颈内动脉
流入
医学
波形
脉动流
计算流体力学
动脉瘤
心脏病学
血流
血流动力学
内科学
外科
机械
物理
量子力学
电压
作者
Mehdi Najafi,Nicole M Cancelliere,Olivier Brina,Pierre Bouillot,María Isabel Vargas,Bénédicte MA Delattre,Vítor Mendes Pereira,David A. Steinman
标识
DOI:10.1136/neurintsurg-2020-015993
摘要
Background Computational fluid dynamics (CFD) has become a popular tool for studying ‘patient-specific’ blood flow dynamics in cerebral aneurysms; however, rarely are the inflow boundary conditions patient-specific. We aimed to test the impact of widespread reliance on generalized inflow rates. Methods Internal carotid artery (ICA) flow rates were measured via 2D cine phase-contrast MRI for 24 patients scheduled for endovascular therapy of an ICA aneurysm. CFD models were constructed from 3D rotational angiography, and pulsatile inflow rates imposed as measured by MRI or estimated using an average older-adult ICA flow waveform shape scaled by a cycle-average flow rate (Q avg ) derived from the patient’s ICA cross-sectional area via an assumed inlet velocity. Results There was good overall qualitative agreement in the magnitudes and spatial distributions of time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and spectral power index (SPI) using generalized versus patient-specific inflows. Sac-averaged quantities showed moderate to good correlations: R 2 =0.54 (TAWSS), 0.80 (OSI), and 0.68 (SPI). Using patient-specific Q avg to scale the generalized waveform shape resulted in near-perfect agreement for TAWSS, and reduced bias, but not scatter, for SPI. Patient-specific waveform had an impact only on OSI correlations, which improved to R 2 =0.93. Conclusions Aneurysm CFD demonstrates the ability to stratify cases by nominal hemodynamic ‘risk’ factors when employing an age- and vascular-territory-specific recipe for generalized inflow rates. Q avg has a greater influence than waveform shape, suggesting some improvement could be achieved by including measurement of patient-specific Q avg into aneurysm imaging protocols.
科研通智能强力驱动
Strongly Powered by AbleSci AI