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Virtual MEG sensors based on beamformer and independent component analysis can reconstruct epileptic activity as measured on simultaneous intracerebral recordings.
Velmurugan, Jayabal; Badier, Jean-Michel; Pizzo, Francesca; Medina Villalon, Samuel; Papageorgakis, Christos; López-Madrona, Victor; Jegou, Aude; Carron, Romain; Bartolomei, Fabrice; Bénar, Christian-G.
Afiliação
  • Velmurugan J; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
  • Badier JM; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
  • Pizzo F; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France.
  • Medina Villalon S; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France.
  • Papageorgakis C; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
  • López-Madrona V; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
  • Jegou A; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
  • Carron R; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, F-13005, France.
  • Bartolomei F; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France.
  • Bénar CG; Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France. Electronic address: christian.benar@univ-amu.fr.
Neuroimage ; 264: 119681, 2022 12 01.
Article em En | MEDLINE | ID: mdl-36270623
ABSTRACT
The prevailing gold standard for presurgical determination of epileptogenic brain networks is intracerebral EEG, a potent yet invasive approach. Magnetoencephalography (MEG) is a state-of-the art non-invasive method for investigating epileptiform discharges. However, it is not clear at what level the precision offered by MEG can reach that of SEEG. Here, we present a strategy for non-invasively retrieving the constituents of the interictal network, with high spatial and temporal precision. Our method is based on MEG and a combination of spatial filtering and independent component analysis (ICA). We validated this approach in twelve patients with drug-resistant focal epilepsy, thanks to the unprecedented ground truth provided by simultaneous recordings of MEG and SEEG. A minimum variance adaptive beamformer estimated the source time series and ICA was used to further decompose these time series into network constituents (MEG-ICs), each having a time series (virtual electrode) and a topography (spatial distribution of amplitudes in the brain). We show that MEG has a considerable sensitivity of 0.80 and 0.84 and a specificity of 0.93 and 0.91 for reconstructing deep and superficial sources, respectively, when compared to the ground truth (SEEG). For each epileptic MEG-IC (n = 131), we found at least one significantly correlating SEEG contact close to zero lag after correcting for multiple comparisons. All the patients except one had at least one epileptic component that was highly correlated (Spearman rho>0.3) with that of SEEG traces. MEG-ICs correlated well with SEEG traces. The strength of correlation coefficients did not depend on the depth of the SEEG contacts or the clinical outcome of the patient. A significant proportion of the MEG-ICs (n = 83/131) were localized in proximity with their maximally correlating SEEG, within a mean distance of 20±12.18mm. Our research is the first to validate the MEG-retrieved beamformer IC sources against SEEG-derived ground truth in a simultaneous MEG-SEEG framework. Observations from the present study suggest that non-invasive MEG source components may potentially provide additional information, comparable to SEEG in a number of instances.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Epilepsia / Epilepsia Resistente a Medicamentos Limite: Humans Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Epilepsia / Epilepsia Resistente a Medicamentos Limite: Humans Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França