Development of a Monte Carlo-wave model to simulate time domain diffuse correlation spectroscopy measurements from first principles.
Development of a Monte Carlo-wave model to simulate time domain diffuse correlation spectroscopy measurements from first principles.
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DOI：
10.1117/1.jbo.27.8.083009
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发表时间：
2022-03
影响因子：
3.5
通讯作者：
Boas DA
中科院分区：
文献类型：
--
作者：
Cheng X;Chen H;Sie EJ;Marsili F;Boas DA
漫相关光谱是一种非侵入性、连续测量血流的光学技术。分布式控制系统的时间域(TD)变体，即TD-DC，已经显示出通过利用脉冲激光光源和门控策略来选择散射组织内不同路径长度的光子(使用单个源-探测器分离)来提高脑深度敏感度和区分浅层和深层血流的潜力。目前还没有一种可以与传统连续波分散控制系统(CW-DCS)相比较的定量工具来预测TD-DCS的性能，但这对于指导这些分散控制系统的继续开发和应用至关重要。我们的目标是建立一个模型，从基本原理出发模拟TD-DCS测量，该模型能够分析测量噪声的影响，可用于量化任何特定TD-DCS系统和测量几何结构的性能。我们将描述生物组织中光子散射的蒙特卡罗模拟与计算组织动力学引起的散斑强度起伏的波动模型相结合，从第一性原理模拟TD-DCS测量。我们的模型能够模拟在探测器处接收的光子计数作为时间的函数，用于CW-DCS和TD-DCS测量。该模型考虑了激光相干性、仪器响应函数、探测器门延迟、门宽度、散斑统计引起的本征噪声和散粒噪声的影响。我们展示了我们的模型在不同条件下模拟TD-DCS测量的能力，并使用我们的模型在几种典型的测量条件下比较了TD-DCS和CW-DCS的性能。我们建立了一个蒙特卡洛波模型，它能够从第一性原理出发模拟CW-DCS和TD-DCS的测量。在我们对参数空间的探索中，我们找不到TD-DCS优于CW-DCS的现实测量条件。然而，TD-DCS对比度噪声比优化的参数空间较大且复杂，因此我们的结果并不意味着TD-DCS在不同条件下的性能确实优于CW-DCS。我们将我们的代码公开提供给该领域的其他人，以找到有利于TD-DCS的用例。TD-DCS还提供了一种使用较短的源-探测器间隔来测量深部脑组织动力学的有前景的方法，这将有助于高密度分布式控制系统和使用有限数量的源-探测器对的图像重建等技术的发展。
Diffuse correlation spectroscopy (DCS) is an optical technique that measures blood flow non-invasively and continuously. The time-domain (TD) variant of DCS, namely, TD-DCS has demonstrated a potential to improve brain depth sensitivity and to distinguish superficial from deeper blood flow by utilizing pulsed laser sources and a gating strategy to select photons with different pathlengths within the scattering tissue using a single source–detector separation. A quantitative tool to predict the performance of TD-DCS that can be compared with traditional continuous wave DCS (CW-DCS) currently does not exist but is crucial to provide guidance for the continued development and application of these DCS systems. We aim to establish a model to simulate TD-DCS measurements from first principles, which enables analysis of the impact of measurement noise that can be utilized to quantify the performance for any particular TD-DCS system and measurement geometry. We have integrated the Monte Carlo simulation describing photon scattering in biological tissue with the wave model that calculates the speckle intensity fluctuations due to tissue dynamics to simulate TD-DCS measurements from first principles. Our model is capable of simulating photon counts received at the detector as a function of time for both CW-DCS and TD-DCS measurements. The effects of the laser coherence, instrument response function, detector gate delay, gate width, intrinsic noise arising from speckle statistics, and shot noise are incorporated in the model. We have demonstrated the ability of our model to simulate TD-DCS measurements under different conditions, and the use of our model to compare the performance of TD-DCS and CW-DCS under a few typical measurement conditions. We have established a Monte Carlo-Wave model that is capable of simulating CW-DCS and TD-DCS measurements from first principles. In our exploration of the parameter space, we could not find realistic measurement conditions under which TD-DCS outperformed CW-DCS. However, the parameter space for the optimization of the contrast to noise ratio of TD-DCS is large and complex, so our results do not imply that TD-DCS cannot indeed outperform CW-DCS under different conditions. We made our code available publicly for others in the field to find use cases favorable to TD-DCS. TD-DCS also provides a promising way to measure deep brain tissue dynamics using a short source–detector separation, which will benefit the development of technologies including high density DCS systems and image reconstruction using a limited number of source–detector pairs.