Prediction of Cerebral Aneurysm Hemodynamics With Porous-Medium Models of Flow-Diverting Stents via Deep Learning

Gaoyang Li,Youjun Liu,Haoran Wang,Aike Qiao,Siwei Liu,Jiayuan Ji,Xuezheng Wang,Yuting Guo,Xiaorui Song

doi:10.3389/fphys.2021.733444

Abstract

The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function <13%), but the calculation time is significantly reduced 1,800 times. This study develops a novel deep learning method that can accurately predict the hemodynamics of different cerebral aneurysms before and after FD stent placement with low computational cost and simple operation processes.

Highlights

Strokes, including cerebral aneurysms, have the highest mortality rate of diseases worldwide (Tsai et al, 2018)
The data sets used in this study were from the Computational fluid dynamics (CFD) simulation hemodynamics of the side-wall aneurysms before and after FD stent placement
The five morphological parameters were the diameter of aneurysm (DA), distance from aneurysm center point to parent artery center line (CC), diameter of parent artery (DP), curvature of parent artery (CP), and location of aneurysm (LA)

Summary

Introduction

Strokes, including cerebral aneurysms, have the highest mortality rate of diseases worldwide (Tsai et al, 2018). Flow-diverting (FD) stent placement is a common and effective method for treating cerebral aneurysms (Li Y. et al, 2018). Based on the given boundary conditions and geometric information of the model, CFD can solve the conservation equations of mass, momentum and energy on the discrete meshes by the Navier–Stokes equation, and obtain the numerical solutions of the flow field hemodynamics. When calculating the hemodynamics of cerebral aneurysm with FD stent, CFD often needs complex operation processes and high computational costs. This is due to the construction and placement simulation of a fully resolved FD stent, which usually requires professional operation skills and long-time iterative calculation (Zhang et al, 2017). It is necessary to develop a method with simple operations and low computational costs

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Discussion

Conclusion