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Publication Detail
Probabilistic landscape of seizure semiology localising values
  • Publication Type:
    Journal article
  • Authors:
    Alim-Marvasti A, Romagnoli G, Dahele K, Modarres H, Pérez-García F, Sparks R, Ourselin S, Clarkson MJ, Chowdhury F, Diehl B, Duncan JS
  • Publisher:
    Oxford University Press (OUP)
  • Publication date:
    19/05/2022
  • Journal:
    Brain Communications
  • Status:
    Accepted
  • Language:
    English
  • Keywords:
    phenotype, data-driven, cortical localisation, epilepsy surgery, presurgical
  • Notes:
    © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
Abstract
Semiology describes the evolution of symptoms and signs during epileptic seizures and contributes to the evaluation of individuals with focal drug-resistant epilepsy for curative resection. Semiology varies in complexity from elementary sensorimotor seizures arising from primary cortex to complex behaviours and automatisms emerging from distributed cerebral networks. Detailed semiology interpreted by expert epileptologists may point towards the likely site of seizure onset, but this process is subjective. No study has captured the variances in semiological localising values in a data-driven manner to allow objective and probabilistic determinations of implicated networks and nodes. We curated an open dataset from the epilepsy literature, in accordance with PRISMA guidelines, linking semiology to hierarchical brain localisations. A total of 11230 datapoints were collected from 4643 patients across 309 articles, labelled using ground-truths (postoperative seizure-freedom, concordance of imaging and neurophysiology, and/or invasive EEG) and a designation method that distinguished between semiologies arising from a predefined cortical region and descriptions of neuroanatomical localisations responsible for generating a particular semiology. This allowed us to mitigate temporal lobe publication bias by filtering studies that preselected patients based on prior knowledge of their seizure-foci. Using this dataset, we describe the probabilistic landscape of semiological localising values as forest plots at the resolution of seven major brain regions: temporal, frontal, cingulate, parietal, occipital, insula, and hypothalamus, and five temporal subregions. We evaluated the intrinsic value of any one semiology over all other ictal manifestations. For example, epigastric auras implicated the temporal lobe with 83% probability when not accounting for the publication bias that favoured temporal lobe epilepsies. Unbiased results for a prior distribution of cortical localisations revised the prevalence of temporal lobe epilepsies from 66% to 44%. Therefore, knowledge about the presence of epigastric auras updates localisation to the temporal lobe with an odds ratio (OR) of 2.4 (CI_{95%} [1.9, 2.9]; and specifically, mesial temporal structures OR 2.8[2.3, 2.9]), attesting the value of epigastric auras. As a further example, although head version is thought to implicate the frontal lobes, it did not add localising value compared to the prior distribution of cortical localisations (OR 0.9[0.7, 1.2]). Objectification of the localising values of the twelve most common semiologies provides a complementary view of brain dysfunction to that of lesion-deficit mappings, as instead of linking brain regions to phenotypic-deficits, semiological phenotypes are linked back to brain sources. This work enables coupling of seizure-propagation with ictal-manifestations, and clinical support algorithms for localising seizure phenotypes.
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Author
Dept of Med Phys & Biomedical Eng
Author
Clinical & Experimental Epilepsy
Author
Clinical & Experimental Epilepsy
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