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

Anesthesia Clinical Trial

Official title:

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

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT03629743
• Other study ID #: 45987
• Status: Active, not recruiting
• Start date: November 11, 2019
• Est. completion date: August 31, 2024

Study information

• Verified date: August 2023
• Source: Stanford University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Improve understanding of the correlation between surface EEG and implanted EEG recordings

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 20
• Est. completion date: August 31, 2024
• Est. primary completion date: August 31, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Anesthesia

Intervention

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)
• ECOG
ECOG will be collected with Nihon Kohden acquisition System and accompanying software and depth electrodes.

Locations

Country	Name	City	State
United States	Stanford University	Stanford	California

Sponsors (1)

Lead Sponsor	Collaborator
Stanford University

Country where clinical trial is conducted

United States, 

References & Publications (7)

Asano E, Brown EC, Juhasz C. How to establish causality in epilepsy surgery. Brain Dev. 2013 Sep;35(8):706-20. doi: 10.1016/j.braindev.2013.04.004. Epub 2013 May 15. — View Citation

Fahy BG, Chau DF. The Technology of Processed Electroencephalogram Monitoring Devices for Assessment of Depth of Anesthesia. Anesth Analg. 2018 Jan;126(1):111-117. doi: 10.1213/ANE.0000000000002331. — View Citation

Hajat Z, Ahmad N, Andrzejowski J. The role and limitations of EEG-based depth of anaesthesia monitoring in theatres and intensive care. Anaesthesia. 2017 Jan;72 Suppl 1:38-47. doi: 10.1111/anae.13739. — View Citation

Hashiguchi K, Morioka T, Yoshida F, Miyagi Y, Nagata S, Sakata A, Sasaki T. Correlation between scalp-recorded electroencephalographic and electrocorticographic activities during ictal period. Seizure. 2007 Apr;16(3):238-47. doi: 10.1016/j.seizure.2006.12.010. Epub 2007 Jan 19. — View Citation

Purdon PL, Sampson A, Pavone KJ, Brown EN. Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures. Anesthesiology. 2015 Oct;123(4):937-60. doi: 10.1097/ALN.0000000000000841. — View Citation

Ramantani G, Maillard L, Koessler L. Correlation of invasive EEG and scalp EEG. Seizure. 2016 Oct;41:196-200. doi: 10.1016/j.seizure.2016.05.018. Epub 2016 Jun 10. — View Citation

Smith EH, Liou JY, Davis TS, Merricks EM, Kellis SS, Weiss SA, Greger B, House PA, McKhann GM 2nd, Goodman RR, Emerson RG, Bateman LM, Trevelyan AJ, Schevon CA. The ictal wavefront is the spatiotemporal source of discharges during spontaneous human seizures. Nat Commun. 2016 Mar 29;7:11098. doi: 10.1038/ncomms11098. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Electrocardiogram (EEG) change before, during, and after anesthesia.	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.	Up to 48 hours. Specific time points are dependent on patient clinical events.
Secondary	Electrocardiogram (EEG) change during any changes in consciousness.	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.	Up to 48 hours. Specific time points are dependent on patient clinical events.
Secondary	Electrocardiogram (EEG) change during any seizures.	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.	Up to 48 hours. Specific time points are dependent on patient clinical events.