Diffuse correlation spectroscopy with a fast Fourier transform-based software autocorrelator

Diffuse correlation spectroscopy (DCS) is an emerging noninvasive technique that probes the deep tissue blood flow, by using the time-averaged intensity autocorrelation function of the fluctuating diffuse reflectance signal. We present a fast Fourier transform (FFT)-based software autocorrelator that utilizes the graphical programming language LabVIEW (National Instruments) to complete data acquisition, recording, and processing tasks. The validation and evaluation experiments were conducted on an in-house flow phantom, human forearm, and photodynamic therapy (PDT) on mouse tumors under the acquisition rate of ~400 kHz. The software autocorrelator in general has certain advantages, such as flexibility in raw photon count data preprocessing and low cost. In addition to that, our FFT-based software autocorrelator offers smoother starting and ending plateaus when compared to a hardware correlator, which could directly benefit the fitting results without too much sacrifice in speed. We show that the blood flow index (BFI) obtained by using a software autocorrelator exhibits better linear behavior in a phantom control experiment when compared to a hardware one. The results indicate that an FFT-based software autocorrelator can be an alternative solution to the conventional hardware ones in DCS systems with considerable benefits.