Diffuse Correlation Spectroscopy at Short Source-Detector Separations: Simulations, Experiments and Theoretical Modeling

Abstract

Diffuse correlation spectroscopy (DCS) has widely been used as a non-invasive optical technique to measure tissue perfusion in vivo. DCS measurements are quantified to yield information about moving scatterers using photon diffusion theory and are therefore obtained at long source-detector separations (SDS). However, short SDS DCS could be used for measuring perfusion in small animal models or endoscopically in clinical studies. Here, we investigate the errors in analytically retrieved flow coefficients from simulated and experimental data acquired at short SDS. Monte Carlo (MC) simulations of photon correlation transport was programmed to simulate DCS measurements and used to (a) examine the accuracy and validity of theoretical analyses, and (b) model experimental measurements made on phantoms at short SDS. Experiments consisted of measurements from a series of optical phantoms containing an embedded flow channel. Both the fluid flow rate and depth of the flow channel from the liquid surface were varied. Inputs to MC simulations required to model experiments were obtained from corrected theoretical analyses. Results show that the widely used theoretical DCS model is robust for quantifying relative changes in flow. We also show that retrieved flow coefficients at short SDS can be scaled to retrieve absolute values via MC simulations.

Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling

“…Many published DCS works utilize the blood flow index (BF i ) calculated from MC forward simulations as an in-silico verification or investigation prior to performing phantom or in-vivo studies. [32][33][34][35] In contrast, taking advantage of advances in computational power and in particular GPU acceleration, we use MC simulations directly as the forward component of our inverse model for estimating BF i in both superficial (scalp) and deep (brain) tissue layers.…”

Beyond diffuse correlations: deciphering random flow in time-of-flight resolved light dynamics

“…( 17), were simulated. The range of values for g dyn encompasses particles of interest such as Intralipid (g dyn ≈ 0.6) [32,45,46], 1 µm diameter polystyrene microspheres (g dyn ≈ 0.9) [47][48][49][50][51], and red blood cells (g dyn ≈ 0.98) [27,52,53]. Unless mentioned, other parameters are kept constant as shown in Table 2.…”

Non-Invasive Blood Flow Speed Measurement Using Optics

“…Modeling of light propagation in this regime led to the development of the oximeter back in 1970s [ 10 ] and many researchers have utilized the diffused light to construct images through highly diffusive biological media, such as reconstructed breast cancer images [ 11 ]. The standard configuration for diffused light correlation spectroscopy includes a point source and a point detector, and the measured correlation function depends on the relative position between the source and the detector [ 12 , 13 , 14 ]. The method of diffused light correlation spectroscopy has been used in blood perfusion measurement [ 15 ], including brain circulations [ 16 , 17 , 18 ].…”