From Event: SPIE BiOS, 2019
Diffuse correlation spectroscopy (DCS) is an emerging technology that allows for the quantitative estimation of blood flow in tissue. By monitoring the autocorrelation of the time course of light speckle intensity, information about the motion of scattering particles, mostly red blood cells in the microvasculature of biological tissues, can be determined. The speckle fluctuations are due to motion of scatters along the entire path length of the photon from the source to the detector, which makes the determination of the location of the motion a difficult task. Multi-distance and tomographic methods have been employed to measure decorrelation times at different source detector separations, which helps to separate superficial blood flow from blood flow deeper in the tissue. DCS in the time-domain (TD-DCS) is being evaluated as a method to increase depth sensitivity by considering only the late arriving photons. Depth resolved quantification of blood flow is especially important when blood flow measurements of the brain are desired, as the superficial blood flow of the scalp is a known contaminant to the cortical signal. Recent demonstrations by other groups have shown the utility of ultrasound tagging of light to be an effective method to discriminate flow at different depths.1 Here we utilize ultrasound pulses to modulate the motion of particles at specific depths, which is dependent upon the time-of-flight of the ultrasound pulse. By analyzing the autocorrelation of the speckle intensity at different delay periods after the pulse, quantitative, depth specific information about the flow can be determined.
References:
1. Tsalach, A. et al. Depth selective acousto-optic flow measurement. Biomed. Opt. Express 6, 4871–86 (2015).
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Mitchell B. Robinson, Stefan A. Carp, David A. Boas, and Maria Angela Franceschini, "Quantitative depth selective measurements of flow using acousto-optic diffuse correlation spectroscopy (Conference Presentation)," Proc. SPIE 10878, Photons Plus Ultrasound: Imaging and Sensing 2019, 108782V (Presented at SPIE BiOS: February 07, 2019; Published: 4 March 2019); https://doi.org/10.1117/12.2510349.6008552143001.