A Quantitative EEG Method for Detecting Post Clamp Changes During Carotid Endarterectomy

Abstract

By applying automatic data-driven feature extraction and classification to short EEG records, it is possible to construct subject-independent computational models that can detect subtle post clamp changes possibly caused by small perturbations in cerebral blood flow. These subtle changes are missed by visual inspection of the EEG and by other quantitative EEG techniques such as r-sBSI and r-tBSI. Within our subject group, the intricate post-clamp EEG signatures were predominantly anterior, bilateral, and had a strong delta rhythm presence.

Consensus Statement on Continuous EEG in Critically Ill Adults and Children, Part I

“…EEG and quantitative EEG techniques have been used to identify ischemia during neurosurgical and interventional neuroradiology vascular procedures (Plestis, Loubser et al 1997, Laman, van der Reijden et al 2001, Pinkerton 2002, van Putten, Peters et al 2004, Botes, Le Roux et al 2007, Ballotta, Saladini et al 2010, Mishra, Banday et al 2011, Skordilis, Rich et al 2011). …”

Continuous Electroencephalography Monitoring in Adults in the Intensive Care Unit

“…EEG is very sensitive in detecting changes in cerebral blood flow (CBF), generally showing regional attenuation of faster frequencies and increases in slow activity; based on these observations, many authors have suggested cEEG for ischemia identification during surgical or neuroradiological procedures, during intracranial hypertension and for the diagnosis of delayed cerebral ischemia (DCI) after subarachnoid hemorrhage [22][23][24]. Although many studies have tried to show a specific ischemic pattern in various conditions, current recommendations suggest cEEG to detect ischemia only for the diagnosis of DCI after subarachnoid hemorrhage [5].…”

Computer assisted interpretation of the human EEG

“…Previous quantitative analysis studies typically focussed on specialized features to point out a disease or abnormality in the brain Chabot and Serfontein, 1996;Hughes and John, 1999;Bares et al, 2012;Prichep et al, 1994;Calzada-Reyes et al, 2011;Begić et al, 2011;Bjork et al, 2011;Jiang et al, 2011;Mishra et al, 2011). The di erence between these and our study, is that we a empt to quantify the same background properties reported by routine visual analysis, and in addition, compare the quantitative output to that of the human reviewer.…”