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Proceedings Paper

3D reconstruction of microvascular flow phantoms with hybrid imaging modalities
Author(s): Jingying Lin; Kevin Hsiung; Russell Ritenour; Jafar Golzarian
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Paper Abstract

Microvascular flow phantoms were built to aid the development of a hemodynamic simulation model for treating hepatocelluar carcinoma. The goal is to predict the blood flow routing for embolotherapy planning. Embolization is to deliver agents (e.g. microspheres) to the vicinity of the tumor to obstruct blood supply and nutrients to the tumor, targeting into 30 - 40 μm arterioles. Due to the size of the catheter, it has to release microspheres at an upper stream location, which may not localize the blocking effect. Accurate anatomical descriptions of microvasculature will help to conduct a reliable simulation and prepare a successful embolization strategy. Modern imaging devices can generate 3D reconstructions with ease. However, with a fixed detector size, larger field of view yields lower resolution. Clinical CT images can't be used to measure micro vessel dimensions, while micro-CT requires more acquisitions to reconstruct larger vessels. A multi-tiered, montage 3D reconstruction method with hybrid-modality imagery is devised to minimize the reconstruction effort. Regular CT is used for larger vessels and micro-CT is used for micro vessels. The montage approach aims to stitch up images with different resolutions and orientations. A resolution-adaptable 3D image registration is developed to assemble the images. We have created vessel phantoms that consist of several tiers of bifurcating polymer tubes in reducing diameters, down to 25 μm. No previous work of physical flow phantom has ventured into this small scale. Overlapping phantom images acquired from clinical CT and micro-CT are used to verify the image registration fidelity.

Paper Details

Date Published: 1 March 2011
PDF: 7 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79642H (1 March 2011); doi: 10.1117/12.878205
Show Author Affiliations
Jingying Lin, Univ. of Minnesota (United States)
Kevin Hsiung, Univ. of Minnesota (United States)
Russell Ritenour, Univ. of Minnesota (United States)
Jafar Golzarian, Univ. of Minnesota (United States)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes, Editor(s)

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