AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging

AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging

Abstract Epicardial adipose tissue (EAT) volume and attenuation are associated with cardiovascular risk, but manual annotation is time-consuming. We evaluated whether automated deep learning-based EAT measurements from ungated computed tomography (CT) are associated with death or myocardial infarcti...

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Bibliographic Details
Main Authors: Robert J. H. Miller, Aakash Shanbhag, Aditya Killekar, Mark Lemley, Bryan Bednarski, Serge D. Van Kriekinge, Paul B. Kavanagh, Attila Feher, Edward J. Miller, Andrew J. Einstein, Terrence D. Ruddy, Joanna X. Liang, Valerie Builoff, Daniel S. Berman, Damini Dey, Piotr J. Slomka
Format: Article
Language:English
Published: Nature Portfolio 2024-02-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-024-01020-z

Internet

https://doi.org/10.1038/s41746-024-01020-z

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