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Updated: Jun 9, 2025
Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
Published on: December 10, 2014
Wavelet and time-based cerebral autoregulation analysis using diffuse correlation spectroscopy on adults undergoing
Irfaan A Dar1, Imad R Khan2, Thomas W Johnson2
1Department of Biomedical Engineering, University of Rochester, Rochester, New York, United States of America.
Introduction:
Adult patients who have suffered acute cardiac or pulmonary failure are increasingly being treated using extracorporeal membrane oxygenation (ECMO), a cardiopulmonary bypass technique. While ECMO has improved the long-term outcomes of these patients, neurological injuries can occur from underlying illness or ECMO itself. Cerebral autoregulation (CA) allows the brain to maintain steady perfusion during changes in systemic blood pressure. Dysfunctional CA is a marker of acute brain injury and can worsen neurologic damage. Monitoring CA using invasive modalities can be risky in ECMO patients due to the necessity of anticoagulation therapy. Diffuse correlation spectroscopy (DCS) measures cerebral blood flow continuously, noninvasively, at the bedside, and can monitor CA. In this study, we compare DCS-based markers of CA in veno-arterial ECMO patients with and without acute brain injury.
Methods:
Adults undergoing ECMO were prospectively enrolled at a single tertiary hospital and underwent DCS and arterial blood pressure monitoring during ECMO. Neurologic injuries were identified using brain computerized tomography (CT) scans obtained in all patients. CA was calculated over a twenty-minute window via wavelet coherence analysis (WCA) over 0.05 Hz to 0.1 Hz and a Pearson correlation (DCSx) between cerebral blood flow measured by DCS and mean arterial pressure.
Results:
Eleven ECMO patients who received CT neuroimaging were recruited. 5 (45%) patients were found to have neurologic injury. CA indices WCOH, the area under the curve of the WCA, were significantly higher for patients with neurological injuries compared to those without neurological injuries (right hemisphere p = 0.041, left hemisphere p = 0.041). %DCSx, percentage of time DCSx was above a threshold 0.4, were not significantly higher (right hemisphere p = 0.268, left hemisphere p = 0.073).
Conclusion:
DCS can be used to detect differences in CA for ECMO patients with neurological injuries compared to uninjured patients using WCA.
