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利用近红外光谱光电容积脉搏波描记法增强扩散相关光谱搏动性脑血流信号

Enhancing diffuse correlation spectroscopy pulsatile cerebral blood flow signal with near-infrared spectroscopy photoplethysmography.

作者信息

Wu Kuan Cheng, Martin Alyssa, Renna Marco, Robinson Mitchell, Ozana Nisan, Carp Stefan A, Franceschini Maria Angela

机构信息

Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States.

Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States.

出版信息

Neurophotonics. 2023 Jul;10(3):035008. doi: 10.1117/1.NPh.10.3.035008. Epub 2023 Sep 6.

Abstract

SIGNIFICANCE

Combining near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) allows for quantifying cerebral blood volume, flow, and oxygenation changes continuously and non-invasively. As recently shown, the DCS pulsatile cerebral blood flow index () can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance ().

AIM

Although current DCS technology allows for reliable monitoring of the slow hemodynamic changes, resolving pulsatile blood flow at large source-detector separations, which is needed to ensure cerebral sensitivity, is challenging because of its low signal-to-noise ratio (SNR). Cardiac-gated averaging of several arterial pulse cycles is required to obtain a meaningful waveform.

APPROACH

Taking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS , reducing the coefficient of variation of the recovered pulsatile waveform () and allowing for an unprecedented temporal resolution (266 Hz) at a large source-detector separation ().

RESULTS

In 10 healthy subjects, we verified the quality of the NIRS-PPG during common tasks, showing high fidelity against ( ). We recovered CrCP and at 0.25 Hz, times faster than previously achieved with DCS.

CONCLUSIONS

NIRS-PPG improves DCS SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and .

摘要

意义

结合近红外光谱(NIRS)和扩散相关光谱(DCS)能够连续且无创地量化脑血容量、血流和氧合变化。最近的研究表明,DCS搏动性脑血流指数()可用于量化临界关闭压(CrCP)和脑血管阻力()。

目的

尽管当前的DCS技术能够可靠地监测缓慢的血流动力学变化,但由于其低信噪比(SNR),在确保脑敏感性所需的大源探测器间距下解析搏动性血流具有挑战性。需要对几个动脉搏动周期进行心脏门控平均才能获得有意义的波形。

方法

利用NIRS的高信噪比,我们展示了一种方法,该方法使用NIRS光电容积脉搏波描记法(NIRS-PPG)的搏动信号来模拟DCS,降低恢复的搏动波形()的变异系数,并在大源探测器间距()下实现前所未有的时间分辨率(266Hz)。

结果

在10名健康受试者中,我们在常见任务期间验证了NIRS-PPG的质量,显示出与()相比的高保真度。我们在0.25Hz时恢复了CrCP和,速度比以前使用DCS快倍。

结论

NIRS-PPG提高了DCS的SNR,减少了恢复CrCP和所需的门控平均心跳次数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/10482352/b454887dcd2e/NPh-010-035008-g001.jpg

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