The Utility of Quantitative EEG in Detecting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage. Issue 3 (March 2022)

• Record Type: Journal Article
• Authors: Baang, Hae Young; Chen, Hsin Yi; Herman, Alison L.; Gilmore, Emily J.; Hirsch, Lawrence J.; Sheth, Kevin N.; Petersen, Nils H.; Zafar, Sahar F.; Rosenthal, Eric S.; Westover, M. Brandon; Kim, Jennifer A.
• Is Part Of: Journal of clinical neurophysiology. Volume 39:Issue 3(2022)
• Publication Date: 2022-03
• Subjects: Quantitative electroencephalography -- EEG -- Delayed cerebral ischemia -- Subarachnoid hemorrhage -- Transcranial Doppler -- Vasospasm; Electroencephalography -- Periodicals; Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electroencephalography; Periodicals; 612.805
• DOI: 10.1097/WNP.0000000000000754
• Languages: English
• ISSNs: 0736-0258

Abstract

Abstract : Summary: In this review, we discuss the utility of quantitative EEG parameters for the detection of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage in the context of the complex pathophysiology of DCI and the limitations of current diagnostic methods. Because of the multifactorial pathophysiology of DCI, methodologies solely assessing blood vessel narrowing (vasospasm) are insufficient to detect all DCI. Quantitative EEG has facilitated the exploration of EEG as a diagnostic modality of DCI. Multiple quantitative EEG parameters such as alpha power, relative alpha variability, and alpha/delta ratio show reliable detection of DCI in multiple studies. Recent studies on epileptiform abnormalities suggest that their potential for the detection of DCI. Quantitative EEG is a promising, continuous, noninvasive, monitoring modality of DCI implementable in daily practice. Future work should validate these parameters in larger populations, facilitated by the development of automated detection algorithms and multimodal data integration.