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Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data
OBJECTIVE: To compare the location of suspect lesions detected by computational analysis of multimodal magnetic resonance imaging data with areas of seizure onset, early propagation, and interictal epileptiform discharges (IEDs) identified with stereoelectroencephalography (SEEG) in a cohort of pati...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8436754/ https://www.ncbi.nlm.nih.gov/pubmed/33567113 http://dx.doi.org/10.1111/epi.16836 |
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author | Kanber, Baris Vos, Sjoerd B. de Tisi, Jane Wood, Tobias C. Barker, Gareth J. Rodionov, Roman Chowdhury, Fahmida Amin Thom, Maria Alexander, Daniel C. Duncan, John S. Winston, Gavin P. |
author_facet | Kanber, Baris Vos, Sjoerd B. de Tisi, Jane Wood, Tobias C. Barker, Gareth J. Rodionov, Roman Chowdhury, Fahmida Amin Thom, Maria Alexander, Daniel C. Duncan, John S. Winston, Gavin P. |
author_sort | Kanber, Baris |
collection | PubMed |
description | OBJECTIVE: To compare the location of suspect lesions detected by computational analysis of multimodal magnetic resonance imaging data with areas of seizure onset, early propagation, and interictal epileptiform discharges (IEDs) identified with stereoelectroencephalography (SEEG) in a cohort of patients with medically refractory focal epilepsy and radiologically normal magnetic resonance imaging (MRI) scans. METHODS: We developed a method of lesion detection using computational analysis of multimodal MRI data in a cohort of 62 control subjects, and 42 patients with focal epilepsy and MRI‐visible lesions. We then applied it to detect covert lesions in 27 focal epilepsy patients with radiologically normal MRI scans, comparing our findings with the areas of seizure onset, early propagation, and IEDs identified at SEEG. RESULTS: Seizure‐onset zones (SoZs) were identified at SEEG in 18 of the 27 patients (67%) with radiologically normal MRI scans. In 11 of these 18 cases (61%), concordant abnormalities were detected by our method. In the remaining seven cases, either early seizure propagation or IEDs were observed within the abnormalities detected, or there were additional areas of imaging abnormalities found by our method that were not sampled at SEEG. In one of the nine patients (11%) in whom SEEG was inconclusive, an abnormality, which may have been involved in seizures, was identified by our method and was not sampled at SEEG. SIGNIFICANCE: Computational analysis of multimodal MRI data revealed covert abnormalities in the majority of patients with refractory focal epilepsy and radiologically normal MRI that co‐located with SEEG defined zones of seizure onset. The method could help identify areas that should be targeted with SEEG when considering epilepsy surgery. |
format | Online Article Text |
id | pubmed-8436754 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84367542021-09-17 Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data Kanber, Baris Vos, Sjoerd B. de Tisi, Jane Wood, Tobias C. Barker, Gareth J. Rodionov, Roman Chowdhury, Fahmida Amin Thom, Maria Alexander, Daniel C. Duncan, John S. Winston, Gavin P. Epilepsia Full‐length Original Research OBJECTIVE: To compare the location of suspect lesions detected by computational analysis of multimodal magnetic resonance imaging data with areas of seizure onset, early propagation, and interictal epileptiform discharges (IEDs) identified with stereoelectroencephalography (SEEG) in a cohort of patients with medically refractory focal epilepsy and radiologically normal magnetic resonance imaging (MRI) scans. METHODS: We developed a method of lesion detection using computational analysis of multimodal MRI data in a cohort of 62 control subjects, and 42 patients with focal epilepsy and MRI‐visible lesions. We then applied it to detect covert lesions in 27 focal epilepsy patients with radiologically normal MRI scans, comparing our findings with the areas of seizure onset, early propagation, and IEDs identified at SEEG. RESULTS: Seizure‐onset zones (SoZs) were identified at SEEG in 18 of the 27 patients (67%) with radiologically normal MRI scans. In 11 of these 18 cases (61%), concordant abnormalities were detected by our method. In the remaining seven cases, either early seizure propagation or IEDs were observed within the abnormalities detected, or there were additional areas of imaging abnormalities found by our method that were not sampled at SEEG. In one of the nine patients (11%) in whom SEEG was inconclusive, an abnormality, which may have been involved in seizures, was identified by our method and was not sampled at SEEG. SIGNIFICANCE: Computational analysis of multimodal MRI data revealed covert abnormalities in the majority of patients with refractory focal epilepsy and radiologically normal MRI that co‐located with SEEG defined zones of seizure onset. The method could help identify areas that should be targeted with SEEG when considering epilepsy surgery. John Wiley and Sons Inc. 2021-02-10 2021-03 /pmc/articles/PMC8436754/ /pubmed/33567113 http://dx.doi.org/10.1111/epi.16836 Text en © 2021 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Full‐length Original Research Kanber, Baris Vos, Sjoerd B. de Tisi, Jane Wood, Tobias C. Barker, Gareth J. Rodionov, Roman Chowdhury, Fahmida Amin Thom, Maria Alexander, Daniel C. Duncan, John S. Winston, Gavin P. Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
title | Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
title_full | Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
title_fullStr | Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
title_full_unstemmed | Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
title_short | Detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
title_sort | detection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data |
topic | Full‐length Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8436754/ https://www.ncbi.nlm.nih.gov/pubmed/33567113 http://dx.doi.org/10.1111/epi.16836 |
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