Quantification and Selection of Ictogenic Zones in Epilepsy Surgery.

Laiou, Petroula; Avramidis, Eleftherios; Lopes, Marinho A; Abela, Eugenio; Müller, Michael; Akman, Ozgur E; Richardson, Mark P; Rummel, Christian; Schindler, Kaspar Anton; Goodfellow, Marc (2019). Quantification and Selection of Ictogenic Zones in Epilepsy Surgery. Frontiers in neurology, 10(1045), p. 1045. Frontiers Media S.A. 10.3389/fneur.2019.01045

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Network models of brain dynamics provide valuable insight into the healthy functioning of the brain and how this breaks down in disease. A pertinent example is the use of network models to understand seizure generation (ictogenesis) in epilepsy. Recently, computational models have emerged to aid our understanding of seizures and to predict the outcome of surgical perturbations to brain networks. Such approaches provide the opportunity to quantify the effect of removing regions of tissue from brain networks and thereby search for the optimal resection strategy. Here, we use computational models to elucidate how sets of nodes contribute to the ictogenicity of networks. In small networks we fully elucidate the ictogenicity of all possible sets of nodes and demonstrate that the distribution of ictogenicity across sets depends on network topology. However, the full elucidation is a combinatorial problem that becomes intractable for large networks. Therefore, we combine computational models with a genetic algorithm to search for minimal sets of nodes that contribute significantly to ictogenesis. We demonstrate the potential applicability of these methods in practice by identifying optimal sets of nodes to resect in networks derived from 20 individuals who underwent resective surgery for epilepsy. We show that they have the potential to aid epilepsy surgery by suggesting alternative resection sites as well as facilitating the avoidance of brain regions that should not be resected.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology

UniBE Contributor:

Abela, Eugenio; Müller, Michael; Rummel, Christian and Schindler, Kaspar Anton

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1664-2295

Publisher:

Frontiers Media S.A.

Language:

English

Submitter:

Martin Zbinden

Date Deposited:

29 Oct 2019 16:12

Last Modified:

03 Nov 2019 02:42

Publisher DOI:

10.3389/fneur.2019.01045

PubMed ID:

31632339

Uncontrolled Keywords:

brain networks epilepsy surgery genetic algorithm graph theory ictogenesis optimization

BORIS DOI:

10.7892/boris.134261

URI:

https://boris.unibe.ch/id/eprint/134261

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