Quantitative Myocardial Perfusion Imaging Versus Visual Analysis in Diagnosing Myocardial Ischemia: A CE-MARC Substudy

JACC. Cardiovascular Imaging
John D BiglandsJohn P Greenwood

Abstract

This study sought to compare the diagnostic accuracy of visual and quantitative analyses of myocardial perfusion cardiovascular magnetic resonance against a reference standard of quantitative coronary angiography. Visual analysis of perfusion cardiovascular magnetic resonance studies for assessing myocardial perfusion has been shown to have high diagnostic accuracy for coronary artery disease. However, only a few small studies have assessed the diagnostic accuracy of quantitative myocardial perfusion. This retrospective study included 128 patients randomly selected from the CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) study population such that the distribution of risk factors and disease status was proportionate to the full population. Visual analysis results of cardiovascular magnetic resonance perfusion images, by consensus of 2 expert readers, were taken from the original study reports. Quantitative myocardial blood flow estimates were obtained using Fermi-constrained deconvolution. The reference standard for myocardial ischemia was a quantitative coronary x-ray angiogram stenosis severity of ≥70% diameter in any coronary artery of >2 mm diameter, or ≥50% in the left main stem. Diagn...Continue Reading

Citations

Sep 2, 2019·Current Treatment Options in Cardiovascular Medicine·Peter D Filev, Arthur E Stillman
May 20, 2020·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Xenios MilidonisAmedeo Chiribiri
Feb 26, 2020·Nature Reviews. Cardiology·Marc DeweyUNKNOWN Quantitative Cardiac Imaging Study Group
Dec 15, 2020·European Heart Journal Cardiovascular Imaging·Marine KinnelJérôme Garot
Jun 11, 2021·Magnetic Resonance in Medical Sciences : MRMS : an Official Journal of Japan Society of Magnetic Resonance in Medicine·Hajime Sakuma, Masaki Ishida

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