Janiga Gábor
Lab. of Fluid Dynamics and Technical Flows, University of Magdeburg "Otto von Guericke", Universitätsplatz 2, Magdeburg D-39106, Germany.
J Biomech. 2019 Jan 3;82:80-86. doi: 10.1016/j.jbiomech.2018.10.014. Epub 2018 Oct 27.
The comparison of different time-varying three-dimensional hemodynamic data (4D) is a formidable task. The purpose of this study is to investigate the potential of the proper orthogonal decomposition (POD) for a quantitative assessment.
The complex spatial-temporal flow information was analyzed using proper orthogonal decomposition to reduce the complexity of the system. PC-MRI blood flow measurements and computational fluid dynamic simulations of two subject-specific IAs were used to compare the different flow modalities. The concept of Modal Assurance Criterion (MAC) provided a further detailed objective characterization of the most energetic individual modes.
The most energetic flow modes were qualitatively compared by visual inspection. The distribution of the kinetic energy on the modes was used to quantitatively compare pulsatile flow data, where the most energetic mode was associated to approximately 90% of the total kinetic energy. This distribution was incorporated in a single measure, termed spectral entropy, showing good agreement especially for Case 1.
The proposed quantitative POD-based technique could be a valuable tool to reduce the complexity of the time-dependent hemodynamic data and to facilitate an easy comparison of 4D flows, e.g., for validation purposes.
比较不同的时变三维血流动力学数据（4D）是一项艰巨的任务。本研究的目的是探讨本征正交分解（POD）用于定量评估的潜力。
使用本征正交分解分析复杂的时空流动信息，以降低系统的复杂性。通过相位对比磁共振成像（PC-MRI）血流测量和两个特定个体颅内动脉瘤（IA）的计算流体动力学模拟，比较不同的流动模式。模态保证准则（MAC）的概念为最具能量的个体模态提供了更详细的客观表征。
通过目视检查对最具能量的流动模态进行了定性比较。利用模态上的动能分布对脉动血流数据进行定量比较，其中最具能量的模态约占总动能的90%。这种分布被纳入一个称为频谱熵的单一测量指标中，特别是在病例1中显示出良好的一致性。
所提出的基于POD的定量技术可能是一种有价值的工具，可降低随时间变化的血流动力学数据的复杂性，并便于对4D流动进行轻松比较，例如用于验证目的。
