Mathematical models of cerebral hemodynamics for detection of vasospasm in major cerebral arteries.
Mathematical models of cerebral hemodynamics for detection of vasospasm in major cerebral arteries.
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DOI：
10.1007/978-3-211-85578-2_13
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Federico S. Cattivelli;A. H. Sayed;Xiao Hu;Darrin J. Lee;P. Vespa
中科院分区：
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作者：
Federico S. Cattivelli;A. H. Sayed;Xiao Hu;Darrin J. Lee;P. Vespa
背景血管痉挛是动脉瘤性蛛网膜下腔出血（SAH）的常见并发症，可能导致脑缺血和死亡。检测血管痉挛的标准方法是传统的脑血管造影，这种方法是侵入性的，并且不能连续监测动脉半径。血管痉挛的监测通常通过测量主要脑动脉中的脑血流速度 (CBFV) 并计算林德加德比来进行。我们描述了一种估计颅内动脉半径的替代方法，该方法基于建模和状态估计技术。目的是获得比林德加德比提供的更好的估计，这可能允许连续监测和可能的血管垃圾预测，而无需血管造影。方法我们提出了两种新的脑血流动力学模型。模型 1 是 Ursino 1991 年模型的更通用版本，其中包括血管痉挛的影响，模型 2 是模型 1 的简化版本。我们使用模型 1 生成针对不同血管痉挛情况的颅内压 (ICP) 和 CBFV 信号，其中 CBFV 是在大脑中动脉 (MCA) 处测量的。然后我们使用模型 2 从这些信号中估计动脉半径。结果模拟表明，模型 2 能够对 MCA 的半径提供良好的估计，从而能够检测血管痉挛。动脉半径的这些变化是通过 CBFV 的测量来估计的，并且 CBF 从未直接测量。这是基于模型的方法的主要优点，其中模型的微分方程考虑了 CBFV、ABP 和 ICP 之间的几个相互关系。结论我们的结果表明，可以使用 ABP、ICP 和 CBFV 的测量来估计动脉半径，从而可以检测血管痉挛。
BackgroundVasospasm is a common complication of aneurismal subarachnoid hemorrhage (SAH) that may lead to cerebral ischemia and death. The standard method for detection of vasospasm is conventional cerebral angiogra-phy, which is invasive and does not allow continuous monitoring of arterial radius. Monitoring of vasospasm is typically performed by measuring Cerebral Blood Flow Velocity (CBFV) in the major cerebral arteries and calculating the Lindegaard ratio. We describe an alternative approach to estimate intracranial arterial radius, which is based on modeling and state-estimation techniques. The objective is to obtain a better estimation than that offered by the Lindegaard ratio, that might allow for continuous monitoring and possibly vasospam prediction without the need for angiography.MethodsWe propose two new models of cerebral hemo-dynamics. Model 1 is a more general version of Ursino's 1991 model that includes the effects of vasospasm, and Model 2 is a simplified version of Model 1. We use Model 1 to generate Intracranial Pressure (ICP) and CBFV signals for different vasospasm conditions, where CBFV is measured at the middle cerebral artery (MCA). Then we use Model 2 to estimate the arterial radii from these signals.FindingsSimulations show that Model 2 is capable of providing good estimates for the radius of the MCA, allowing the detection of the vasospasm. These changes in arterial radius are being estimated from measurements of CBFV, and CBF is never being measured directly. This is the main advantage of the model-based approach where several interrelations between CBFV, ABP and ICP are taken into account by the differential equations of the model.ConclusionsOur results indicate that arterial radius may be estimated using measurements of ABP, ICP and CBFV, allowing the detection of vasospasm.