Neural Systems and Dynamics Laboratory, Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
J Neurosci Methods. 2011 Apr 15;197(1):171-9. doi: 10.1016/j.jneumeth.2011.01.032. Epub 2011 Feb 15.
A method has been recently developed to reduce the confounding factors of extracranial origins on the intracranial latency (the time interval between the electrocardiogram QRS component and the initial inflection of the resulting pulse). Although, the proposed model was shown to portray a better characterization of cerebral vasculature, the parameters of the model and their physiological interpretations have not been fully explored. The present work improves the physiological understanding of these parameters, refines the model and extends its ability to monitor real-time changes in overall cerebrovascular resistance. We show that the slope of the linear model which relates the latency of arterial blood pressure to that of the cerebral blood flow velocity, could be a measure of resistance, and that the intercept is a function of slope and pre-ejection period. A dataset of cerebral blood flow velocity and arterial blood pressure signals from 18 normal subjects at rest was used to validate the derived parameters of the model. Also, the results of further data processing verified our hypothesis that the slope of the model would significantly increase during a period of CO₂ rebreathing, due to dilation of the vessels and reduction of cerebrovascular resistance (p ≤ 0.02). Finally as the slope of the proposed model is shown to be highly correlated with other conventional measures of cerebrovascular resistance, (resistance area product and critical closing pressure), we conclude that the derived slope metric is a measure of overall cerebrovascular resistance and therefore could be useful in guiding the non-invasive cerebrovascular management of patients.
最近开发了一种方法来减少颅外起源对颅内潜伏期(心电图 QRS 分量与产生的脉搏初始拐点之间的时间间隔)的混杂因素。虽然所提出的模型显示出更好地描述脑血管的能力,但该模型的参数及其生理解释尚未得到充分探索。本工作提高了对这些参数的生理理解,改进了模型,并扩展了其监测整体脑血管阻力实时变化的能力。我们表明,将动脉血压潜伏期与脑血流速度潜伏期相关联的线性模型的斜率可以作为阻力的度量,而截距是斜率和射血前期的函数。使用来自 18 名正常休息受试者的脑血流速度和动脉血压信号数据集来验证模型的推导参数。此外,进一步的数据处理结果验证了我们的假设,即在 CO₂ 再呼吸期间,由于血管扩张和脑血管阻力降低,模型的斜率会显著增加(p ≤ 0.02)。最后,由于所提出的模型的斜率与其他脑血管阻力的常规测量值(阻力面积乘积和临界关闭压力)高度相关,因此我们得出结论,所得斜率指标是整体脑血管阻力的度量,因此可用于指导患者的非侵入性脑血管管理。