Clinical implications of exercise‐induced regional wall motion abnormalities in significant aortic regurgitation
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DOI: 10.1111/echo.14855
Abstract: Significant aortic regurgitation (AR) is sometimes accompanied by regional wall motion abnormalities (RWMA) during exercise stress echocardiography. The aim of this study was to estimate the association between RWMA after exercise and in the presence… read more here.
Keywords: wall motion; regional wall; aortic regurgitation; significant aortic ... See more keywords
Four‐dimensional quantification on left atrial volume‐strain in coronary heart disease patients without regional wall motion abnormalities: Correlation with the severity of coronary stenosis
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DOI: 10.1111/echo.15355
Abstract: Echocardiography is a time and cost‐effective imaging modality, providing evidence of myocardial ischemia by detecting the regional wall motion abnormalities (RWMA). However, quite a few coronary heart disease (CHD) patients do not present RWMA. The… read more here.
Keywords: heart disease; disease; coronary heart; regional wall ... See more keywords
Deep learning automates detection of wall motion abnormalities via measurement of longitudinal strain from ECG-gated CT images
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DOI: 10.3389/fcvm.2022.1009445
Abstract: Introduction 4D cardiac CT (cineCT) is increasingly used to evaluate cardiac dynamics. While echocardiography and CMR have demonstrated the utility of longitudinal strain (LS) measures, measuring LS from cineCT currently requires reformatting the 4D dataset… read more here.
Keywords: long axis; longitudinal strain; deep learning; wall motion ... See more keywords
Echocardiography-based AI detection of regional wall motion abnormalities and quantification of cardiac function in myocardial infarction
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DOI: 10.3389/fcvm.2022.903660
Abstract: Objective To compare the performance of a newly developed deep learning (DL) framework for automatic detection of regional wall motion abnormalities (RWMAs) for patients presenting with the suspicion of myocardial infarction from echocardiograms obtained with… read more here.
Keywords: cardiac function; quantification cardiac; detection; wall motion ... See more keywords
Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning
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DOI: 10.3389/fcvm.2022.919751
Abstract: Background The presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent indicator of adverse cardiovascular events in patients with cardiovascular diseases. We develop and evaluate the ability to detect cardiac wall motion… read more here.
Keywords: motion abnormalities; volume rendering; wall motion; volume ... See more keywords