Virtual Interventions for Image-based Blood Flow Computation.
Virtual Interventions for Image-based Blood Flow Computation.
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DOI：
10.1016/j.cad.2011.01.004
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发表时间：
2012-01
期刊：
影响因子：
--
通讯作者：
Taylor CA
中科院分区：
文献类型：
--
作者：
Xiong G;Choi G;Taylor CA
基于图像的血流计算为血管装置的评估和外科手术的评估提供了广阔的前景。然而，许多先前的研究采用理想化的动脉和设备模型，或者仅采用设备部署后的图像数据中的患者特定模型，因为用于模型构建的工具不可用或有限且使用繁琐。此外，与现有数据的回顾性研究相比，迫切需要以手术规划为目标的前瞻性分析。因此，有必要以快速、虚拟、交互式的方式利用已部署的设备构建模型。本文的目标是开发新的几何方法，将支架或覆膜支架虚拟部署到根据医学图像 3D 分割构建的患者特定几何模型。从分割中提取代表血管内腔边界的三角形表面。患病部分要么被夹住并被展开的装置的表面取代，要么在旁路移植的情况下重新布线。对于接近分叉的患病动脉，生成分叉装置模型。还提出了一种在设备表面映射 2D 支柱图案的方法。我们通过血流计算展示了我们的方法在主动脉瘤、主动脉缩窄和冠状动脉狭窄的个性化手术计划中的三种应用。我们的方法能够实现前瞻性模型构建，并可能有助于扩大未来常规临床用途所需的吞吐量。
Image-based blood flow computation provides great promise for evaluation of vascular devices and assessment of surgical procedures. However, many previous studies employ idealized arterial and device models or only patient-specific models from the image data after device deployment, since the tools for model construction are unavailable or limited and tedious to use. Moreover, in contrast to retrospective studies from existing data, there is a pressing need for prospective analysis with the goal of surgical planning. Therefore, it is necessary to construct models with deployed devices in a fast, virtual and interactive fashion. The goal of this paper is to develop new geometric methods to deploy stents or stent grafts virtually to patient-specific geometric models constructed from a 3D segmentation of medical images. A triangular surface representing the vessel lumen boundary is extracted from the segmentation. The diseased portion is either clipped and replaced by the surface of a deployed device or rerouted in the case of a bypass graft. For diseased arteries close to bifurcations, bifurcated device models are generated. A method to map a 2D strut pattern on the surface of a device is also presented. We demonstrate three applications of our methods in personalized surgical planning for aortic aneurysms, aortic coarctation, and coronary artery stenosis using blood flow computation. Our approach enables prospective model construction and may help to expand the throughput required by routine clinical uses in the future.
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影响因子：
2.6
作者：
Figueroa, C. Alberto;Taylor, Charles A.;Zarins, Christopher K.
通讯作者：
Zarins, Christopher K.
影响因子：
3.2
作者：
Cacho, Fernando;Doblare, Manuel;Holzapfel, Gerhard A.
通讯作者：
Holzapfel, Gerhard A.
影响因子：
10.6
作者：
Antiga, L;Ene-Iordache, B;Remuzzi, A
通讯作者：
Remuzzi, A
DOI：
10.1016/j.comgeo.2006.11.009
发表时间：
2007-09-01
影响因子：
0.6
作者：
Hachenberger, Peter;Kettner, Lutz;Mehlhorn, Kurt
通讯作者：
Mehlhorn, Kurt
影响因子：
3.1
作者：
Hager, WW;Zhang, HC
通讯作者：
Zhang, HC