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Aligning Coronary Anatomy and Myocardial Perfusion Territories

Authors :
Wei Guo
Richard T. George
Marcelo F. Di Carli
Julie M. Miller
Kihei Yoneyama
Armin Arbab-Zadeh
Joao A.C. Lima
Courtney Foster
Christopher Cox
Rodrigo Cerci
Vishal C. Mehra
Jeffrey A. Brinker
Andrea L. Vavere
John H. Texter
Source :
Circulation: Cardiovascular Imaging. 5:587-595
Publication Year :
2012
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2012.

Abstract

Background— Appropriate clinical decisions concerning diagnosis and treatment of coronary artery disease rely on correct integration of data on coronary anatomy and myocardial perfusion. The purpose of this article is to introduce a new left ventricular segmentation model for improved alignment of coronary arterial segments and myocardial perfusion territories, designed for the CORE320 study. Methods and Results— CORE320 is a prospective, multicenter study with a primary objective to evaluate the diagnostic accuracy of 320-row detector computed tomography (CT) to detect coronary artery luminal stenosis and corresponding myocardial perfusion deficits in patients with suspected coronary artery disease compared with the gold standard of conventional coronary angiography and single-photon emission CT myocardial perfusion imaging. We describe a 19-coronary segment and 13-myocardial territory alignment model, its application in both standard and CT image data sets, and the adjudication process of the initial cohort of patients recruited for the CORE320 study. Adjudication committees reviewed the images of the first 101 gold standard and 107 CT data sets. On the basis of the presented model and rules, all cases for adjudication were correctly identified. During image review, 6 (5.9%) gold standard and 9 (8.4%) CT data sets needed further realignment not triggered by the algorithm. Conclusions— We present a vascular territory distribution model developed for the CORE320 multicenter study, which accounts for variability in coronary anatomy and potential myocardial perfusion territory overlap. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00934037.

Details

ISSN :
19420080 and 19419651
Volume :
5
Database :
OpenAIRE
Journal :
Circulation: Cardiovascular Imaging
Accession number :
edsair.doi.dedup.....065dd807d7c77659ad9497ab9a0be9bf
Full Text :
https://doi.org/10.1161/circimaging.111.970608