Suppr超能文献

直接评估脑外信号对脑血流、氧合和代谢光学测量的污染。

Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism.

作者信息

Milej Daniel, Abdalmalak Androu, Rajaram Ajay, St Lawrence Keith

机构信息

Lawson Health Research Institute, Imaging Program, London, Ontario, Canada.

Western University, Department of Medical Biophysics, London, Ontario, Canada.

出版信息

Neurophotonics. 2020 Oct;7(4):045002. doi: 10.1117/1.NPh.7.4.045002. Epub 2020 Oct 7.

Abstract

Near-infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), oxygenation, and oxygen metabolism. However, these methods are vulnerable to signal contamination from the scalp. Our work evaluated methods of reducing the impact of this contamination using time-resolved (TR) NIRS and multidistance (MD) DCS. The magnitude of scalp contamination was evaluated by measuring the flow, oxygenation, and metabolic responses to a global hemodynamic challenge. Contamination was assessed by collecting data with and without impeding scalp blood flow. Experiments involved healthy participants. A pneumatic tourniquet was used to cause scalp ischemia, as confirmed by contrast-enhanced NIRS, and a computerized gas system to generate a hypercapnic challenge. Comparing responses acquired with and without the tourniquet demonstrated that the TR-NIRS technique could reduce scalp contributions in hemodynamic signals up to 4 times ( ) and 6 times ( ). Similarly, blood flow responses from the scalp and brain could be separated by analyzing MD DCS data with a multilayer model. Using these techniques, there was no change in metabolism during hypercapnia, as expected, despite large increases in CBF and oxygenation. NIRS/DCS can accurately monitor CBF and metabolism with the appropriate enhancement to depth sensitivity, highlighting the potential of these techniques for neuromonitoring.

摘要

近红外光谱(NIRS)与扩散相关光谱(DCS)相结合,为监测脑血流量(CBF)、氧合和氧代谢提供了一种非侵入性方法。然而,这些方法容易受到头皮信号污染的影响。我们的工作评估了使用时间分辨(TR)NIRS和多距离(MD)DCS减少这种污染影响的方法。通过测量对整体血流动力学挑战的血流、氧合和代谢反应来评估头皮污染的程度。通过在有和没有阻碍头皮血流的情况下收集数据来评估污染情况。实验涉及健康参与者。使用气动止血带导致头皮缺血,这通过对比增强NIRS得到证实,并使用计算机化气体系统产生高碳酸血症挑战。比较使用止血带和不使用止血带时获得的反应表明,TR-NIRS技术可以将血流动力学信号中头皮的贡献减少多达4倍( )和6倍( )。同样,通过使用多层模型分析MD DCS数据,可以分离头皮和大脑的血流反应。使用这些技术,尽管CBF和氧合大幅增加,但正如预期的那样,高碳酸血症期间代谢没有变化。NIRS/DCS通过适当增强深度敏感性,可以准确监测CBF和代谢,突出了这些技术在神经监测方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e3/7540337/5e9221e60d40/NPh-007-045002-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验