Time Domain Diffuse Correlation Spectroscopy for Detecting Human Brain Function: Optimize System on Real Experimental Conditions by Simulation Method
Time Domain Diffuse Correlation Spectroscopy for Detecting Human Brain Function: Optimize System on Real Experimental Conditions by Simulation Method
复制标题
检测人脑功能的时域扩散相关光谱：通过仿真方法在真实实验条件下优化系统
DOI：
10.1109/jphot.2021.3089635
复制
发表时间：
2021-08-01
影响因子：
2.4
通讯作者：
Li, Jun
中科院分区：
文献类型：
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作者：
Qiu, Lina;Zhang, Tingzhen;Li, Jun
为了实现高灵敏度时域扩散相关光谱（TD-DCS）测量脑血流功能变化，本研究在真实的实验条件下（包括考虑有限相干长度L-C和非理想仪器响应函数IRF的影响），采用仿真方法对TD-DCS系统进行优化。在真实的实验条件下，入射功率为75 mW，源-探测器距离为1.0 cm，IRF的半峰全宽为160 ps，我们采用模拟实验研究了两种脑功能状态（即，基线和激活）和TD-DCS系统参数（包括L-C、IRF、源-探测器距离、门打开时间和门宽度）。我们的模拟结果表明，更长的L-C和更长的积分时间都有利于更灵敏的检测。在L-C和积分时间一定的情况下，最佳的门开启时间为800 ps（相对于IRF峰值时间），门宽度大于等于800 ps。这项研究可能有助于指导人类大脑功能的灵敏测量（例如，脑血流的变化）。
In order to achieve high-sensitivity time-domain diffuse correlation spectroscopy (TD-DCS) measurement of functional changes in cerebral blood flow, this study applied simulation methods to optimize the TD-DCS system under real experimental conditions (including the consideration of the effects of finite coherence length L-C and non-ideal instrument response function IRF). Under a real experimental condition where the incident power is 75 mW, the source-detector distance is 1.0 cm, and the full width at half maxima of the IRF is 160 ps, we used simulation experiments to investigate the relationship between the contrast of the intensity autocorrelation function (g(2)) in two brain functional states (i.e., baseline and activation) and TD-DCS system parameters (including L-C, IRF, source-detector distance, gate opening time and gate width). Our simulation results show that both longer L-C and longer integration time are beneficial to a more sensitive detection. With a fixed L-C and integration time, the optimal parameters of gate opening time is 800 ps (relative to the peak time of IRF), and gate width is equal to or larger than 800 ps. This study may be useful for guiding the sensitive measurement of human brain functions (e.g., changes in cerebral blood flow) using the TD-DCS technology.