Paper
24 July 1998 Computed rotational angiography: system performance assessment using in-vitro and in-vivo models
Rebecca Fahrig, David W. Holdsworth, Stephen P. Lownie, Allan J. Fox
Author Affiliations +
Abstract
Problems in visualizing the complex anatomy of the cerebral vasculature during intravascular embolization therapy remain due to the two-dimensional nature of digital subtration angiography. We describe the characterization of a three- dimensional (3-D) imaging technique, Computed Rotational Angiography (CRA). Projection images were acquired by rotating a modified Siemens Multistar Angiographic prototype system (C- arm mounted XRII) around the object, resulting in approximately 130 images over 200 degrees in less than 5 s. Exposure time is less than 20 ms/frame; tube voltage ranges from 73 - 110 kVp; tube current ranges from 100 - 500 mA. In vitro resolution was tested using both small area (line patterns) and large area (beads) phantoms. Investigations using in vivo porcine models examined SNR in the presence of physiological flow conditions. Limiting high-contrast resolution was better than 6.2 lp/cm. Reconstruction of the large area phantom demonstrated uniform image quality. A comparison of model and measured SNR showed good agreement for low dose but significant difference for high dose reconstructions. SNR was 60 in multi-planar reformatted slices, and 140 in the maximum intensity projection through the same volume. In conclusion, the CRA technique we describe, -- combined with recent advances in computing hardware -- make the presentation of 3-D volumes in under 5 minutes during interventional procedures a very real possibility.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rebecca Fahrig, David W. Holdsworth, Stephen P. Lownie, and Allan J. Fox "Computed rotational angiography: system performance assessment using in-vitro and in-vivo models", Proc. SPIE 3336, Medical Imaging 1998: Physics of Medical Imaging, (24 July 1998); https://doi.org/10.1117/12.317030
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Cited by 4 scholarly publications.
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KEYWORDS
Signal to noise ratio

Reconstruction algorithms

Angiography

3D image reconstruction

3D image processing

Data acquisition

In vivo imaging

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