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Automated Quantification in Echocardiography.
Nolan, Mark T; Thavendiranathan, Paaladinesh.
Afiliação
  • Nolan MT; Division of Cardiology, Peter Munk Cardiac Centre, Division of Cardiology and Department of Medical Imaging, University Health Network, Toronto, Ontario, Canada.
  • Thavendiranathan P; Division of Cardiology, Peter Munk Cardiac Centre, Division of Cardiology and Department of Medical Imaging, University Health Network, Toronto, Ontario, Canada. Electronic address: dinesh.thavendiranathan@uhn.ca.
JACC Cardiovasc Imaging ; 12(6): 1073-1092, 2019 06.
Article em En | MEDLINE | ID: mdl-31171260
ABSTRACT
Echocardiography remains the predominant modality for cardiac imaging. Recent technological advances have led to the availability of new echocardiographic techniques for more accurate quantification of volumes, function, myocardial mechanics, and valvular heart disease. However, in our opinion, the real-world clinical uptake of these techniques has been poor due to limited awareness and familiarity, associated time burden, and issues of variability. Automation represents a potential solution to these issues and has already made routine myocardial strain measurements and 2- and 3-dimensional left ventricular ejection fraction measurements a clinical reality. Further enhancements in automation and data in understudied populations are likely to assist in the uptake of these new quantitative echocardiographic techniques in routine clinical practice. This review discusses current automated quantification techniques in echocardiography and their limitations and describes how these techniques can be incorporated into echocardiography laboratories.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecocardiografia / Interpretação de Imagem Assistida por Computador / Cardiopatias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecocardiografia / Interpretação de Imagem Assistida por Computador / Cardiopatias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article