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Novelties in 3D Transthoracic Echocardiography

Cardiovascular imaging is developing at a rapid pace and the newer modalities, in particular three-dimensional echocardiography, allow better analysis of heart structures. Identifying valve lesions and grading their severity represents crucial information and nowadays is strengthened by the introduc...

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Autores principales: Italiano, Gianpiero, Fusini, Laura, Mantegazza, Valentina, Tamborini, Gloria, Muratori, Manuela, Ghulam Ali, Sarah, Penso, Marco, Garlaschè, Anna, Gripari, Paola, Pepi, Mauro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865963/
https://www.ncbi.nlm.nih.gov/pubmed/33494387
http://dx.doi.org/10.3390/jcm10030408
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author Italiano, Gianpiero
Fusini, Laura
Mantegazza, Valentina
Tamborini, Gloria
Muratori, Manuela
Ghulam Ali, Sarah
Penso, Marco
Garlaschè, Anna
Gripari, Paola
Pepi, Mauro
author_facet Italiano, Gianpiero
Fusini, Laura
Mantegazza, Valentina
Tamborini, Gloria
Muratori, Manuela
Ghulam Ali, Sarah
Penso, Marco
Garlaschè, Anna
Gripari, Paola
Pepi, Mauro
author_sort Italiano, Gianpiero
collection PubMed
description Cardiovascular imaging is developing at a rapid pace and the newer modalities, in particular three-dimensional echocardiography, allow better analysis of heart structures. Identifying valve lesions and grading their severity represents crucial information and nowadays is strengthened by the introduction of new software, such as transillumination, which provide detailed morphology descriptions. Chambers quantification has never been so rapid and accurate: machine learning algorithms generate automated volume measurements, including left ventricular systolic and diastolic function, which is extremely important for clinical decisions. This review provides an overview of the latest innovations in the echocardiography field, and is helpful by providing a better insight into heart diseases.
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spelling pubmed-78659632021-02-07 Novelties in 3D Transthoracic Echocardiography Italiano, Gianpiero Fusini, Laura Mantegazza, Valentina Tamborini, Gloria Muratori, Manuela Ghulam Ali, Sarah Penso, Marco Garlaschè, Anna Gripari, Paola Pepi, Mauro J Clin Med Review Cardiovascular imaging is developing at a rapid pace and the newer modalities, in particular three-dimensional echocardiography, allow better analysis of heart structures. Identifying valve lesions and grading their severity represents crucial information and nowadays is strengthened by the introduction of new software, such as transillumination, which provide detailed morphology descriptions. Chambers quantification has never been so rapid and accurate: machine learning algorithms generate automated volume measurements, including left ventricular systolic and diastolic function, which is extremely important for clinical decisions. This review provides an overview of the latest innovations in the echocardiography field, and is helpful by providing a better insight into heart diseases. MDPI 2021-01-21 /pmc/articles/PMC7865963/ /pubmed/33494387 http://dx.doi.org/10.3390/jcm10030408 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Italiano, Gianpiero
Fusini, Laura
Mantegazza, Valentina
Tamborini, Gloria
Muratori, Manuela
Ghulam Ali, Sarah
Penso, Marco
Garlaschè, Anna
Gripari, Paola
Pepi, Mauro
Novelties in 3D Transthoracic Echocardiography
title Novelties in 3D Transthoracic Echocardiography
title_full Novelties in 3D Transthoracic Echocardiography
title_fullStr Novelties in 3D Transthoracic Echocardiography
title_full_unstemmed Novelties in 3D Transthoracic Echocardiography
title_short Novelties in 3D Transthoracic Echocardiography
title_sort novelties in 3d transthoracic echocardiography
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865963/
https://www.ncbi.nlm.nih.gov/pubmed/33494387
http://dx.doi.org/10.3390/jcm10030408
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