Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients.


Journal

Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065

Informations de publication

Date de publication:
01 08 2020
Historique:
received: 04 10 2019
revised: 18 02 2020
accepted: 11 03 2020
pubmed: 10 5 2020
medline: 11 11 2021
entrez: 10 5 2020
Statut: ppublish

Résumé

Source localization of interictal epileptiform discharges (IEDs) is clinically useful in the presurgical workup of epilepsy patients. We aimed to compare the performance of four different distributed magnetic source imaging (dMSI) approaches: Minimum norm estimate (MNE), dynamic statistical parametric mapping (dSPM), standardized low-resolution electromagnetic tomography (sLORETA), and coherent maximum entropy on the mean (cMEM). We also evaluated whether a simple average of maps obtained from multiple inverse solutions (Ave) can improve localization accuracy. We analyzed dMSI of 206 IEDs derived from magnetoencephalography recordings in 28 focal epilepsy patients who had a well-defined focus determined through intracranial EEG (iEEG), epileptogenic MRI lesions or surgical resection. dMSI accuracy and spatial properties were quantitatively estimated as: (a) distance from the epilepsy focus, (b) reproducibility, (c) spatial dispersion (SD), (d) map extension, and (e) effect of thresholding on map properties. Clinical performance was excellent for all methods (median distance from the focus MNE = 2.4 mm; sLORETA = 3.5 mm; cMEM = 3.5 mm; dSPM = 6.8 mm, Ave = 0 mm). Ave showed the lowest distance between the map maximum and epilepsy focus (Dmin lower than cMEM, MNE, and dSPM, p = .021, p = .008, p < .001, respectively). cMEM showed the best spatial features, with lowest SD outside the focus (SD lower than all other methods, p < .001 consistently) and high contrast between the generator and surrounding regions. The average map Ave provided the best localization accuracy, whereas cMEM exhibited the lowest amount of spurious distant activity. dMSI techniques have the potential to significantly improve identification of iEEG targets and to guide surgical planning, especially when multiple methods are combined.

Identifiants

pubmed: 32386115
doi: 10.1002/hbm.24994
pmc: PMC7336148
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3019-3033

Subventions

Organisme : CIHR
ID : MOP-93614
Pays : Canada
Organisme : CIHR
ID : MOP‐159948
Pays : Canada
Organisme : CIHR
ID : PJT‐133619
Pays : Canada

Informations de copyright

© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

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Auteurs

Giovanni Pellegrino (G)

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
IRCCS Fondazione San Camillo Hospital, Venice, Italy.
Department of Multimodal Functional Imaging Lab, Biomedical Engineering, McGill University, Montreal, Quebec, Canada.

Tanguy Hedrich (T)

Department of Multimodal Functional Imaging Lab, Biomedical Engineering, McGill University, Montreal, Quebec, Canada.

Manuel Porras-Bettancourt (M)

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.

Jean-Marc Lina (JM)

Departement de Genie Electrique, Ecole de Technologie Superieure, Montreal, Quebec, Canada.
Centre de Recherches Mathematiques, Montréal, Quebec, Canada.

Ümit Aydin (Ü)

Physics Department and PERFORM Centre, Concordia University, Montreal, Quebec, Canada.

Jeffery Hall (J)

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.

Christophe Grova (C)

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
Department of Multimodal Functional Imaging Lab, Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
Centre de Recherches Mathematiques, Montréal, Quebec, Canada.
Physics Department and PERFORM Centre, Concordia University, Montreal, Quebec, Canada.

Eliane Kobayashi (E)

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.

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