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Molecular diagnostics in drug‐resistant focal epilepsy define new disease entities
Author(s) -
Kobow Katja,
Baulac Stéphanie,
Deimling Andreas,
Lee Jeong Ho
Publication year - 2021
Publication title -
brain pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.986
H-Index - 132
eISSN - 1750-3639
pISSN - 1015-6305
DOI - 10.1111/bpa.12963
Subject(s) - epilepsy , medicine , magnetic resonance imaging , epilepsy surgery , disease , pathology , neuroimaging , bioinformatics , radiology , neuroscience , psychology , biology , psychiatry
Structural brain lesions, including the broad range of malformations of cortical development (MCD) and glioneuronal tumors, are among the most common causes of drug‐resistant focal epilepsy. Epilepsy surgery can provide a curative treatment option in respective patients. The currently available pre‐surgical multi‐modal diagnostic armamentarium includes high‐ and ultra‐high resolution magnetic resonance imaging (MRI) and intracerebral EEG to identify a focal structural brain lesion as epilepsy underlying etiology. However, specificity and accuracy in diagnosing the type of lesion have proven to be limited. Moreover, the diagnostic process does not stop with the decision for surgery. The neuropathological diagnosis remains the gold standard for disease classification and patient stratification, but is particularly complex with high inter‐observer variability. Here, the identification of lesion‐specific mosaic variants together with epigenetic profiling of lesional brain tissue became new tools to more reliably identify disease entities. In this review, we will discuss how the paradigm shifts from histopathology toward an integrated diagnostic approach in cancer and the more recent development of the DNA methylation‐based brain tumor classifier have started to influence epilepsy diagnostics. Some examples will be highlighted showing how the diagnosis and our mechanistic understanding of difficult to classify structural brain lesions associated with focal epilepsy has improved with molecular genetic data being considered in decision making.

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