Establishing the diffuse correlation spectroscopy signal relationship with blood flow.

Area of Science:

• Biophotonics
• Biomedical Optics
• Physiological Measurement

Background:

• Diffuse correlation spectroscopy (DCS) measures tissue blood flow by analyzing light scattering.
• Blood flow is inferred from red blood cell (RBC) movement, specifically their mean square displacement (MSD).
• Theoretical models predict exponential decay based on convective flow, but experimental data often show diffusive behavior.

Purpose of the Study:

• To quantitatively assess the contributions of convective and diffusive red blood cell (RBC) movements in Diffuse Correlation Spectroscopy (DCS).
• To develop a theoretical model explaining the dominance of diffusive motion in DCS measurements.
• To establish a quantitative link between DCS parameters and absolute tissue blood flow.

Main Methods:

• Monte Carlo simulations of light scattering in tissue with varying vessel densities.
• Inclusion of laminar flow profiles and shear-induced diffusion effects for RBCs.
• Analysis of the temporal autocorrelation function of scattered light.

Main Results:

• Simulations confirmed that diffusive RBC motion is the primary driver of correlation decay in typical DCS parameters.
• A quantitative relationship was established between the RBC diffusion coefficient and absolute tissue blood flow.
• The DCS blood flow index (BF) was found to be linearly proportional to blood flow, modulated by hemoglobin concentration and vessel diameter.

Conclusions:

• This study provides the first theoretical support for the empirical use of the DCS blood flow index (BF) in quantifying tissue perfusion.
• The findings reconcile the discrepancy between theoretical predictions of convective flow and experimental observations of diffusive behavior.
• The developed model enhances the accuracy and reliability of DCS for non-invasive blood flow assessment.