Acharya Deepshikha, Mukherjea Ankita, Cao Jiaming, Ruesch Alexander, Schmitt Samantha, Yang Jason, Smith Matthew A, Kainerstorfer Jana M
Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Metabolites. 2022 Jul 20;12(7):667. doi: 10.3390/metabo12070667.
Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measure cerebral hemodynamics, which in turn can be used to assess the cerebral metabolic rate of oxygen (CMRO) and cerebral autoregulation (CA). However, current mathematical models for CMRO estimation make assumptions that break down for cerebral perfusion pressure (CPP)-induced changes in CA. Here, we performed preclinical experiments with controlled changes in CPP while simultaneously measuring NIRS and DCS at rest. We observed changes in arterial oxygen saturation (10%) and arterial blood volume (50%) with CPP, two variables often assumed to be constant in CMRO estimations. Hence, we propose a general mathematical model that accounts for these variations when estimating CMRO and validate its use for CA monitoring on our experimental data. We observed significant changes in the various oxygenation parameters, including the coupling ratio (CMRO/blood flow) between regions of autoregulation and dysregulation. Our work provides an appropriate model and preliminary experimental evidence for the use of NIRS- and DCS-based tissue oxygenation and metabolism metrics for non-invasive diagnosis of CA health in CPP-altering neuropathologies.
近红外光谱（NIRS）和扩散相关光谱（DCS）可测量脑血流动力学，进而用于评估脑氧代谢率（CMRO）和脑自动调节功能（CA）。然而，当前用于估计CMRO的数学模型所做的假设，在脑灌注压（CPP）引起的CA变化情况下不再成立。在此，我们进行了临床前实验，在控制CPP变化的同时，于静息状态下同步测量NIRS和DCS。我们观察到，随着CPP变化，动脉血氧饱和度（约10%）和动脉血容量（约50%）发生了变化，而这两个变量在CMRO估计中通常被假定为恒定不变。因此，我们提出了一个通用数学模型，在估计CMRO时考虑这些变化，并基于我们的实验数据验证了其用于监测CA的有效性。我们观察到各种氧合参数发生了显著变化，包括自动调节和失调区域之间的耦合比（CMRO/血流）。我们的工作为利用基于NIRS和DCS的组织氧合及代谢指标对CPP改变的神经病理学中CA健康状况进行无创诊断提供了合适的模型和初步实验证据。
