Identifying epileptogenic abnormalities through spatial clustering of MEG interictal band power.

Autor: Owen TW; CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK., Janiukstyte V; CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK., Hall GR; CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK., Horsley JJ; CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK., McEvoy A; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK., Miserocchi A; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK., de Tisi J; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK.; NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London, UK., Duncan JS; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK.; NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London, UK., Rugg-Gunn F; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK., Wang Y; CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK.; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK., Taylor PN; CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.; UCL Queen Square Institute of Neurology, London, UK.; National Hospital for Neurology & Neurosurgery, London, UK.; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
Jazyk: angličtina
Zdroj: Epilepsia open [Epilepsia Open] 2023 Sep; Vol. 8 (3), pp. 1151-1156. Date of Electronic Publication: 2023 Jun 05.
DOI: 10.1002/epi4.12767
Abstrakt: Successful epilepsy surgery depends on localizing and resecting cerebral abnormalities and networks that generate seizures. Abnormalities, however, may be widely distributed across multiple discontiguous areas. We propose spatially constrained clusters as candidate areas for further investigation and potential resection. We quantified the spatial overlap between the abnormality cluster and subsequent resection, hypothesizing a greater overlap in seizure-free patients. Thirty-four individuals with refractory focal epilepsy underwent pre-surgical resting-state interictal magnetoencephalography (MEG) recording. Fourteen individuals were totally seizure-free (ILAE 1) after surgery and 20 continued to have some seizures post-operatively (ILAE 2+). Band power abnormality maps were derived using controls as a baseline. Patient abnormalities were spatially clustered using the k-means algorithm. The tissue within the cluster containing the most abnormal region was compared with the resection volume using the dice score. The proposed abnormality cluster overlapped with the resection in 71% of ILAE 1 patients. Conversely, an overlap only occurred in 15% of ILAE 2+ patients. This effect discriminated outcome groups well (AUC = 0.82). Our novel approach identifies clusters of spatially similar tissue with high abnormality. This is clinically valuable, providing (a) a data-driven framework to validate current hypotheses of the epileptogenic zone localization or (b) to guide further investigation.
(© 2023 The Authors. Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)
Databáze: MEDLINE
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