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      The role of left ventricular deformation in the assessment of microvascular obstruction and intramyocardial haemorrhage

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          Abstract

          In the setting of acute ST-elevation myocardial infarction (STEMI), it remains unclear which strain parameter most strongly correlates with microvascular obstruction (MVO) or intramyocardial haemorrhage (IMH). We aimed to investigate the association of MVO, IMH and convalescent left ventricular (LV) remodelling with strain parameters measured with cardiovascular magnetic resonance (CMR). Forty-three patients with reperfused STEMI and 10 age and gender matched healthy controls underwent CMR within 3-days and at 3-months following reperfused STEMI. Cine, T2-weighted, T2*-imaging and late gadolinium enhancement (LGE) imaging were performed. Infarct size, MVO and IMH were quantified. Peak global longitudinal strain (GLS), global radial strain (GRS), global circumferential strain (GCS) and their strain rates were derived by feature tracking analysis of LV short-axis, 4-chamber and 2-chamber cines. All 43 patients and ten controls completed the baseline scan and 34 patients completed 3-month scans. In multivariate regression, GLS demonstrated the strongest association with MVO or IMH (beta = 0.53, p < 0.001). The optimal cut-off value for GLS was −13.7% for the detection of MVO or IMH (sensitivity 76% and specificity 77.8%). At follow up, 17% (n = 6) of patients had adverse LV remodeling (defined as an absolute increase of LV end-diastolic/end-systolic volumes >20%). Baseline GLS also demonstrated the strongest diagnostic performance in predicting adverse LV remodelling (AUC = 0.79; 95% CI 0.60–0.98; p = 0.03). Post-reperfused STEMI, baseline GLS was most closely associated with the presence of MVO or IMH. Baseline GLS was more strongly associated with adverse LV remodelling than other CMR parameters.

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          Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection.

          The receiver operating characteristic (ROC) curve is used to evaluate a biomarker's ability for classifying disease status. The Youden Index (J), the maximum potential effectiveness of a biomarker, is a common summary measure of the ROC curve. In biomarker development, levels may be unquantifiable below a limit of detection (LOD) and missing from the overall dataset. Disregarding these observations may negatively bias the ROC curve and thus J. Several correction methods have been suggested for mean estimation and testing; however, little has been written about the ROC curve or its summary measures. We adapt non-parametric (empirical) and semi-parametric (ROC-GLM [generalized linear model]) methods and propose parametric methods (maximum likelihood (ML)) to estimate J and the optimal cut-point (c *) for a biomarker affected by a LOD. We develop unbiased estimators of J and c * via ML for normally and gamma distributed biomarkers. Alpha level confidence intervals are proposed using delta and bootstrap methods for the ML, semi-parametric, and non-parametric approaches respectively. Simulation studies are conducted over a range of distributional scenarios and sample sizes evaluating estimators' bias, root-mean square error, and coverage probability; the average bias was less than one percent for ML and GLM methods across scenarios and decreases with increased sample size. An example using polychlorinated biphenyl levels to classify women with and without endometriosis illustrates the potential benefits of these methods. We address the limitations and usefulness of each method in order to give researchers guidance in constructing appropriate estimates of biomarkers' true discriminating capabilities. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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            Treatment of myocardial infarction in a coronary care unit. A two year experience with 250 patients.

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              Principles of cardiovascular magnetic resonance feature tracking and echocardiographic speckle tracking for informed clinical use

              Tissue tracking technology of routinely acquired cardiovascular magnetic resonance (CMR) cine acquisitions has increased the apparent ease and availability of non-invasive assessments of myocardial deformation in clinical research and practice. Its widespread availability thanks to the fact that this technology can in principle be applied on images that are part of every CMR or echocardiographic protocol. However, the two modalities are based on very different methods of image acquisition and reconstruction, each with their respective strengths and limitations. The image tracking methods applied are not necessarily directly comparable between the modalities, or with those based on dedicated CMR acquisitions for strain measurement such as tagging or displacement encoding. Here we describe the principles underlying the image tracking methods for CMR and echocardiography, and the translation of the resulting tracking estimates into parameters suited to describe myocardial mechanics. Technical limitations are presented with the objective of suggesting potential solutions that may allow informed and appropriate use in clinical applications.
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                Author and article information

                Contributors
                + 44 113 3437720 , S.Plein@leeds.ac.uk
                Journal
                Int J Cardiovasc Imaging
                Int J Cardiovasc Imaging
                The International Journal of Cardiovascular Imaging
                Springer Netherlands (Dordrecht )
                1569-5794
                1875-8312
                26 October 2016
                26 October 2016
                2017
                : 33
                : 3
                : 361-370
                Affiliations
                [1 ]ISNI 0000 0004 1936 8403, GRID grid.9909.9, Multidisciplinary Cardiovascular Research Centre and Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, , University of Leeds, ; Leeds, UK
                [2 ]GRID grid.410567.1, Department of Cardiology and Cardiovascular Research Institute Basel (CRIB), , University Hospital Basel, ; Basel, Switzerland
                Author information
                http://orcid.org/0000-0002-5483-169X
                Article
                1006
                10.1007/s10554-016-1006-x
                5344946
                27785677
                3709ef20-e6e4-4247-bab7-03217ff860b0
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), 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.

                History
                : 25 August 2016
                : 20 October 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation;
                Award ID: FS/1062/28409
                Award Recipient :
                Categories
                Original Paper
                Custom metadata
                © Springer Science+Business Media Dordrecht 2017

                Cardiovascular Medicine
                haemorrhage,cardiovascular magnetic resonance,myocardial infarction,left ventricular function

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