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      Myocardial tissue characterisation using echocardiographic deformation imaging

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          Abstract

          Myocardial pathology results in significant morbidity and mortality, whether due to primary cardiomyopathic processes or secondary to other conditions such as ischemic heart disease. Cardiac imaging techniques characterise the underlying tissue directly, by assessing a signal from the tissue itself, or indirectly, by inferring tissue characteristics from global or regional function. Cardiac magnetic resonance imaging is currently the most investigated imaging modality for tissue characterisation, but, due to its accessibility, advanced echocardiography represents an attractive alternative. Speckle tracking echocardiography (STE) is a reproducible technique used to assess myocardial deformation at both segmental and global levels. Since distinct myocardial pathologies affect deformation differently, information about the underlying tissue can be inferred by STE. In this review, the current available studies correlating STE deformation parameters with underlying tissue characteristics in humans are examined, with separate emphasis on global and segmental analysis. The current knowledge is placed in the context of integrated backscatter and the future of echocardiographic based tissue characterisation is discussed. The use of these imaging techniques to more precisely phenotype myocardial pathology more precisely will allow the design of translational cardiac research studies and, potentially, tailored management strategies.

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          Most cited references44

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          Standardization of left atrial, right ventricular, and right atrial deformation imaging using two-dimensional speckle tracking echocardiography: a consensus document of the EACVI/ASE/Industry Task Force to standardize deformation imaging

          The EACVI/ASE/Industry Task Force to standardize deformation imaging prepared this consensus document to standardize definitions and techniques for using two-dimensional (2D) speckle tracking echocardiography (STE) to assess left atrial, right ventricular, and right atrial myocardial deformation. This document is intended for both the technical engineering community and the clinical community at large to provide guidance on selecting the functional parameters to measure and how to measure them using 2D STE.This document aims to represent a significant step forward in the collaboration between the scientific societies and the industry since technical specifications of the software packages designed to post-process echocardiographic datasets have been agreed and shared before their actual development. Hopefully, this will lead to more clinically oriented software packages which will be better tailored to clinical needs and will allow industry to save time and resources in their development.
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            Relative apical sparing of longitudinal strain using two-dimensional speckle-tracking echocardiography is both sensitive and specific for the diagnosis of cardiac amyloidosis.

            The diagnosis of cardiac amyloidosis (CA) is challenging owing to vague symptomatology and non-specific echocardiographic findings. To describe regional patterns in longitudinal strain (LS) using two-dimensional speckle-tracking echocardiography in CA and to test the hypothesis that regional differences would help differentiate CA from other causes of increased left ventricular (LV) wall thickness. 55 consecutive patients with CA were compared with 30 control patients with LV hypertrophy (n=15 with hypertrophic cardiomyopathy, n=15 with aortic stenosis). A relative apical LS of 1.0, defined using the equation (average apical LS/(average basal LS + mid-LS)), was sensitive (93%) and specific (82%) in differentiating CA from controls (area under the curve 0.94). In a logistic regression multivariate analysis, relative apical LS was the only parameter predictive of CA (p=0.004). CA is characterised by regional variations in LS from base to apex. A relative 'apical sparing' pattern of LS is an easily recognisable, accurate and reproducible method of differentiating CA from other causes of LV hypertrophy.
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              Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography.

              Machine-learning models may aid cardiac phenotypic recognition by using features of cardiac tissue deformation.
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                Author and article information

                Contributors
                mohammed.moharram@otago.ac.nz
                regis.lamberts@otago.ac.nz
                gillian.whalley@otago.ac.nz
                michael.williams@otago.ac.nz
                +64-3-4740999 , sean.coffey@otago.ac.nz
                Journal
                Cardiovasc Ultrasound
                Cardiovasc Ultrasound
                Cardiovascular Ultrasound
                BioMed Central (London )
                1476-7120
                15 November 2019
                15 November 2019
                2019
                : 17
                : 27
                Affiliations
                [1 ]ISNI 0000 0004 1936 7830, GRID grid.29980.3a, Department of Medicine – HeartOtago, , Dunedin School of Medicine, University of Otago, ; Box 56, Dunedin, PO 9054 New Zealand
                [2 ]ISNI 0000 0004 1936 7830, GRID grid.29980.3a, Department of Physiology – HeartOtago, , School of Biomedical Sciences, University of Otago, ; Dunedin, New Zealand
                Author information
                http://orcid.org/0000-0003-2312-4666
                Article
                176
                10.1186/s12947-019-0176-9
                6858720
                31730467
                3a008f4c-069c-46e6-ae87-1436295a7829
                © The Author(s). 2019

                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. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 April 2019
                : 6 November 2019
                Funding
                Funded by: Department of Medicine, University of Otago
                Award ID: Tony Hocken Scholarship
                Award Recipient :
                Categories
                Review
                Custom metadata
                © The Author(s) 2019

                Cardiovascular Medicine
                echocardiography,strain,speckle tracking,fibrosis,myocardial histology
                Cardiovascular Medicine
                echocardiography, strain, speckle tracking, fibrosis, myocardial histology

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