Diagnostic Performance of Fully Automated Pixel-Wise Quantitative Myocardial Perfusion Imaging by Cardiovascular Magnetic Resonance

The authors developed a fully automated framework to quantify myocardial blood flow (MBF) from contrast-enhanced cardiac magnetic resonance (CMR) perfusion imaging and evaluated its diagnostic performance in patients. Fully quantitative CMR perfusion pixel maps were previously validated with microsp...

Full description

Saved in:
Bibliographic Details
Published in:JACC. Cardiovascular imaging 2018-05, Vol.11 (5), p.697-707
Main Authors: Hsu, Li-Yueh, Jacobs, Matthew, Benovoy, Mitchel, Ta, Allison D., Conn, Hannah M., Winkler, Susanne, Greve, Anders M., Chen, Marcus Y., Shanbhag, Sujata M., Bandettini, W. Patricia, Arai, Andrew E.
Format: Article
Language:English
Subjects:
Automation
Blood Flow Velocity
Case-Control Studies
computer-aided diagnosis
Coronary Artery Disease - diagnostic imaging
Coronary Artery Disease - physiopathology
Coronary Circulation
Coronary Stenosis - diagnostic imaging
Coronary Stenosis - physiopathology
Humans
Image Interpretation, Computer-Assisted
image processing
magnetic resonance imaging
Magnetic Resonance Imaging - methods
myocardial blood flow
Myocardial Perfusion Imaging - methods
myocardial perfusion
Predictive Value of Tests
quantification
Reproducibility of Results
Severity of Illness Index
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The authors developed a fully automated framework to quantify myocardial blood flow (MBF) from contrast-enhanced cardiac magnetic resonance (CMR) perfusion imaging and evaluated its diagnostic performance in patients. Fully quantitative CMR perfusion pixel maps were previously validated with microsphere MBF measurements and showed potential in clinical applications, but the methods required laborious manual processes and were excessively time-consuming. CMR perfusion imaging was performed on 80 patients with known or suspected coronary artery disease (CAD) and 17 healthy volunteers. Significant CAD was defined by quantitative coronary angiography (QCA) as ≥70% stenosis. Nonsignificant CAD was defined by: 1) QCA as 
ISSN:1936-878X
1876-7591
DOI:10.1016/j.jcmg.2018.01.005