Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: "Concordant" if the node identified by DCM matches the presumed focus, "Discordant" if the node is distant from the presumed focus, or "Inconclusive" (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.

fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study / Vaudano, A. E.; Mirandola, L.; Talami, F.; Giovannini, G.; Monti, G.; Riguzzi, P.; Volpi, L.; Michelucci, R.; Bisulli, F.; Pasini, E.; Tinuper, P.; Di Vito, L.; Gessaroli, G.; Malagoli, M.; Pavesi, G.; Cardinale, F.; Tassi, L.; Lemieux, L.; Meletti, S.. - In: BRAIN TOPOGRAPHY. - ISSN 0896-0267. - 34:5(2021), pp. 632-650. [10.1007/s10548-021-00857-x]

fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study

Vaudano A. E.;Giovannini G.;Pavesi G.;Meletti S.
2021

Abstract

Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: "Concordant" if the node identified by DCM matches the presumed focus, "Discordant" if the node is distant from the presumed focus, or "Inconclusive" (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.
2021
34
5
632
650
fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study / Vaudano, A. E.; Mirandola, L.; Talami, F.; Giovannini, G.; Monti, G.; Riguzzi, P.; Volpi, L.; Michelucci, R.; Bisulli, F.; Pasini, E.; Tinuper, P.; Di Vito, L.; Gessaroli, G.; Malagoli, M.; Pavesi, G.; Cardinale, F.; Tassi, L.; Lemieux, L.; Meletti, S.. - In: BRAIN TOPOGRAPHY. - ISSN 0896-0267. - 34:5(2021), pp. 632-650. [10.1007/s10548-021-00857-x]
Vaudano, A. E.; Mirandola, L.; Talami, F.; Giovannini, G.; Monti, G.; Riguzzi, P.; Volpi, L.; Michelucci, R.; Bisulli, F.; Pasini, E.; Tinuper, P.; Di Vito, L.; Gessaroli, G.; Malagoli, M.; Pavesi, G.; Cardinale, F.; Tassi, L.; Lemieux, L.; Meletti, S.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1255658
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