基于扩散相干散斑技术的脑血流检测方法研究

Research on Cerebral Blood Flow Detection Based on Diffuse Speckle Technique

摘要:

脑血流（Cerebral Blood Flow，CBF）是脑血管疾病早期预警、精准诊疗及脑功能机制解析的关键生物标志物。针对近红外光检测脑血流系统中信噪比、检测深度与大脑特异性之间相互制约的问题，本文结合光外差检测技术与扩散干涉光谱技术，搭建了扩散相干散斑成像系统，使用CMOS相机实现了对脑血流的低成本、高灵敏度并行检测。通过在体的被动体位改变实验，与“金标准”经颅多普勒技术（Transcranial Doppler, TCD）同步进行脑血流检测，检测结果表明系统测量的脑血流指数（Blood Flow Index，BFI）与TCD测量的峰值收缩期血流速度（Peak Systolic Velocity, PSV）、平均血流速度（Mean Velocity, MV）和舒张末期血流速度（End diastolic Velocity, EDV）具有一定的线性相关性，证明了系统具有一定的在体监测脑血流的能力，有望进一步在临床上应用。

Abstract:

Cerebral Blood Flow (CBF) serves as a crucial biomarker for the early warning, precise diagnosis, and treatment of cerebrovascular diseases, as well as for the analysis of the brain function mechanism. In the near-infrared light detection of the cerebral blood flow system, there exists an issue of mutual constraints among the signal-to-noise ratio, detection depth, and brain specificity. To address this, this paper integrated optical heterodyne detection technology and diffusion interference spectrum technology to construct a diffusion speckle imaging system. Moreover, a CMOS camera was employed to realize low-cost, high-sensitivity parallel detection of cerebral blood flow. Through in-vivo passive posture change experiments, the cerebral blood flow was synchronously detected using the “gold standard” transcranial Doppler (TCD) technology. The detection results demonstrated that the blood flow index (BFI) measured by the system exhibits a certain linear correlation with the peak systolic velocity (PSV), mean velocity (MV), and end diastolic velocity (EDV) measured by TCD. This verified that the system has a certain capacity for in-vivo cerebral blood flow monitoring and holds promise for further clinical applications.