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利用CT、血管内超声(IVUS)和双平面X线血管造影图像将内膜和外膜模型重建为未受导管影响的状态。

Reconstruction of Intima and Adventitia Models into a State Undeformed by a Catheter by Using CT, IVUS, and Biplane X-Ray Angiogram Images.

作者信息

Son Jinwon, Choi Young

机构信息

School of Mechanical Engineering, Chung-Ang University, 221 Heukseok-dong, Dongjak-gu, Seoul 156-756, Republic of Korea.

出版信息

Comput Math Methods Med. 2017;2017:9807617. doi: 10.1155/2017/9807617. Epub 2017 Jan 5.

Abstract

The number of studies on blood flow analysis using fluid-structure interaction (FSI) analysis is increasing. Though a 3D blood vessel model that includes intima and adventitia is required for FSI analysis, there are difficulties in generating it using only one type of medical imaging. In this paper, we propose a 3D modeling method for accurate FSI analysis. An intravascular ultrasound (IVUS) image is used with biplane X-ray angiogram images to calculate the position and orientation of the blood vessel. However, these images show that the blood vessel is deformed by the catheter inserted into the blood vessel for IVUS imaging. To eliminate such deformation, a CT image was added and the two models were registered. First, a 3D model of the undeformed intima was generated using a CT image. In the second stage, a model of intima and adventitia deformed by the catheter was generated by combining the IVUS image and the X-ray angiogram images. A 3D model of intima and adventitia with the deformation caused by insertion of the catheter eliminated was generated by matching these 3D blood vessel models in different states. In addition, a 3D blood vessel model including bifurcation was generated using the proposed method.

摘要

使用流固耦合(FSI)分析进行血流分析的研究数量正在增加。尽管FSI分析需要一个包含内膜和外膜的三维血管模型,但仅使用一种医学成像技术来生成该模型存在困难。在本文中,我们提出了一种用于精确FSI分析的三维建模方法。将血管内超声(IVUS)图像与双平面X射线血管造影图像结合使用,以计算血管的位置和方向。然而,这些图像显示血管因插入用于IVUS成像的导管而变形。为了消除这种变形,添加了CT图像并对两个模型进行了配准。首先,使用CT图像生成未变形内膜的三维模型。在第二阶段,通过结合IVUS图像和X射线血管造影图像生成因导管而变形的内膜和外膜模型。通过匹配不同状态下的这些三维血管模型,生成了消除了因导管插入而导致的变形的内膜和外膜三维模型。此外,使用所提出的方法生成了包括分叉的三维血管模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3740/5244750/c5d87e841e32/CMMM2017-9807617.001.jpg

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