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Abstract #4832

Fully automated 16- and 32-segmentation quantitative perfusion CMR in detection of obstructive coronary artery disease

Sonia Borodzicz-Jazdzyk1,2, Roel Hoek1, Caitlin Vink1, Luuk Hopman1, Mark Hofman3, Yvemarie Somsen1, Ruben de Winter1, Paul Knaapen1, Mitchel Benovoy4, and Marco Gotte1
1Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands, 21st Chair and Department of Cardiology,, Medical University of Warsaw, Warsaw, Poland, 3Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Amsterdam, Netherlands, 4Area19 Medical Inc, Montreal, QC, Canada

Synopsis

Keywords: Atherosclerosis, PerfusionRecently, a fully automated QP CMR workflow has been established, which provides measures of stress MBF according to a 32-segmentation model with subdivision into endo- and epicardial subsegments. We compared the diagnostic accuracy of QP CMR according to the standard AHA 16-segment model (16M-QP) and the newly developed automated 32-segment model (32M-QP) with conventional visual assessment in patients who underwent adenosine stress perfusion CMR imaging followed by invasive coronary angiography and/or coronary computed tomography angiography. Our preliminary data have not shown superiority of diagnostic accuracy of 16M-QP or 32M-QP in comparison to visual assessment of adenosine stress first-pass perfusion imaging.

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Keywords