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Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
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Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts.
Wesley B Baker1, Ashwin B Parthasarathy1, Tiffany S Ko1
1University of Pennsylvania , Department of Physics and Astronomy, 3231 Walnut Street, Philadelphia, Pennsylvania 19104, United States.
Neurophotonics
|August 25, 2015
Summary
This study presents a new pressure-based method to accurately measure cerebral blood flow using diffuse correlation spectroscopy (DCS). The technique effectively separates brain and scalp signals, improving monitoring accuracy for neurological conditions.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Medical Physics
Background:
- Accurate optical monitoring of cerebral blood flow (CBF) is crucial for diagnosing and managing neurological disorders.
- Superficial extracerebral tissue contamination poses a significant challenge in diffuse correlation spectroscopy (DCS) measurements of CBF.
- Existing methods often require anatomical information or complex modeling to differentiate between cerebral and extracerebral signals.
Purpose of the Study:
- To introduce and validate a novel pressure modulation technique to reduce extracerebral signal contamination in DCS-based CBF monitoring.
- To develop a method for determining subject-specific contributions of extracerebral and cerebral tissues to the DCS signal.
- To adapt the pressure modulation approach for improved monitoring of cerebral blood oxygenation and volume using near-infrared spectroscopy (NIRS).
Main Methods:
- A two-layer head model was employed, utilizing long and short source-detector separations in DCS.
- Probe pressure modulation was applied to induce controlled variations in extracerebral blood flow.
- A modified Beer-Lambert law for flow was combined with pressure modulation to linearly relate differential DCS signals to blood flow variations.
Main Results:
- The pressure modulation technique successfully isolated cerebral blood flow during functional tasks (finger-tapping) and induced ischemia in healthy adults.
- The method demonstrated the ability to differentiate between cerebral and extracerebral blood flow contributions without requiring prior anatomical data.
- The algorithm effectively reduced extracerebral contamination in DCS signals.
Conclusions:
- The validated pressure measurement paradigm significantly enhances the accuracy of optical monitoring for cerebral blood flow.
- This non-invasive technique offers a promising approach for real-time assessment of brain hemodynamics in clinical and research settings.
- The adapted algorithm shows potential for improving NIRS-based monitoring of cerebral oxygenation and blood volume.
