, suppression strength).
• Markers were derived from high-density iEEG signals, with spatial spread quantified via electrode connectivity and signal propagation metrics.
• Statistical comparisons were performed using the Wilcoxon rank-sum test to assess differences in marker values between focal and subclinical seizures.
• Circular linear correlation and Spearman’s rank correlation were used to assess relationships between marker values and time of day or time in the EEG monitoring unit.
• Permutation tests with 1,000 iterations were applied to assess significance of correlations with time of day.

Experimental results

Research questions

• RQ1 Can quantitative EEG markers objectively distinguish between clinically distinct seizure types, such as focal and subclinical seizures?
• RQ2 Do individual patients exhibit measurable fluctuations in seizure severity over circadian or longer-term timescales?
• RQ3 Which specific EEG markers show significant temporal correlations with seizure occurrence time (e.g., day/night patterns)?
• RQ4 How consistent are the quantitative severity markers across patients in reflecting known clinical distinctions in seizure severity?
• RQ5 To what extent do post-ictal suppression and spatial spread of seizure activity vary over time within individual patients?

Key findings

• Fifty-three percent of patients showed a moderate to large difference (ranksum r > 0.3, p < 0.05) between focal and subclinical seizures in three or more quantitative markers.
• Seizure severity markers revealed circadian and longer-term fluctuations in severity for the majority of patients, as indicated by significant correlations between markers and time of day or time in the monitoring unit.
• Markers such as major suppression duration, suppression strength, and duration showed significant correlations with time of day in multiple patients (p < 0.05, permutation test).
• Spatial spread markers (e.g., line length, channel count) and power-based features (e.g., δ, θ, β band power) exhibited significant temporal correlations with seizure timing in several patients.
• The library of markers successfully distinguished focal from subclinical seizures across patients, demonstrating their sensitivity to clinically relevant differences in severity.
• The study identified patient-specific patterns of severity modulation, including circadian rhythms in subclinical seizures and dynamic changes in suppression and spread over time.