Du Le V N, Srinivasan Vivek J
Opt Express. 2020 Apr 13;28(8):11191-11214. doi: 10.1364/OE.385202.
Diffusing wave spectroscopy (DWS) and diffuse correlation spectroscopy (DCS) can assess blood flow index (BFI) of biological tissue with multiply scattered light. Though the main biological function of red blood cells (RBCs) is advection, in DWS/DCS, RBCs are assumed to undergo Brownian motion. To explain this discrepancy, we critically examine the cumulant approximation, a major assumption in DWS/DCS. We present a precise criterion for validity of the cumulant approximation, and in realistic tissue models, identify conditions that invalidate it. We show that, in physiologically relevant scenarios, the first cumulant term for random flow and second cumulant term for Brownian motion alone can cancel each other. In such circumstances, assuming pure Brownian motion of RBCs and the first cumulant approximation, a routine practice in DWS/DCS of BFI, can yield good agreement with data, but only because errors due to two incorrect assumptions cancel out. We conclude that correctly assessing random flow from scattered light dynamics requires going beyond the cumulant approximation and propose a more accurate model to do so.
扩散波谱学(DWS)和扩散相关光谱学(DCS)可以利用多次散射光来评估生物组织的血流指数(BFI)。尽管红细胞(RBC)的主要生物学功能是平流,但在DWS/DCS中,红细胞被假定为进行布朗运动。为了解释这种差异,我们严格审视了累积量近似,这是DWS/DCS中的一个主要假设。我们提出了累积量近似有效性的精确标准,并在实际的组织模型中,确定了使其无效的条件。我们表明,在生理相关的情况下,随机流动的一阶累积量项和仅布朗运动的二阶累积量项可以相互抵消。在这种情况下,假设红细胞的纯布朗运动和一阶累积量近似(这是DWS/DCS中BFI的常规做法),可以与数据产生良好的一致性,但这仅仅是因为两个错误假设导致的误差相互抵消。我们得出结论,要从散射光动力学中正确评估随机流动,需要超越累积量近似,并提出了一个更准确的模型来实现这一点。