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Automated deep learning quantification of epicardial adiposity on cardiac CT predicts atrial fibrillation risk immediately following cardiac surgery and long-term

26 August 2022 (08:00 - 19:30)
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Congress Presentation Part of: Epicardial fat, coronary atherosclerosis and beyond Coronary Computed Tomography Angiography (Coronary CTA, CCTA) ESC Professional Premium Access ESC Congress 2022

About the speaker

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Doctor Henry West

University of Oxford, Oxford (United Kingdom of Great Britain & Northern Ireland)

5 More presentations in this session

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Clinical impact of novel pericoronary adipose tissue measurement on ECG-gated non-contrast chest CT scan
Doctor D. Takahashi (Hongo, Bunkyo-ku, Tokyo, JP)
Abstract Slides
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Epicardial and pericoronary fat volume and attenuation, lipid lowering therapy and coronary high risk coronary plaque burden
Doctor B. Balcer (Essen, DE)
Abstract Slides
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Influence of gender on coronary atherosclerosis and inflammatory biomarker profile: A CT angiographic study
Assistant Professor D. Bittner (Augsburg, DE)
Abstract Slides
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Coronary artery stenosis and vulnerable plaque quantification on CCTA by deep learning methods
Doctor A. He (Perth, AU)
Abstract Slides
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Coronary computed tomography angiography based endothelial wall shear stress in normal coronary arteries
Doctor J. Schultz (Turku, FI)
Abstract Slides

Access the full session

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Epicardial fat, coronary atherosclerosis and beyond

The Event

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ESC Congress 2022

26 August - 29 August 2022

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources