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Correlate of Surface Electroencephalogram (EEG) With Implanted EEG Recordings (ECOG)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT03629743
Recruitment Status : Recruiting
First Posted : August 14, 2018
Last Update Posted : November 19, 2019
Sponsor:
Information provided by (Responsible Party):
David R. Drover, Stanford University

Brief Summary:
Improve understanding of the correlation between surface EEG and implanted EEG recordings

Condition or disease Intervention/treatment
Anesthesia Device: EEG Device: ECOG

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Study Type : Observational
Estimated Enrollment : 20 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Correlate of Surface Electroencephalogram (EEG) With Implanted EEG Recordings (ECOG)
Actual Study Start Date : November 11, 2019
Estimated Primary Completion Date : December 1, 2020
Estimated Study Completion Date : December 1, 2020

Group/Cohort Intervention/treatment
ECOG and EEG Sensor
Study subjects are neurosurgical patients with medically refractory epilepsy who will have implanted with intracranial ECoG electrodes. The electrodes will be used during a period of inpatient monitoring to identify resectable seizure foci.
Device: EEG
EEG will be collected with Brain Product's VAMP-16 channel EEG Monitor using the accompanying software. (Website with further specifications and product details: https://www.brainproducts.com/productdetails.php?id=15)

Device: ECOG
ECOG will be collected with Nihon Kohden acquisition System and accompanying software and depth electrodes.




Primary Outcome Measures :
  1. Electrocardiogram (EEG) change before, during, and after anesthesia. [ Time Frame: Up to 48 hours. Specific time points are dependent on patient clinical events. ]
    Patient subjective level of consciousness during and after anesthesia administration will be assessed using response to verbal stimuli, response via button press, reported subjective level of consciousness, and/or response to memory tests (i.e. demonstration of explicit memory recall). Around loss and recovery of consciousness time points (e.g. induction or emergence from anesthesia or when patient falls asleep or wakes up during 24 hour postoperative time points) level of consciousness will be assessed in brief intervals (seconds) until patient no longer responds or begins to respond. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared.


Secondary Outcome Measures :
  1. Electrocardiogram (EEG) change during any changes in conciousness. [ Time Frame: Up to 48 hours. Specific time points are dependent on patient clinical events. ]
    Scalp and cortical electrical activity collected using EEG and ECOG arrays respectively will be analyzed using standard frequency-derived measures (e.g. spectrograms, Fourier analysis), nonlinear dynamical analyses (e.g. correlation dimension, entropy), network dynamics (e.g. connectivity matrices, path length), and/or machine learning. These measures will include all of the data collected from the start of the implant procedure until 24 hours after the implant procedure has ended. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. Reports will included characterization of electrophysiological activity before, during, and after variations in behavioral and subjectively reported consciousness.

  2. Electrocardiogram (EEG) change during any seizures. [ Time Frame: Up to 48 hours. Specific time points are dependent on patient clinical events. ]
    Scalp and cortical electrical activity collected using EEG and ECOG arrays respectively will be analyzed using standard frequency-derived measures (e.g. spectrograms, Fourier analysis), nonlinear dynamical analyses (e.g. correlation dimension, entropy), network dynamics (e.g. connectivity matrices, path length), and/or machine learning. Data collected before, after, and during seizure activity if a patient loses consciousness or has diminished consciousness may also be compared. Reports will include characterization and comparison of EEG and ECOG electrophysiological activity and analyses during consciousness transitions and significant time points.



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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Stanford Health Care and Clinics
Criteria

Inclusion Criteria:

  • Male or Female subjects 18 years of age or older.
  • English or Spanish Speaking
  • Subjects who have been previously diagnosed with intractable epilepsy and require implantation of invasive electrophysiological recordings as part of their routine clinical presurgical workup.

Exclusion Criteria:

  • Patients with skin abnormalities at the planned application sites that would interfere with sensor or electrode applications.
  • Patients with pre-existing conditions and/or co-morbidities that would prohibit them from participating in the study due to unacceptable risks to their health and well-being, as determined by the Principal Investigator (PI).
  • Patients who the PI deems ineligible at the PI's discretion
  • Pregnant patients

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03629743


Locations
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United States, California
Stanford University Recruiting
Stanford, California, United States, 94305
Contact: Angelica Pritchard, BS    650-723-9229    apritcha@stanford.edu   
Principal Investigator: David Drover, MD         
Sponsors and Collaborators
Stanford University
Investigators
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Principal Investigator: David Drover, MD Stanford University
Publications:

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Responsible Party: David R. Drover, Principle Investigator, Stanford University
ClinicalTrials.gov Identifier: NCT03629743    
Other Study ID Numbers: 45987
First Posted: August 14, 2018    Key Record Dates
Last Update Posted: November 19, 2019
Last Verified: November 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: Yes
Product Manufactured in and Exported from the U.S.: Yes