Significance: Time domain diffuse correlation spectroscopy (TD-DCS) can offer increased sensitivity to cerebral hemodynamics and reduced contamination from extracerebral layers by differentiating photons based on their travel time in tissue. We have developed rigorous simulation and evaluation procedures to determine the optimal time gate parameters for monitoring cerebral perfusion considering instrumentation characteristics and realistic measurement noise. Aim: We simulate TD-DCS cerebral perfusion monitoring performance for different instrument response functions (IRFs) in the presence of realistic experimental noise and evaluate metrics of sensitivity to brain blood flow, signal-to-noise ratio (SNR), and ability to reject the influence of extracerebral blood flow across a variety of time gates to determine optimal operating parameters. Approach: Light propagation was modeled on an MRI-derived human head geometry using Monte Carlo simulations for 765- and 1064-nm excitation wavelengths. We use a virtual probe with a source–detector separation of 1 cm placed in the pre-frontal region. Performance metrics described above were evaluated to determine optimal time gate(s) for different IRFs. Validation of simulation noise estimates was done with experiments conducted on an intralipid-based liquid phantom. Results: We find that TD-DCS performance strongly depends on the system IRF. Among Gaussian pulse shapes, ∼300 ps pulse length appears to offer the best performance, at wide gates (500 ps and larger) with start times 400 and 600 ps after the peak of the TPSF at 765 and 1064 nm, respectively, for a 1-s integration time at photon detection rates seen experimentally (600 kcps at 765 nm and 4 Mcps at 1064 nm). Conclusions: Our work shows that optimal time gates satisfy competing requirements for sufficient sensitivity and sufficient SNR. The achievable performance is further impacted by system IRF with ∼300 ps quasi-Gaussian pulse obtained using electro-optic laser shaping providing the best results.

中文翻译：

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用于测量脑血流的时域扩散相关光谱参数的优化

意义：时域扩散相关光谱 (TD-DCS) 可以通过根据光子在组织中的传播时间来区分光子，从而提高对脑血流动力学的敏感性并减少来自脑外层的污染。我们开发了严格的模拟和评估程序，以确定用于监测脑灌注的最佳时间门参数，考虑仪器特性和实际测量噪声。目的：我们在存在真实实验噪声的情况下模拟不同仪器响应函数 (IRF) 的 TD-DCS 脑灌注监测性能，并评估对脑血流、信噪比 (SNR) 和拒绝能力的敏感性指标脑外血流对各种时间门的影响，以确定最佳操作参数。方法：使用 765 和 1064 纳米激发波长的蒙特卡罗模拟，在 MRI 衍生的人体头部几何结构上对光传播进行建模。我们使用放置在前额叶区域的具有 1 cm 源-探测器间距的虚拟探针。评估上述性能指标以确定不同 IRF 的最佳时间门。模拟噪声估计的验证是通过在基于脂类的液体模型上进行的实验来完成的。结果：我们发现 TD-DCS 性能强烈依赖于系统 IRF。在高斯脉冲形状中，~300 ps 脉冲长度似乎提供最佳性能，在宽门（500 ps 和更大）处，开始时间分别在 765 和 1064 nm 的 TPSF 峰值之后 400 和 600 ps，在实验中看到的光子检测率下的 1 秒积分时间（765 nm 处为 600 kcps，1064 nm 处为 4 Mcps）。结论：我们的工作表明，最佳时间门满足对足够灵敏度和足够 SNR 的竞争要求。可实现的性能受到系统 IRF 的进一步影响，使用电光激光整形获得的~300 ps 准高斯脉冲提供了最佳结果。