Alan C Kwan, Ernest W Chang, Ishan Jain, John Theurer, Xiu Tang, Nadia Francisco, Francois Haddad, David Liang, Alexandra Fábián, Andrea Ferencz, Neal Yuan, Béla Merkely, Robert Siegel, Susan Cheng, Attila Kovács, Márton Tokodi, David Ouyang
BACKGROUND: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GLS) from standard echocardiography B-mode images would greatly improve post hoc research applications and may streamline patient analyses. OBJECTIVES: This study was seeking to develop an automated deep learning strain (DLS) analysis pipeline and validate its performance across multiple applications and populations...
March 12, 2024: JACC. Cardiovascular Imaging