Multi-channel DCS System Towards Dynamic Topography Of Blood Flow Index

Blood flow is one of the clinical indicators to characterize tissue health and function.Thus,the image of blood flow in the focused region is of great significance for diagnosing and monitoring tissue diseases that are associated with abnormal blood flow.In recent years,Diffusion Correlation Spectroscopy(DCS)has attracted an increasing attention in blood flow detection owing to its advantages of non-invasiveness,high sensitivity to blood flow changes,high penetration,real-time potential and suitability for bedside monitoring.A minimum configured DCS system consists of a coherent NIR laser tailed with a single-or multi-mode output fiber,a single photon avalanche photodiode(SPAD)detector coupled with a single-or few-mode fiber,a single-channel correlator and an BFI extraction algorithm.Normally,the BFI is reconstructed by fitting the measured correlation function curve to the correlation diffusion equation(c-DE)solution under an optically homogenous tissue model of semi-infinite planar geometry,DCS has made great progress in methods and technology,but increasing the acquisition speed to achieve real-time fast imaging is still a problem to be solved.Aiming at the problems in fast DCS measurement,this paper proposed a multi-channel DCS system for BFI dynamic topology imaging in deep tissue and a fast blood flow index extraction method.The system used a hardware correlator designed according to the diffused photon correlation noise model to obtain a complete full-time intensity autocorrelation curve at high speed by limited hardware resource.At the same time,we proposed a Curve Fitting Guided by Prior Value for blood flow index extraction based on Curve-Fitting using Typical Value.The simple algorithm is more suitable for realtime imaging system.After combining the high-concurrency of multi-channel multi-τhardware correlator,near-infrared sensitivity ofsingle photon avalanche photodiode(SPAD)and the quick extraction algorithm,the system achieved high-speed dynamic imaging of deep tissue blood flow.In order to ensure the reliability and the imaging capabilities of system,we conducted a series of performance evaluation experiments,phantom verification experiments and in vivo experiments.The performance evaluation experiment evaluated the stability and dynamic range of the system.The results show that the coefficient of variation of the system light source is almost less than 1%,which will not affect the accuracy of photon counting.The system’s dynamic range is as high as 74 dB,ensuring the ability to image different tissues.The results of the phantom verification experiments show that the system can resolve the speed difference as low as 0.32ml/min in depth up to 11 mm,and it can dynamically detect the change of the velocity.In the in vivo experiment,the system captures changes in blood flow during cuff compression and relaxation,demonstrating the ability to image the human body.