TY - JOUR
T1 - Exploring the feasibility of EEG for pre-hospital detection of medium and large vessel occlusion strokes
T2 - a proof-of-concept study
AU - Peterson, William
AU - Ramakrishnan, Nithya
AU - Tinklepaugh, David
AU - Hamburger, Adrian
AU - Kowell, Arthur
AU - Browder, Krag
AU - Sanossian, Nerses
AU - Nguyen, Peggy
AU - Fink, Ezekiel
N1 - Publisher Copyright:
Copyright © 2025 Peterson, Ramakrishnan, Tinklepaugh, Hamburger, Kowell, Browder, Sanossian, Nguyen and Fink.
PY - 2025
Y1 - 2025
N2 - Introduction: Early and accurate identification of stroke subtypes, particularly medium (MeVO) and large vessel occlusions (LVO), is critical for timely intervention and improving patient outcomes. Current pre-hospital diagnostic methods are limited in sensitivity, delaying treatment for ischemic stroke candidates eligible for endovascular thrombectomy (EVT). Methods: This proof-of-concept study explores the feasibility of using electroencephalography (EEG) as a diagnostic tool for pre-hospital detection of MeVO and LVO strokes. Conducted in the emergency department setting, this study assessed the efficacy of quantitative EEG biomarkers in differentiating MeVO/LVO-positive cases (n = 4) from MeVO/LVO-negative cases (n = 23). EEG data was acquired using both dry and wet electrode systems, with wet electrodes yielding lower attrition rates arising from superior signal quality. Results: Findings from MeVO- and LVO-positive subjects revealed hemispheric asymmetry in delta and alpha frequency bands, particularly in frontal and temporal regions, as well as a global attenuation of power irrespective of the region of stroke. Discussion: This study supports the potential of EEG for real-time, non-invasive stroke detection in pre-hospital and clinical environments, demonstrating the need for wet EEG systems for reliable signal acquisition. Future work aims to validate the use of EEG in the pre-hospital setting in an effort to facilitate rapid triage and reduce time to treatment for stroke patients.
AB - Introduction: Early and accurate identification of stroke subtypes, particularly medium (MeVO) and large vessel occlusions (LVO), is critical for timely intervention and improving patient outcomes. Current pre-hospital diagnostic methods are limited in sensitivity, delaying treatment for ischemic stroke candidates eligible for endovascular thrombectomy (EVT). Methods: This proof-of-concept study explores the feasibility of using electroencephalography (EEG) as a diagnostic tool for pre-hospital detection of MeVO and LVO strokes. Conducted in the emergency department setting, this study assessed the efficacy of quantitative EEG biomarkers in differentiating MeVO/LVO-positive cases (n = 4) from MeVO/LVO-negative cases (n = 23). EEG data was acquired using both dry and wet electrode systems, with wet electrodes yielding lower attrition rates arising from superior signal quality. Results: Findings from MeVO- and LVO-positive subjects revealed hemispheric asymmetry in delta and alpha frequency bands, particularly in frontal and temporal regions, as well as a global attenuation of power irrespective of the region of stroke. Discussion: This study supports the potential of EEG for real-time, non-invasive stroke detection in pre-hospital and clinical environments, demonstrating the need for wet EEG systems for reliable signal acquisition. Future work aims to validate the use of EEG in the pre-hospital setting in an effort to facilitate rapid triage and reduce time to treatment for stroke patients.
KW - EEG
KW - emergency care
KW - large vessel occlusion
KW - prehospital / EMS
KW - stroke
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U2 - 10.3389/fneur.2025.1509443
DO - 10.3389/fneur.2025.1509443
M3 - Article
AN - SCOPUS:105002395828
SN - 1664-2295
VL - 16
JO - Frontiers in Neurology
JF - Frontiers in Neurology
M1 - 1509443
ER -