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Information Theoretic Measurement of Blood Flow Complexity in Vessels and Aneurysms: Interlacing Complexity Index

机译:血管和动脉瘤血流复杂性的信息理论测量:隔行复杂度指数

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Haemodynamics is believed to be a crucial factor in the aneurysm formation, evolution and eventual rupture. The 3D blood flow is typically derived by computational fluid dynamics (CFD) from patient-specific models obtained from angiographic images. Typical quantitative haemodynamic indices are local. Some qualitative classifications of global haemodynamic features have been proposed. However these classifications are subjective, depending on the operator visual inspection. In this work we introduce an information theoretic measurement of the blood flow complexity, based on Shannon's Mutual Information, named Interlacing Complexity Index (ICI). ICI is an objective quantification of the flow complexity from aneurysm inlet to aneurysm outlets. It measures how unpredictable is the location of the streamlines at the outlets from knowing the location at the inlet, relative to the scale of observation. We selected from the @neurIST database a set of 49 cerebral vas-culatures with aneurysms in the middle cerebral artery. Surface models of patient-specific vascular geometries were obtained by geodesic active region segmentation and manual correction, and unsteady flow simulations were performed imposing physiological flow boundary conditions. The obtained ICI has been compared to several qualitative classifications performed by an expert, revealing high correlations.
机译:血流动力学被认为是动脉瘤形成,发展和最终破裂的关键因素。 3D血流通常通过从血管造影图像获得的患者特定模型的计算流体动力学(CFD)得出。典型的定量血流动力学指标是局部的。已经提出了整体血流动力学特征的一些定性分类。但是,这些分类是主观的,具体取决于操作员的目视检查。在这项工作中,我们介绍了基于Shannon的相互信息(称为隔行复杂度指数(ICI))的血流复杂性的信息理论测量方法。 ICI是对从动脉瘤入口到动脉瘤出口的血流复杂性的客观量化。通过了解相对于观测范围的入口位置,可以测量出流线在出口处的位置是如何不可预测的。我们从@neurIST数据库中选择了一组在大脑中动脉具有动脉瘤的49个脑血管。通过测地线活动区域分割和手动校正,获得了特定于患者的血管几何形状的表面模型,并通过施加生理流动边界条件进行了非稳态流动模拟。已将获得的ICI与专家进行的几种定性分类进行比较,显示出很高的相关性。

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