Suppr超能文献

扩展的颅内潜伏期模型有助于非侵入性检测脑血管变化。

An extended model of intracranial latency facilitates non-invasive detection of cerebrovascular changes.

机构信息

Neural Systems and Dynamics Laboratory, Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.

出版信息

J Neurosci Methods. 2011 Apr 15;197(1):171-9. doi: 10.1016/j.jneumeth.2011.01.032. Epub 2011 Feb 15.

Abstract

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.

摘要

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。

相似文献

1
An extended model of intracranial latency facilitates non-invasive detection of cerebrovascular changes.
J Neurosci Methods. 2011 Apr 15;197(1):171-9. doi: 10.1016/j.jneumeth.2011.01.032. Epub 2011 Feb 15.
2
Dynamics of cerebral blood flow regulation explained using a lumped parameter model.
Am J Physiol Regul Integr Comp Physiol. 2002 Feb;282(2):R611-22. doi: 10.1152/ajpregu.00285.2001.
3
Inferring cerebrovascular changes from latencies of systemic and intracranial pulses: a model-based latency subtraction algorithm.
J Cereb Blood Flow Metab. 2009 Apr;29(4):688-97. doi: 10.1038/jcbfm.2008.160. Epub 2009 Jan 14.
5
The critical closing pressure of the cerebral circulation.
Med Eng Phys. 2003 Oct;25(8):621-32. doi: 10.1016/s1350-4533(03)00027-4.
6
Estimation and identification of parameters in a lumped cerebrovascular model.
Math Biosci Eng. 2009 Jan;6(1):93-115. doi: 10.3934/mbe.2009.6.93.
7
Latency relationships between cerebral blood flow velocity and intracranial pressure.
Acta Neurochir Suppl. 2012;114:5-9. doi: 10.1007/978-3-7091-0956-4_2.

引用本文的文献

1
Intracranial Blood Flow Quantification by Accelerated Dual-venc 4D Flow MRI: Comparison With Transcranial Doppler Ultrasound.
J Magn Reson Imaging. 2022 Oct;56(4):1256-1264. doi: 10.1002/jmri.28115. Epub 2022 Feb 10.
2
Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach.
Physiol Meas. 2020 Nov 6;41(10):104003. doi: 10.1088/1361-6579/abbcbb.
3
Identification of Pulse Onset on Cerebral Blood Flow Velocity Waveforms: A Comparative Study.
Biomed Res Int. 2019 Jul 2;2019:3252178. doi: 10.1155/2019/3252178. eCollection 2019.
5
Steady-state indicators of the intracranial pressure dynamic system using geodesic distance of the ICP pulse waveform.
Physiol Meas. 2012 Dec;33(12):2017-31. doi: 10.1088/0967-3334/33/12/2017. Epub 2012 Nov 15.

本文引用的文献

1
Effects of hypobaric hypoxia on cerebral autoregulation.
Stroke. 2010 Apr;41(4):641-6. doi: 10.1161/STROKEAHA.109.574749. Epub 2010 Feb 25.
2
Inferring cerebrovascular changes from latencies of systemic and intracranial pulses: a model-based latency subtraction algorithm.
J Cereb Blood Flow Metab. 2009 Apr;29(4):688-97. doi: 10.1038/jcbfm.2008.160. Epub 2009 Jan 14.
3
An algorithm for extracting intracranial pressure latency relative to electrocardiogram R wave.
Physiol Meas. 2008 Apr;29(4):459-71. doi: 10.1088/0967-3334/29/4/004. Epub 2008 Mar 17.
5
Modelling the circle of Willis to assess the effects of anatomical variations and occlusions on cerebral flows.
J Biomech. 2007;40(8):1794-805. doi: 10.1016/j.jbiomech.2006.07.008. Epub 2006 Oct 11.
6
Differential sensitivities of cerebral and brachial blood flow to hypercapnia in humans.
J Appl Physiol (1985). 2007 Jan;102(1):87-93. doi: 10.1152/japplphysiol.00772.2006. Epub 2006 Oct 5.
7
Arterial stiffness in Behcet's disease: increased regional pulse wave velocity values.
Ann Rheum Dis. 2006 Mar;65(3):415-6. doi: 10.1136/ard.2005.043430.
8
Spatiotemporal pattern of the extracranial component of the rheoencephalographic signal.
Physiol Meas. 2005 Dec;26(6):925-38. doi: 10.1088/0967-3334/26/6/004. Epub 2005 Sep 23.
9
Pulse transit time measured from the ECG: an unreliable marker of beat-to-beat blood pressure.
J Appl Physiol (1985). 2006 Jan;100(1):136-41. doi: 10.1152/japplphysiol.00657.2005. Epub 2005 Sep 1.
10
Prediction of cerebral vasospasm in patients presenting with aneurysmal subarachnoid hemorrhage: a review.
Neurosurgery. 2005 Apr;56(4):633-54; discussion 633-54. doi: 10.1227/01.neu.0000156644.45384.92.

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