Diffuse correlation spectroscopy (DCS) is an emerging noninvasive optical technique used to measure an index of blood flow index (BFI). However, accurate quantification of BFI relies on a priori knowledge of the optical properties of tissue, namely, the absorption and reduced scattering coefficients. Traditionally, optical properties are measured with a separate near-infrared spectroscopy (NIRS) system, which can add appreciable cost to the measurements. Alternatively, optical properties are assumed from literature, which can induce significant errors in the estimation of BFI. Recently, a handful of “stand-alone” DCS methods have been proposed that employ multi-distance and/or multi-wavelength measurements to simultaneously estimate both optical properties and BFI, thereby reducing the need for reliance on costly NIRS systems. In this work, we employ in silico simulations to investigate the performance of these stand-alone DCS methods across a wide range of physiologically relevant tissue optical properties and BFI. We find that all methods are highly sensitive to even modest noise at large (> 2 cm) source-detector separations, making their clinical utility for deep tissue monitoring suspect. However, the multi-wavelength, multi-distance stand-alone method performs well at SDS 1.5-2.5cm when the reduced scattering coefficient < 7 cm-1, suggesting a possible role for the modality in tissue types with low scattering, e.g., muscle perfusion or assessment of cerebral blood flow in preterm infants.
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