Machine learning of native T1 mapping radiomics for classification of hypertrophic cardiomyopathy phenotypes

Machine learning of native T1 mapping radiomics for classification of hypertrophic cardiomyopathy phenotypes

Abstract We explored whether radiomic features from T1 maps by cardiac magnetic resonance (CMR) could enhance the diagnostic value of T1 mapping in distinguishing health from disease and classifying cardiac disease phenotypes. A total of 149 patients (n = 30 with no heart disease, n = 30 with LVH, n...

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Main Authors: Alexios S. Antonopoulos, Maria Boutsikou, Spyridon Simantiris, Andreas Angelopoulos, George Lazaros, Ioannis Panagiotopoulos, Evangelos Oikonomou, Mikela Kanoupaki, Dimitris Tousoulis, Raad H. Mohiaddin, Konstantinos Tsioufis, Charalambos Vlachopoulos
Format: Article
Language:English
Published: Nature Portfolio 2021-12-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-02971-z

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https://doi.org/10.1038/s41598-021-02971-z

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