Gholampour Seifollah, Fatouraee Nasser
Department of Biomedical Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran.
Biological Fluid Mechanics Research Laboratory, Biomechanics Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran.
Commun Biol. 2021 Mar 23;4(1):394. doi: 10.1038/s42003-021-01920-w.
Three-D head geometrical models of eight healthy subjects and 11 hydrocephalus patients were built using their CINE phase-contrast MRI data and used for computer simulations under three different inlet/outlet boundary conditions (BCs). The maximum cerebrospinal fluid (CSF) pressure and the ventricular system volume were more effective and accurate than the other parameters in evaluating the patients' conditions. In constant CSF pressure, the computational patient models were 18.5% more sensitive to CSF volume changes in the ventricular system under BC "C". Pulsatile CSF flow rate diagrams were used for inlet and outlet BCs of BC "C". BC "C" was suggested to evaluate the intracranial compliance of the hydrocephalus patients. The results suggested using the computational fluid dynamic (CFD) method and the fully coupled fluid-structure interaction (FSI) method for the CSF dynamic analysis in patients with external and internal hydrocephalus, respectively.
利用8名健康受试者和11名脑积水患者的电影相位对比磁共振成像(CINE phase-contrast MRI)数据构建了三维头部几何模型,并在三种不同的进出口边界条件(BCs)下用于计算机模拟。在评估患者病情时,最大脑脊液(CSF)压力和脑室系统体积比其他参数更有效、更准确。在恒定脑脊液压力下,计算患者模型在边界条件“C”下对脑室系统中脑脊液体积变化的敏感度高18.5%。脉动脑脊液流速图用于边界条件“C”的进出口边界。建议采用边界条件“C”来评估脑积水患者的颅内顺应性。结果表明,分别采用计算流体动力学(CFD)方法和全耦合流固相互作用(FSI)方法对外部和内部脑积水患者进行脑脊液动力学分析。