Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study

Abstract Background The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D). Methods EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study...

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發表在:	Cardiovascular Diabetology
Main Authors:	Bénédicte Gaborit, Jean Baptiste Julla, Joris Fournel, Patricia Ancel, Astrid Soghomonian, Camille Deprade, Adèle Lasbleiz, Marie Houssays, Badih Ghattas, Pierre Gascon, Maud Righini, Frédéric Matonti, Nicolas Venteclef, Louis Potier, Jean François Gautier, Noémie Resseguier, Axel Bartoli, Florian Mourre, Patrice Darmon, Alexis Jacquier, Anne Dutour
格式:	Article
語言:	英语
出版:	BMC 2024-09-01
主題:	Epicardial adipose tissue Deep learning Type 2 diabetes Cardiac computed tomography CAC score
在線閱讀:	https://doi.org/10.1186/s12933-024-02411-y