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      Fully quantitative cardiovascular magnetic resonance myocardial perfusion ready for clinical use: a comparison between cardiovascular magnetic resonance imaging and positron emission tomography

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          Recent studies have shown that quantification of myocardial perfusion (MP) at stress and myocardial perfusion reserve (MPR) offer additional diagnostic and prognostic information compared to qualitative and semi-quantitative assessment of myocardial perfusion distribution in patients with coronary artery disease (CAD). Technical advancements have enabled fully automatic quantification of MP using cardiovascular magnetic resonance (CMR) to be performed in-line in a clinical workflow. The aim of this study was to validate the use of the automated CMR perfusion mapping technique for quantification of MP using 13N–NH3 cardiac positron emission tomography (PET) as the reference method.


          Twenty-one patients with stable CAD were included in the study. All patients underwent adenosine stress and rest perfusion imaging with 13N–NH3 PET and a dual sequence, single contrast bolus CMR on the same day. Global and regional MP were quantified both at stress and rest using PET and CMR.


          There was good agreement between global MP quantified by PET and CMR both at stress (−0.1 ± 0.5 ml/min/g) and at rest (0 ± 0.2 ml/min/g) with a strong correlation ( r = 0.92, p < 0.001; y = 0.94× + 0.14). Furthermore, there was strong correlation between CMR and PET with regards to regional MP ( r = 0.83, p < 0.001; y = 0.87× + 0.26) with a good agreement (−0.1 ± 0.6 ml/min/g). There was also a significant correlation between CMR and PET with regard to global and regional MPR ( r = 0.69, p = 0.001 and r = 0.57, p < 0.001, respectively).


          There is good agreement between MP quantified by 13N–NH3 PET and dual sequence, single contrast bolus CMR in patients with stable CAD. Thus, CMR is viable in clinical practice for quantification of MP.

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          Most cited references 26

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          Incremental prognostic value of myocardial perfusion single photon emission computed tomography for the prediction of cardiac death: differential stratification for risk of cardiac death and myocardial infarction.

          The incremental prognostic value of stress single photon emission computed tomography (SPECT) for the prediction of cardiac death as an individual end point and the implications for risk stratification are undefined. We identified 5183 consecutive patients who underwent stress/rest SPECT and were followed up for the occurrence of cardiac death or myocardial infarction. Over a mean follow up of 642+/-226 days, 119 cardiac deaths and 158 myocardial infarctions occurred (3.0% cardiac death rate, 2.3% myocardial infarction rate). Patients with normal scans were at low risk (< or =0.5%/y), and rates of both outcomes increased significantly with worsening scan abnormalities. Patients who underwent exercise stress and had mildly abnormal scans had low rates of cardiac death but higher rates of myocardial infarction (0.7%/y versus 2.6%/y; P<.05). After adjustment for prescan information, scan results provided incremental prognostic value toward the prediction of cardiac death. The identification of patients at intermediate risk of nonfatal myocardial infarction and low risk for cardiac death by SPECT may result in significant cost savings when applied to a clinical testing strategy. Myocardial perfusion SPECT yields incremental prognostic information toward the identification of cardiac death. Patients with mildly abnormal scans after exercise stress are at low risk for cardiac death but intermediate risk for nonfatal myocardial infarction and thus may benefit from a noninvasive strategy and may not require invasive management.
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            Gadgetron: an open source framework for medical image reconstruction.

            This work presents a new open source framework for medical image reconstruction called the "Gadgetron." The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or "Gadgets" from raw data to reconstructed images. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without recompiling the basic framework infrastructure. Gadgets are typically implemented in C/C++, but the framework includes wrapper Gadgets that allow the user to implement new modules in the Python scripting language for rapid prototyping. In addition to the streaming framework infrastructure, the Gadgetron comes with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its application to Cartesian and non-Cartesian parallel magnetic resonance imaging. Copyright © 2012 Wiley Periodicals, Inc.
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              Prognosis of negative adenosine stress magnetic resonance in patients presenting to an emergency department with chest pain.

              This study was designed to determine the diagnostic value of adenosine cardiac magnetic resonance (CMR) in troponin-negative patients with chest pain. We hypothesized that adenosine CMR could determine which troponin-negative patients with chest pain in an emergency department have coronary artery disease (CAD) or future adverse cardiac events. Adenosine stress CMR was performed on 135 patients who presented to the emergency department with chest pain and had acute myocardial infarction (MI) excluded by troponin-I. The main study outcome was detecting any evidence of significant CAD. Patients were contacted at one year to determine the incidence of significant CAD defined as coronary artery stenosis >50% on angiography, abnormal correlative stress test, new MI, or death. Adenosine perfusion abnormalities had 100% sensitivity and 93% specificity as the single most accurate component of the CMR examination. Both cardiac risk factors and CMR were significant in Kaplan-Meier analysis (log-rank test, p = 0.0006 and p < 0.0001, respectively). However, an abnormal CMR added significant prognostic value in predicting future diagnosis of CAD, MI, or death over clinical risk factors. In receiver operator curve analysis, adenosine CMR was a more accurate predictor than cardiac risk factors (p < 0.002). In patients with chest pain who had MI excluded by troponin-I and non-diagnostic electrocardiograms, an adenosine CMR examination predicted with high sensitivity and specificity which patients had significant CAD during one-year follow-up. Furthermore, no patients with a normal adenosine CMR study had a subsequent diagnosis of CAD or an adverse outcome.

                Author and article information

                +46 46 173328 ,
                J Cardiovasc Magn Reson
                J Cardiovasc Magn Reson
                Journal of Cardiovascular Magnetic Resonance
                BioMed Central (London )
                19 October 2017
                19 October 2017
                : 19
                [1 ]ISNI 0000 0001 0930 2361, GRID grid.4514.4, Department of Clinical Physiology, , Clinical Sciences, Lund University and Lund University Hospital, ; Lund, Sweden
                [2 ]ISNI 0000 0001 2297 5165, GRID grid.94365.3d, National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, ; 10 Center Drive, Bethesda, MD 20892 USA
                [3 ]GRID grid.411843.b, Department of Radiation Physics, , Lund University Hospital, ; Lund, Sweden
                [4 ]ISNI 0000000109457005, GRID grid.4793.9, Laboratory of Computing, Medical Informatics and Biomedical – Imaging Technologies, , School of Medicine, Aristotle University of Thessaloniki, ; Thessaloniki, Greece
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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