EEG Patterns Predicting Cerebral Herniation with Neuroimaging Correlation in High-Risk Adult Patients
Abstract number :
2.168
Submission category :
3. Neurophysiology / 3B. ICU EEG
Year :
2025
Submission ID :
5
Source :
www.aesnet.org
Presentation date :
12/7/2025 12:00:00 AM
Published date :
Authors :
Presenting Author: Shane Sampson, MD – Wayne State University - Detroit Medical Center
Arichena Manmatharayan, MD – Wayne State University/Detroit Medical Center
Jonathan Izygon, MD – Wayne State University/Detroit Medical Center
Rumyah Rafique, Student – Wayne State University
Najeeb Baig, Student – Wayne State University
Ahmad Abdelhak, Student – Wayne State University
Mohammad Emari, DO – Wayne State University/Detroit Medical Center
Zahir Arrayeh, MD – Wayne State University/Detroit Medical Center
Phillip Kucab, MD – Wayne State University/Detroit Medical Center
Omar Danoun, MD – Henry Ford Health
Fazeel Siddiqui, MD, FAHA – University of Michigan Health-West
Mona Elsayed, MD – Detroit Medical Center - Wayne State University
Rationale: Cerebral herniation is a life-threatening neurologic emergency that can arise from various etiologies, requiring rapid diagnosis and intervention. Continuous electroencephalogram (cEEG) monitoring may offer an early detection method for the onset and progression of cerebral herniation, potentially improving patient outcomes.
Methods: A total of six cases admitted to our Neurointensive Care Unit were retrospectively analyzed. The patients underwent cEEG monitoring and revealed cerebral herniation patterns confirmed via neuroimaging. Epileptologists reviewed the cEEG data for patterns indicative of early cerebral herniation, and these findings were compared with neuroimaging results.
Results: Six cases (three females, three males; ages 19-70) exhibited different types of cerebral herniation due to various causes including: i) anterior cerebral artery ruptured aneurysm with subfalcine herniation, ii) HIV and toxoplasmosis with subfalcine herniation, iii) brain mass with subfalcine and uncal herniation, iv) infectious encephalitis with transtentorial herniation, v) hemorrhagic transformation of the left-sided cerebral infarct with left uncal herniation, vi) and large hyperacute on acute left-sided subdural hematoma, subarachnoid hemorrhage with supratentorial herniation. The cEEG showed higher amplitude quasi-rhythmic delta (QRDA) activity on the side contralateral to the herniating process and lower amplitude polymorphic delta activity (PMDA) that was ipsilateral to the herniating process. These waves at the time did not correspond to any focal neurologic changes, but in all six cases ultimately their cEEG progressed from QRDA and PMDA to attenuation and suppression. The cEEG patterns showed a strong correlation with neuroimaging findings.
Conclusions: cEEG can effectively predict cerebral herniation, showing a strong correlation with neuroimaging. Recognizing these specific EEG patterns may enable earlier intervention for high-risk patients, potentially improving outcomes. Larger studies are warranted to further explore the utility of cEEG in the management of cerebral herniation.
Funding: No funding was received.
Neurophysiology