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Proceedings Paper

Feasibility of determining myocardial transient ischemic dilation from cardiac CT by automated stress/rest registration
Author(s): Jonghye Woo; Piotr J. Slomka; Ryo Nakazato; Balaji K. Tamarappoo; James K. Min; Guido Germano; Daniel S. Berman; Damini Dey
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Paper Abstract

Transient ischemic dilation (TID) of the left ventricle measured by myocardial perfusion Single Photon Emission Computed Tomography (SPECT) and defined as a the ratio of stress myocardial blood volume to rest myocardial blood volume has been shown to be highly specific for detection of severe coronary artery disease. This work investigates automated quantification of TID from cardiac Computed Tomography (CT) perfusion images. To date, TID has not been computed from CT. Previous studies to compute TID have assumed accurate segmentation of the left ventricle and performed subsequent analysis of volume change mainly on static or less often on gated myocardial perfusion SPECT. This, however, may limit the accuracy of TID due to potential errors from segmentation, perfusion defects or volume measurement from both images. In this study, we propose to use registration methods to determine TID from cardiac CT scans where deformation field within the structure of interest is used to measure the local volume change between stress and rest. Promising results have been demonstrated with 7 datasets, showing the potential of this approach as a comparative method for measuring TID.

Paper Details

Date Published: 14 February 2012
PDF: 6 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83140G (14 February 2012); doi: 10.1117/12.911472
Show Author Affiliations
Jonghye Woo, Cedars-Sinai Medical Ctr. (United States)
Piotr J. Slomka, Cedars-Sinai Medical Ctr. (United States)
Univ. of California, Los Angeles (United States)
Ryo Nakazato, Cedars-Sinai Medical Ctr. (United States)
Balaji K. Tamarappoo, Cedars-Sinai Medical Ctr. (United States)
James K. Min, Cedars-Sinai Medical Ctr. (United States)
Univ. of California, Los Angeles (United States)
Guido Germano, Cedars-Sinai Medical Ctr. (United States)
Univ. of California, Los Angeles (United States)
Daniel S. Berman, Cedars-Sinai Medical Ctr. (United States)
Univ. of California, Los Angeles (United States)
Damini Dey, Cedars-Sinai Medical Ctr. (United States)
Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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