Image-based computational fluid dynamics provides great promise for evaluation of vascular devices and assessment of surgical procedures. However, many previous studies employ idealized arterial and device models or patient-specific models with a limited number of cases, since the model construction process is tedious and time-consuming. Moreover, in contrast to retrospective studies from existing image data, there is a pressing need of prospective analysis with the goal of surgical planning. Therefore, it is necessary to construct models with implanted devices in a fast, virtual and interactive fashion. The goal of this paper is to develop new geometric methods to deploy stent grafts virtually to patient-specific models constructed from direct 3D segmentation of medical images. A triangular surface representing vessel lumen boundary is extracted from the segmentation. The diseased portion is then clipped and replaced by the surface of a virtual stent graft following the centerline obtained from the clipped portion. A Y-shape stent graft is employed in case of bifurcated arteries. A method to map a 2D strut pattern on the stent graft is also presented. We demonstrate the application of our methods to quantify wall shear stresses and forces acting on stent grafts in personalized surgical planning for endovascular treatment of thoracic and abdominal aortic aneurysms. Our approach enables prospective model construction and may help to increase its throughput required by routine clinical uses in the future. © 2010 Springer-Verlag.
CITATION STYLE
Xiong, G., & Taylor, C. A. (2010). Virtual stent grafting in personalized surgical planning for treatment of aortic aneurysms using image-based computational fluid dynamics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6363 LNCS, pp. 375–382). https://doi.org/10.1007/978-3-642-15711-0_47
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