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Updated: Aug 12, 2025

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Published on: November 19, 2020

Numerical approach to quantify depth-dependent blood flow changes in real-time using the diffusion equation with

Michael Helton¹, Suraj Rajasekhar², Samantha Zerafa³

¹Applied Physics Program, University of Michigan, Ann Arbor, USA.

Biomedical Optics Express

|January 26, 2023

Summary

This summary is machine-generated.

This study introduces a new analysis method for diffuse correlation spectroscopy (DCS) to accurately measure both scalp and brain blood flow in real-time. The validated model effectively separates extracerebral and cerebral blood flow, improving non-invasive brain perfusion quantification.

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Published on: March 14, 2013

Area of Science:

Biomedical Optics
Physiological Measurement
Neuroimaging

Background:

Diffuse correlation spectroscopy (DCS) is a non-invasive optical method for measuring brain perfusion.
Accurate quantification of cerebral blood flow (CBF) is limited by the inability to distinguish it from extracerebral scalp blood flow (SBF).
Current methods for separating SBF and CBF often require multiple channels or time-domain techniques, and a robust real-time analysis is still needed.

Purpose of the Study:

To validate a novel data analysis procedure for DCS capable of quantifying both SBF and CBF.
To assess the accuracy and speed of the analysis procedure for both continuous-wave (CW) and time-domain (TD) DCS measurements.
To provide a robust, real-time method for separating and quantifying extracerebral and cerebral blood flow.

Main Methods:

Development and validation of a data analysis procedure based on the diffusion equation in layered media.
Application of the model to both continuous-wave (CW) and time-domain (TD) DCS data.
Comparison of model results with Monte Carlo simulations using a 3-layered brain model.

Main Results:

The validated model accurately quantifies SBF and CBF coefficients with less than 5% error compared to Monte Carlo simulations.
The analysis procedure demonstrates real-time capabilities, fitting CW data in <10 ms and TD data in <250 ms using a least-squares optimizer.
The model effectively separates and quantifies both extracerebral and cerebral blood flow in both CW and TD DCS measurements.

Conclusions:

The developed diffusion equation-based analysis procedure provides accurate and rapid quantification of both SBF and CBF using DCS.
This method offers a robust solution for separating partial volume effects in both CW and TD-DCS, enhancing the accuracy of non-invasive brain perfusion measurements.
The real-time capability of the analysis procedure facilitates its application in clinical settings for dynamic monitoring of brain hemodynamics.