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Proceedings Paper

Modified distance-density methods for instantaneous angiographic blood-flow measurement
Author(s): Simon D. Shpilfoygel; Robert A. Close; Reza Jahan; Gary R. Duckwiler M.D.; Daniel J. Valentino
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Paper Abstract

Blood flow rate is an important parameter for functional evaluation of vascular disease. Instantaneous blood flow measurements from digital cerebral angiograms can be performed during endovascular interventional procedures providing interventional radiologists with minimally invasive real-time flow measurements. Distance-density curve matching (DDCM) methods are a promising class of videodensitometric techniques. However, published techniques have a relatively low theoretical maximum of measurable flow rate and sensitivity to noise and image artifacts. We investigate the use of alternative difference metrics along with curve fitting and extrapolation. These modifications can potentially reduce the influence of noise, image defects and flow irregularities. Extrapolation of difference profiles may overcome the theoretical limit for maximum measurable flow rate. The proposed methods were evaluated using both simulated angiograms and angiograms obtained by imaging a flow phantom under clinically realistic flow and contrast injection conditions. Our results indicate that under the conditions of constant flow the proposed modifications yield some improvement in both accuracy and reliability of instantaneous flow rate measurements. These improvements were the most noticeable during the early contrast wash-out phase, when the published DDCM methods were observed to fail.

Paper Details

Date Published: 3 July 1998
PDF: 11 pages
Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); doi: 10.1117/12.312569
Show Author Affiliations
Simon D. Shpilfoygel, UCLA School of Medicine (United States)
Robert A. Close, Cedars-Sinai Medical Ctr. (United States)
Reza Jahan, UCLA School of Medicine (United States)
Gary R. Duckwiler M.D., UCLA School of Medicine (United States)
Daniel J. Valentino, UCLA School of Medicine (United States)


Published in SPIE Proceedings Vol. 3337:
Medical Imaging 1998: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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