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Bond Graph Model of Cerebral Circulation: Toward Clinically Feasible Systemic Blood Flow Simulations

机译:脑循环的邦德图模型:走向临床可行的全身血流模拟

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摘要

We propose a detailed CellML model of the human cerebral circulation that runs faster than real time on a desktop computer and is designed for use in clinical settings when the speed of response is important. A lumped parameter mathematical model, which is based on a one-dimensional formulation of the flow of an incompressible fluid in distensible vessels, is constructed using a bond graph formulation to ensure mass conservation and energy conservation. The model includes arterial vessels with geometric and anatomical data based on the ADAN circulation model. The peripheral beds are represented by lumped parameter compartments. We compare the hemodynamics predicted by the bond graph formulation of the cerebral circulation with that given by a classical one-dimensional Navier-Stokes model working on top of the whole-body ADAN model. Outputs from the bond graph model, including the pressure and flow signatures and blood volumes, are compared with physiological data.
机译:我们提出了有关人脑循环的详细CellML模型,该模型在台式计算机上的运行速度比实时运行的速度快,并且设计用于在反应速度很重要的临床环境中使用。使用键合图公式构建集总参数数学模型,该模型基于一维公式表示可膨胀容器中不可压缩流体的流动,以确保质量守恒和节能。该模型包括具有基于ADAN循环模型的几何和解剖学数据的动脉血管。外围床由集总参数隔室表示。我们将通过脑循环结合图公式预测的血液动力学与在全身ADAN模型之上工作的经典一维Navier-Stokes模型给出的血液动力学进行比较。键合图模型的输出(包括压力和流量特征以及血容量)将与生理数据进行比较。

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