Epilepsy Clinical Trial
Official title:
Investigation of Human Epileptic Networks by fMRI Based Effective Connectivity: a New Approach to Identify the Neuronal Drivers of the Pathological Activity in Surgically Remediable Epilepsies
Background:
In the Emilia-Romagna Region approximately 19.000 people are affected by epilepsy. About 25%
of epileptic patients are drug-resistant (DRE) and some of them are eligible for resective
surgery of the epileptogenic zone (EZ). The precise EZ localization is crucial for a good
surgical outcome. Intracranial EEG (icEEG) recordings remain the gold-standard to localise
the EZ. New neuroimaging techniques, like simultaneous recording of functional MRI and EEG
(EEG-fMRI), with advanced methodological approaches as effective connectivity analysis (i.e.
Dynamic Causal Modelling-DCM) might improve the EZ localization.
Objectives:
(1) To develop a non-invasive protocol for the investigation of the epileptic network in
patients with surgically remediable epilepsies; (2) To shed light on the patho-physiological
mechanisms of drug resistance in DRE; (3) To provide a validation of effective connectivity
applied to fMRI data in epilepsy.
Methods:
Two Research Units (RU1, RU2) will identify and characterize a cohort of DRE patients
eligible for resective surgery. RU1 will be in charge to perform the EEG/fMRI coregistration
and data analysis. RU2 will be responsible for the surgical resection of epileptic foci.
IcEEG recordings will be performed at the Claudio Munari Epilepsy Center, Ospedale Niguarda,
Milano. RU1&RU2 will evaluate the fMRI data results and compare with icEEG findings or
expert's surgical decision. The principle measures of outcome are: (a) percentage of
concordance of fMRI results with icEEG findings or electro-clinical features in term
epileptic network identification; (b) percentage of concordance between DCM findings and
EZ/IZ localization; (c) percentage of concordance of DCM findings with icEEG or
electro-clinical features regarding the causal hierarchy within the epileptic network.
Background:
About 25% of epileptic patients are drug-resistant (DRE) and some of them are eligible for
resective surgery of the epileptogenic zone (EZ). The precise EZ localization is crucial for
a good surgical outcome. Intracranial EEG (icEEG) recordings remain the gold-standard to
localise the EZ. New neuroimaging techniques, like simultaneous recording of functional MRI
and EEG (EEG-fMRI), with advanced methodological approaches as effective connectivity
analysis (i.e. Dynamic Causal Modelling-DCM) might improve the EZ localization. This
innovative tool will have the advantage to be non-invasive and safe with significant decrease
of injuries, hospitalization, with a resulting favourable cost/benefit ratio.
Objectives:
(1) to provide a validation of effective connectivity applied to fMRI data in epilepsy. (2)To
develop a non-invasive protocol for the investigation of the epileptic network in patients
with surgically remediable epilepsies; (3) To shed light on the patho-physiological
mechanisms of drug resistance in DRE.
Methods:
Two Research Units (RU1, RU2) will identify and characterize a cohort of DRE patients
eligible for resective surgery. RU1 will perform patients' recruitment, presurgical
evaluation and EEG/fMRI coregistration and data analysis. RU2 will perform patients'
recruitment, presurgical evaluation and surgical resection of epileptic foci. IcEEG
recordings will be performed at the Claudio Munari Epilepsy Center, Ospedale Niguarda, Milano
. RU1&RU2 will evaluate the fMRI data results and compare with icEEG findings or expert's
surgical decision. The principle measures of outcome are: (a) percentage of concordance of
fMRI results with icEEG findings or electro-clinical features in term epileptic network
identification; (b) percentage of concordance between DCM findings and EZ/IZ localization;
(c) percentage of concordance of DCM findings with icEEG or electro-clinical features
regarding the causal hierarchy within the epileptic network.
;
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