University of Pennsylvania , Department of Physics and Astronomy, 3231 Walnut Street, Philadelphia, Pennsylvania 19104, United States.
University of Pennsylvania , Department of Physics and Astronomy, 3231 Walnut Street, Philadelphia, Pennsylvania 19104, United States ; Children's Hospital of Philadelphia , Division of Neurology, 3401 Civic Center Boulevard, Philadelphia, Pennsylvania 19104, United States.
Neurophotonics. 2015 Jul;2(3):035004. doi: 10.1117/1.NPh.2.3.035004. Epub 2015 Aug 4.
We introduce and validate a pressure measurement paradigm that reduces extracerebral contamination from superficial tissues in optical monitoring of cerebral blood flow with diffuse correlation spectroscopy (DCS). The scheme determines subject-specific contributions of extracerebral and cerebral tissues to the DCS signal by utilizing probe pressure modulation to induce variations in extracerebral blood flow. For analysis, the head is modeled as a two-layer medium and is probed with long and short source-detector separations. Then a combination of pressure modulation and a modified Beer-Lambert law for flow enables experimenters to linearly relate differential DCS signals to cerebral and extracerebral blood flow variation without a priori anatomical information. We demonstrate the algorithm's ability to isolate cerebral blood flow during a finger-tapping task and during graded scalp ischemia in healthy adults. Finally, we adapt the pressure modulation algorithm to ameliorate extracerebral contamination in monitoring of cerebral blood oxygenation and blood volume by near-infrared spectroscopy.
我们引入并验证了一种压力测量范式,该范式可减少在使用漫反射相关光谱(DCS)进行脑血流光学监测时来自表面组织的脑外污染。该方案通过利用探头压力调制来诱导脑外血流变化,从而确定 DCS 信号中外脑组织和脑组织的特定于个体的贡献。在分析中,头部被建模为两层介质,并使用长和短的源-探测器分离进行探测。然后,压力调制和用于流量的修正 Beer-Lambert 定律的组合使实验者能够在线性上将差分 DCS 信号与脑血流和脑外血流变化相关联,而无需先验的解剖信息。我们证明了该算法在手指敲击任务和健康成年人分级头皮缺血期间隔离脑血流的能力。最后,我们将压力调制算法改编为通过近红外光谱来改善脑血氧和血流监测中的脑外污染。