Epileptogenic Network Visualisation With Advanced MRI (EPIVAM)
Primary Purpose
Drug Resistant Epilepsy
Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Advanced MRI
Sponsored by
About this trial
This is an interventional diagnostic trial for Drug Resistant Epilepsy focused on measuring epilepsy, network, non-invasive investigation
Eligibility Criteria
Inclusion Criteria: Patient suffering from drug-resistant epilepsy Patient already selected for SEEG implantation as part of their epileptic networks Exclusion Criteria: Patient excluded from SEEG (pregnant women, children too young for the procedure, patient unable to undergo the procedure) Contra-indication for MRI
Sites / Locations
Arms of the Study
Arm 1
Arm Type
Experimental
Arm Label
Single Arm
Arm Description
Single Arm
Outcomes
Primary Outcome Measures
Network identification with MRI
Analysis of the anatomical overlap of radiological network (with MRI) and the electrophysiological network (with SEEG) using coregistration and a sublobar analysis. Overlap will be quantified in %.
Prognosis of network targetting with surgery
Analysis of the impact on epileptic outcome in accordance with effect of the surgery on the network. The impact of the surgery on the network will be assessed by coregistration to determine which part of the network has been removed or disconnected. The epileptic outcome will be assessed using the Engel classification
Interest of adding epileptic network radiological analysis in a standard epileptic work-up
Analyse the impact on therapeutic and/or diagnostic decision of the network radiological analysis in a standard clinical practice. This impact will be assessed by measuring the change in the type of decision (further work-up, invasive EEG, "curative" surgery, "palliative" surgery or no modification) or the modification in the extent of surgery (more/less electrodes for invasive EEG, more/less tissue targeted with surgery)
Secondary Outcome Measures
Network quantification
Analysis of the strength of the network using radiological data (r², Z-score, diffusion metrics obtained via microfingerprinting such as fiber volume fraction and fiber fraction) vs electrophysiological metrics (epileptogenic index, h²)
Network regulation with surgery
Analysis of the impact of the surgery on the radiological parameters of the network cited in outcome 4 (r² and Z-score for rsfMRI, number of tracts for tractography and strenght of tract with fiber fraction and fiber volume fraction for microfingerprinting)
Full Information
NCT ID
NCT06059157
First Posted
September 6, 2023
Last Updated
September 22, 2023
Sponsor
Cliniques universitaires Saint-Luc- Université Catholique de Louvain
1. Study Identification
Unique Protocol Identification Number
NCT06059157
Brief Title
Epileptogenic Network Visualisation With Advanced MRI
Acronym
EPIVAM
Official Title
Epileptogenic Network Visualisation With Advanced MRI
Study Type
Interventional
2. Study Status
Record Verification Date
September 2023
Overall Recruitment Status
Not yet recruiting
Study Start Date
October 2023 (Anticipated)
Primary Completion Date
October 2026 (Anticipated)
Study Completion Date
October 2029 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Cliniques universitaires Saint-Luc- Université Catholique de Louvain
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes
5. Study Description
Brief Summary
The goal of this clinical trial is to improve non-invasive identification of epileptogenic networks in drug-resistant epileptic patient.
The investigators aim to compare epileptogenic network identification with stereo-EEG (used as glod standard) with the identification of the same network using advanced MRI (rs-fMRI, microstructural analysis of white matter, ...). The main goals are to:
Compare the accuracy of network identification.
Analyse the effect of the MRI sequences on candidates selection and target identification.
Participants will already have been selected for stereoEEG and will undergo a supplementary MRI (about 1h) with the additional MRI sequences. Follow-up MRI are scheduled for patient undergoing a second, therapeutic epileptic surgery.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Drug Resistant Epilepsy
Keywords
epilepsy, network, non-invasive investigation
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
80 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Single Arm
Arm Type
Experimental
Arm Description
Single Arm
Intervention Type
Device
Intervention Name(s)
Advanced MRI
Intervention Description
resting-state functional MRI, diffusion with advanced post-processing (microstructure analysis), myelin mapping
Primary Outcome Measure Information:
Title
Network identification with MRI
Description
Analysis of the anatomical overlap of radiological network (with MRI) and the electrophysiological network (with SEEG) using coregistration and a sublobar analysis. Overlap will be quantified in %.
Time Frame
At the end of phase 1 - expected to be 3 years after first inclusion
Title
Prognosis of network targetting with surgery
Description
Analysis of the impact on epileptic outcome in accordance with effect of the surgery on the network. The impact of the surgery on the network will be assessed by coregistration to determine which part of the network has been removed or disconnected. The epileptic outcome will be assessed using the Engel classification
Time Frame
One year after surgery (phase 2)
Title
Interest of adding epileptic network radiological analysis in a standard epileptic work-up
Description
Analyse the impact on therapeutic and/or diagnostic decision of the network radiological analysis in a standard clinical practice. This impact will be assessed by measuring the change in the type of decision (further work-up, invasive EEG, "curative" surgery, "palliative" surgery or no modification) or the modification in the extent of surgery (more/less electrodes for invasive EEG, more/less tissue targeted with surgery)
Time Frame
Approximately 1 year after the start of phase 3
Secondary Outcome Measure Information:
Title
Network quantification
Description
Analysis of the strength of the network using radiological data (r², Z-score, diffusion metrics obtained via microfingerprinting such as fiber volume fraction and fiber fraction) vs electrophysiological metrics (epileptogenic index, h²)
Time Frame
At the end of phase 1 - expected to be 3 years after first inclusion
Title
Network regulation with surgery
Description
Analysis of the impact of the surgery on the radiological parameters of the network cited in outcome 4 (r² and Z-score for rsfMRI, number of tracts for tractography and strenght of tract with fiber fraction and fiber volume fraction for microfingerprinting)
Time Frame
One year after surgery (phase 2)
10. Eligibility
Sex
All
Minimum Age & Unit of Time
3 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Patient suffering from drug-resistant epilepsy
Patient already selected for SEEG implantation as part of their epileptic networks
Exclusion Criteria:
Patient excluded from SEEG (pregnant women, children too young for the procedure, patient unable to undergo the procedure)
Contra-indication for MRI
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Riëm El Tahry, PhD
Phone
003227641080
Email
riem.eltahry@saintluc.uclouvain.be
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Riëm El Tahry, PhD
Organizational Affiliation
Cliniques universitaires Saint-Luc- Université Catholique de Louvain
Official's Role
Principal Investigator
12. IPD Sharing Statement
Plan to Share IPD
Undecided
IPD Sharing Plan Description
Data will be kept on RedCap and made available after reasonable request
Learn more about this trial
Epileptogenic Network Visualisation With Advanced MRI
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