Department of Mechanical and Materials Engineering, Wright State University, Dayton, OH, 45435, USA.
Department of Mechanical and Materials Engineering, Wright State University, Dayton, OH, 45435, USA.
Comput Biol Med. 2024 Jun;176:108563. doi: 10.1016/j.compbiomed.2024.108563. Epub 2024 May 6.
Boundary conditions (BCs) is one pivotal factor influencing the accuracy of hemodynamic predictions on intracranial aneurysms (IAs) using computational fluid dynamics (CFD) modeling. Unfortunately, a standard procedure to secure accurate BCs for hemodynamic modeling does not exist. To bridge such a knowledge gap, two representative patient-specific IA models (Case-I and Case-II) were reconstructed and their blood flow velocity waveforms in the internal carotid artery (ICA) were measured by ultrasonic techniques and modeled by discrete Fourier transform (DFT). Then, numerical investigations were conducted to explore the appropriate number of samples (N) for DFT modeling to secure the accurate BC by comparing a series of hemodynamic parameters using in-vitro validated CFD modeling. Subsequently, a comprehensive comparison in hemodynamic characteristics under patient-specific BCs and a generalized BC based on a one-dimensional (1D) model was conducted to reinforce the understanding that a patient-specific BC is pivotal for accurate hemodynamic risk evaluations on IA pathophysiology. In addition, the influence of the variance of heart rate/cardiac pulsatile period on hemodynamic characteristics in IA models was studied preliminarily. The results showed that N ≥ 16 for DFT model is a decent choice to secure the proper BC profile to calculate time-averaged hemodynamic parameters, while more data points such as N ≥ 36 can ensure the accuracy of instantaneous hemodynamic predictions. In addition, results revealed the generalized BC could overestimate or underestimate the hemodynamic risks on IAs significantly; thus, patient-specific BCs are highly recommended for hemodynamic modeling for IA risk evaluation. Furthermore, this study discovered the variance of heart rate has rare influences on hemodynamic characteristics in both instantaneous and time-averaged parameters under the assumption of an identical blood flow rate.
边界条件 (BCs) 是影响使用计算流体动力学 (CFD) 模型对颅内动脉瘤 (IA) 进行血流动力学预测准确性的关键因素之一。不幸的是，目前尚不存在确保血流动力学建模准确边界条件的标准程序。为了弥补这一知识空白，本研究重建了两个具有代表性的患者特定的 IA 模型 (Case-I 和 Case-II)，并使用超声技术测量了颈内动脉 (ICA) 中的血流速度波形，通过离散傅里叶变换 (DFT) 对其进行建模。然后，通过比较一系列使用体外验证的 CFD 建模的血流动力学参数，进行数值研究，以探索 DFT 建模中合适的样本数量 (N)，从而确保准确的边界条件。随后，在患者特定的边界条件和基于一维 (1D) 模型的广义边界条件下，对血流动力学特征进行了全面比较，以强化这样一种认识，即患者特定的边界条件对于准确评估 IA 病理生理学中的血流动力学风险至关重要。此外，初步研究了心率/心脏脉动周期变化对 IA 模型血流动力学特征的影响。结果表明，对于 DFT 模型，N ≥ 16 是确保适当边界条件轮廓以计算时均血流动力学参数的不错选择，而更多的数据点，如 N ≥ 36，则可以确保瞬时血流动力学预测的准确性。此外，研究结果表明，广义边界条件可能会显著高估或低估 IA 的血流动力学风险；因此，强烈建议对 IA 风险评估的血流动力学建模采用患者特定的边界条件。此外，本研究发现，在假设相同血流量的情况下，心率的变化对瞬时和时均参数下的血流动力学特征的影响很小。
