Literature DB >> 33450559

Photoparoxysmal response and its characteristics in a large EEG database using the SCORE system.

Pirgit Meritam Larsen1, Stephan Wüstenhagen1, Daniella Terney1, Elena Gardella2, Jørgen Alving1, Harald Aurlien3, Sándor Beniczky4.   

Abstract

OBJECTIVE: To characterize photoparoxysmal EEG response (PPR) using a standardized protocol of intermittent photic stimulation (IPS) and standardized definitions for PPR, classified into six types.
METHODS: Using the SCORE system (Standardized Computer-Based Organized Reporting of EEG) we prospectively built a large database of standardized EEG annotations. In this study, we extracted the features related to PPR from the structured dataset consisting of 10,671 EEG recordings with IPS, from 7,188 patients.
RESULTS: The standardized IPS protocol elicited PPR in 375 recordings (3.5%), in 288 patients (4%), with a preponderance among young (11-20 years) and female patients (67%). PPR was persistent in patients with multiple recordings. The most frequent type of PPR was activation of preexisting epileptogenic area (58%), followed by generalized-PPR limited to the stimulus train (22%). We could not find any recording with self-sustained posterior response. Seizures were elicited in 27% of patients with PPR, most often myoclonic seizures and absences, in patients with self-sustained generalized PPR.
CONCLUSIONS: The most common type of PPR was accentuation of preexisting epileptogenic area. Self-sustained posterior response could not be documented. Self-sustained generalized-PPR had the highest association with seizures. SIGNIFICANCE: Using standardized stimulation protocol and definitions for PPR types, IPS provides high diagnostic yield.
Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Classification; EEG; Epilepsy; Intermittent photic stimulation; Photoparoxysmal response; Photosensitivity

Mesh:

Year:  2021        PMID: 33450559     DOI: 10.1016/j.clinph.2020.10.029

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  2 in total

Review 1.  Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning-clinical application perspectives.

Authors:  Mubeen Janmohamed; Duong Nhu; Levin Kuhlmann; Amanda Gilligan; Chang Wei Tan; Piero Perucca; Terence J O'Brien; Patrick Kwan
Journal:  Brain Commun       Date:  2022-08-29

2.  Implementing the SCORE system improves the quality of clinical EEG reading.

Authors:  Giorgi Japaridze; Sofia Kasradze; Harald Aurlien; Sándor Beniczky
Journal:  Clin Neurophysiol Pract       Date:  2022-09-01
  2 in total

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