# Synthetic Tissue Doppler Imaging

A multi-cohort external validation shows that a previously trained generative adversarial network, applied without retraining, can synthesize mitral annular tissue-Doppler velocities and displacement from a standard 12-lead ECG. Among 1,065 hospitalized acute myocardial infarction patients, synthetic e′ independently predicted all-cause mortality beyond the GRACE score; in the post-discharge subgroup it raised discrimination from a C-index of 0.67 to 0.70 and stayed independent of AI-ECG-predicted and measured ejection fraction. In 219,564 outpatients, all three parameters were associated with MI-specific mortality, with MAPSE showing the largest effect.

A multi-cohort external validation shows that a previously trained generative adversarial network, applied without retraining, can synthesize mitral annular tissue-Doppler velocities and displacement from a standard 12-lead ECG. Among 1,065 hospitalized acute myocardial infarction patients, synthetic e′ independently predicted all-cause mortality beyond the GRACE score; in the post-discharge subgroup it raised discrimination from a C-index of 0.67 to 0.70 and stayed independent of AI-ECG-predicted and measured ejection fraction. In 219,564 outpatients, all three parameters were associated with MI-specific mortality, with MAPSE showing the largest effect.