EEG biomarker candidates for the identification of epilepsy

Autor: Stefano Gallotto, Margitta Seeck
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Clinical Neurophysiology Practice, Vol 8, Iss , Pp 32-41 (2023)
Druh dokumentu: article
ISSN: 2467-981X
DOI: 10.1016/j.cnp.2022.11.004
Popis: Electroencephalography (EEG) is one of the main pillars used for the diagnosis and study of epilepsy, readily employed after a possible first seizure has occurred. The most established biomarker of epilepsy, in case seizures are not recorded, are interictal epileptiform discharges (IEDs). In clinical practice, however, IEDs are not always present and the EEG may appear completely normal despite an underlying epileptic disorder, often leading to difficulties in the diagnosis of the disease. Thus, finding other biomarkers that reliably predict whether an individual suffers from epilepsy even in the absence of evident epileptic activity would be extremely helpful, since they could allow shortening the period of diagnostic uncertainty and consequently decreasing the risk of seizure. To date only a few EEG features other than IEDs seem to be promising candidates able to distinguish between epilepsy, i.e. > 60 % risk of recurrent seizures, or other (pathological) conditions. The aim of this narrative review is to provide an overview of the EEG-based biomarker candidates for epilepsy and the techniques employed for their identification.
Databáze: Directory of Open Access Journals