The transition of the inflow jet to turbulence is crucial in understanding the pathology of brain aneurysms. Previous works (Le et al., 2010, Le et al., 2013) have shown evidence for a highly dynamic inflow jet in the ostium of brain aneurysms. While it is highly desired to investigate this inflow jet dynamics in clinical practice, the constraints on spatial and temporal resolutions of in vivo data do not allow a detailed analysis of this transition. In this work, Dynamic Mode Decomposition (DMD) is used to identify the most energetic modes of the inflow jet in patient-specific models of internal carotid aneurysms via the utilization of high-resolution simulation data. It is hypothesized that dynamic modes are not solely controlled by the blood flow waveform at the parent artery. They are also dependent on jet-wall interaction phenomena. DMD analysis shows that the spatial extent of low- frequency modes corresponds well to the most energetic areas of the inflow jet. The high-frequency modes are short-lived and correspond to the flow separation at the proximal neck and the jet’s impingement onto the aneurysmal wall. Low-frequency modes can be reconstructed at relatively low spatial and temporal resolutions comparable to ones of in vivo data. The current results suggest that DMD can be practically useful in analyzing blood flow patterns of brain aneurysms with in vivo data.

流入射流向湍流的过渡对于理解脑动脉瘤的病理学至关重要。先前的研究（Le等，2010； Le等，2013）已经显示出脑动脉瘤口中动态血流的证据。虽然非常需要在临床实践中研究这种流入射流的动力学，但对体内时空分辨率的限制数据不允许对此转换进行详细分析。在这项工作中，动态模式分解（DMD）用于通过高分辨率模拟数据的利用来识别特定于患者的内部颈动脉瘤模型中流入射流的最活跃模式。假设动态模式不仅仅由母动脉处的血流波形控制。它们还取决于喷射壁相互作用现象。DMD分析表明，低频模式的空间范围很好地对应于射流的最活跃区域。高频模式是短暂的，并且对应于近端颈部处的血流分离以及射流对动脉瘤壁的撞击。低频模式可以在相对较低的空间和时间分辨率下与体内数据。目前的结果表明，DMD在利用体内数据分析脑动脉瘤的血流模式方面实际上是有用的。