Abstract
Intra and post-operative blood flow monitoring of tissue has been shown to be effective in the improvement of patient outcomes. Diffuse correlation spectroscopy (DCS) has been shown to be effective in measuring blood flow at the bedside, and is a useful technique in measuring cerebral blood flow (CBF) in many clinical settings. However, DCS suffers from reduced sensitivity to blood flow changes at larger tissue depths, making measurements of CBF in adults difficult. This issue can be addressed with acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS), which is a hybrid technique that combines the sensitivity of DCS to blood flow with ultrasound resolution to allow for improved spatial resolution of the optical signal based on knowledge of the area which is insonified by ultrasound. We present a quantitative model for perfusion estimation based on AOM-DCS in the presence of continuous wave ultrasound, supported by theoretical derivations, Monte Carlo simulations, and phantom and human subject experiments. Quantification of the influence of individual mechanisms that contribute to the temporal fluctuations of the optical intensity due to ultrasound is shown to agree with previously derived results. By using this model, the recovery of blood-flow induced scatterer dynamics based on ultrasound-modulated light is shown to deviate by less than one percent from the standard DCS measurement of scatterer dynamics over a range of optical scattering values and scatterer motion conditions. This work provides an important step towards future implementation of AOM-DCS setups with more complex spatio-temporal distributions of ultrasound pressure, which are needed to enhance the DCS spatial resolution.
Highlights
Hemodynamic monitoring of patients in the intra and post-operative periods has been shown to be effective in guiding treatment and reducing negative outcomes such as organ failure [1]
Of the speckle intensity allows the interrogation of dynamic motion in the tissue through the analysis of the intensity temporal autocorrelation function, known in the literature as g2(τ). This function has a characteristic decay that is due to the motion of the scattering particles in the tissue, dominated by red blood cells (RBC), and allows for the quantification of perfusion in terms of a blood flow index (BFi) [6]
diffuse correlation spectroscopy (DCS) can quantify the motion of RBCs in the microvasculature, but as with near-infrared spectroscopy (NIRS) and other optical methods, it loses sensitivity to RBC motion with increased depth [7]
Summary
Hemodynamic monitoring of patients in the intra and post-operative periods has been shown to be effective in guiding treatment and reducing negative outcomes such as organ failure [1]. Past work has shown that the combined use of ultrasound and light is useful in the quantification of cerebral blood flow using a cross-correlation technique of input ultrasound pressure and the modulation of the measured speckle intensity [8]. This technique is effective in quantifying relative flow differences at different depths in tissue, though the use of the cross-correlation allows for only a single correlation parameter to be calculated at each depth, and doesn’t allow for the extraction of the entire autocorrelation function, g2(τ). Though the full benefits of increased spatial localization given by ultrasound tagging of light are not realized in this work, as continuous wave ultrasound is used, this work acts as a basis for the future development of the AOM-DCS setups with more complex ultrasound pressure distributions, like those seen in focused or pulsed ultrasound
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