Improving EPilepsy Surgery Management and progNOsis Using Virtual Epileptic Patient Software (VEP)

NCT ID: NCT03643016

Last Updated: 2022-11-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

356 participants

Study Classification

INTERVENTIONAL

Study Start Date

2019-06-26

Study Completion Date

2025-12-23

Brief Summary

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Every year, thousands of patients worldwide with drug resistant focal epilepsy (DRE) undergo resective brain surgery with the aim of achieving seizure freedom.

Despite technical advances over the last 50 years, the success rate of epilepsy surgery in terms of seizure freedom has not greatly improved, remaining overall at around 50%. Depending on features of individual cases, presurgical evaluation includes a first phase of non-invasive data including video-EEG recordings, magnetoencephalography, structural and functional neuroimaging and neuropsychological evaluation. If these investigations do not allow adequate localization of likely region of seizure organization in the brain (the epileptogenic zone, EZ), then a second invasive phase using intracerebral EEG recording may be necessary (stereoelectroencephalography, SEEG). Interpretation of SEEG remains difficult in many cases, in particular since seizure onset is often characterized by discharges that very rapidly involve several distinct brain regions.

No reliable measuring instrument currently exists to combine the various prognostic factors for a given patient. This leads to great uncertainty on an individual scale in predicting the effects of surgery. The mapping of epileptic networks in patients with DRE is an innovative scientifically-validated and clinically-tested method to significantly improve accuracy of SEEG and presurgical interpretation and guide surgical strategies in patients with DRE. Therefore, the investigators developed the Virtual Epilepsy Patient software. Retrospective study already demonstrated the pertinence of this approach in improving the anatomical mapping of epileptogenic networks. Now, the investigators aim to prospectively demonstrate the role of VEP during presurgical evaluation of DRE patients

Detailed Description

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Conditions

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Epilepsy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

OTHER

Blinding Strategy

NONE

Study Groups

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Group with Virtual Epileptic Patient brain access data

Group Type EXPERIMENTAL

Surgical strategy based on a software

Intervention Type OTHER

Surgical strategy décision based on a software

Group without Virtual Epileptic Patient brain access data

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Surgical strategy based on a software

Surgical strategy décision based on a software

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Patient or pediatric patient suffering from drug-resistant focal epilepsy.
* Standardized presurgical evaluation including medical history, scalp video-EEG, 3T MRI (DTI and rsMRI), FDG-PET, Neuropsychological tests.
* Inpatient in one of the participating centers for recording seizure during long term SEEG-monitoring.

Exclusion Criteria

* Epilepsy surgery performed without the requirement of SEEG or contra-indication to epilepsy surgery.
Minimum Eligible Age

12 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Assistance Publique Hopitaux De Marseille

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Emilie Garrido-Pradalié

Role: STUDY_DIRECTOR

Assitance Publique Hôpitaux de Marseille

Locations

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Assistance Publique Hopitaux de Marseille

Marseille, , France

Site Status RECRUITING

Countries

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France

Central Contacts

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Fabrice Bartolomei, MD/PhD

Role: CONTACT

+33491385829

Other Identifiers

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2018-41

Identifier Type: -

Identifier Source: org_study_id

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