Using a simulation approach to optimize time-domain diffuse correlation spectroscopy measurement on human head

Abstract

Time-domain diffuse correlation spectroscopy (TD-DCS) has been recently proposed to improve detection of deep blood flow dynamics in a biological tissue, such as human brain. To obtain a high sensitive measurement, several experimental parameters such as the source-detector (SD) distance, gate opening time, and width need to be considered and optimized. We use a simulation approach to optimize these parameters based on Monte Carlo computations using a realistic human head model. Two cortical regions are investigated including the frontal and temporal lobes. SD distance ranging from 0 to 45 mm, gate opening time from 400 to 1000 ps, and gate width from 50 to 3000 ps are considered. The goal is to find out the optimal combinations of these parameters by which the higher contrast measurement on the cortical dynamics can be achieved. The simulations show that with an acceptable input power of light, the combinations of SD distance ranging from 0 to 15 mm, gate opening time at 700 to 800 ps, and gate width of 800 ps are optimal for achieving higher contrast measurement on the cortical dynamics. The simulation approach and results are helpful for the optimization of TD-DCS experimental design focused on brain functional detection.

Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism

“…31,32 Although TR detection has also been proposed for DCS, 33 neuromonitoring applications of this approach are challenging due to the poorer signal-to-noise ratio (SNR) of current technology. 34 However, the substantially higher blood flow in the brain compared with the scalp gives DCS an inherent advantage in terms of depth sensitivity compared with CW NIRS. 15 Studies involving tissue-mimicking phantoms, animal models, and human applications have shown that scalp and CBF can be separated using multilayered analytical models to analyze DCS data collected at different source-detector separations.…”

Time Domain Diffuse Correlation Spectroscopy for Detecting Human Brain Function: Optimize System on Real Experimental Conditions by Simulation Method

“…In other words, TD-DCS can provide higher sensitivity detection for deep dynamics. In recent years, TD-DCS technology has developed rapidly, including the proposal of various theoretical models, the verification of simulation and phantom experiments, as well as in vivo measurement of the human arm and head [11][12][13][14][15][16][17].…”

“…In order to obtain highly sensitive TD-DCS measurement of deep dynamics, in addition to the above two factors, some other experimental factors (e.g., gate opening time and gate width, SD distance) should be considered in the experimental design and data analysis. Very recently, we have optimized some experimental factors on a realistic head model based on the simulation method, including SD distance and gate opening time and gate width [13]. The results showed that under acceptable input power of light, a high-contrast measurement of deep dynamic changes (e.g., cerebral blood flow caused by functional activation) can be achieved by selecting the optimal combination of SD distance(s) and time gate(s).…”

“…Therefore, to obtain a more accurate and sensitive TD-DCS measurement of cerebral blood flow under limited input laser power, we need to consider a more realistic TD-DCS measurement of human cerebral blood flow. In this study, we simulated the real measurement of TD-DCS on a head model based on the previous study [13], and further considered the effect of and IRF. In this simulation experiment, we studied the effect of IRF, , gate opening time and gate width on the TD-DCS intensity autocorrelation function ( 2 ).…”

“…In this simulation experiment, we studied the effect of IRF, , gate opening time and gate width on the TD-DCS intensity autocorrelation function ( 2 ). For this, we used an optimal SD distance (i.e., SD = 1.0 cm) obtained from our previous study [13] and utilized a mimic IRF and with several possible values for a real TD-DCS system. A Monte Carlo simulation was first performed on the frontal lobe of a realistic human head model to obtain the TPSF of the detected photons, and then the time-resolved (or path length resolved) intensity autocorrelation functions ( 2 ) for the two brain functional conditions (i.e., baseline and activation) were simulated.…”