BACKGROUND: The pathophysiology of Takotsubo syndrome (TTS) remains perplexing. We developed a motion-informed neural network (MiNN-Echo) using echocardiograms to elucidate the diastolic mechanics of TTS. METHODS: We trained and validated MiNN-Echo, a deep convolutional neural network (2D+t) echocardiographic prediction model using multi-vendor echocardiograms from 1142 patients (596 TTS and 546 anterior myocardial infarction) in a multi-institutional cohort. A total of 68 expert echocardiographic readers performed human interpretation. The network’s dual-branch architecture independently learns spatial and temporal features, using 2-dimensional image frames for spatial representation and segmentation, and optical flow with sinusoidal phase encoding for temporal dynamics. The MiNN-Echo model integrates static cardiac anatomic changes with motion details from 2-dimensional echocardiographic videos to produce interpretable disease predictions. RESULTS: The MiNN-Echo model achieved an area under the curve of 0.77, compared with 0.69 among human readers in differentiating TTS from acute myocardial infarction. Myocardial motion features during diastole contributed more (≈71%) to the differential diagnosis than those during systole. Compared with patients with acute myocardial infarction, TTS patients showed increased isovolumic relaxation time (112.5 [interquartile range (IQR), 68.75–165.94] ms versus 87.5 [IQR, 54.17–140] ms, P <0.001; 28% versus 19% of diastolic time, P <0.001), decreased passive ventricular filling (before atrial contraction) time (176.04 [IQR, 114.2–248.12] ms versus 258.62 [IQR, 199.89–331.9] ms, P <0.001; 44% versus 54% of diastolic time, P <0.001), and a different mitral-annulus motion trajectory: lower pixel-wise myocardial displacement in the isovolumic relaxation (0.35 [IQR, 0.26–0.47] versus 0.38 [IQR, 0.28–0.51]; P =0.006), passive (0.45 [IQR, 0.33–0.58] versus 0.50 [IQR, 0.38–0.68]; P <0.001), and active ventricular filling (0.43 [IQR, 0.32–0.56] versus 0.48 [IQR, 0.35–0.63]; P =0.001) phases, and altered rotation angles (away from the horizontal A–V plane) in the passive ventricular filling phase (−70.19 [IQR, −89.62 to −41.33] versus −60.34 [IQR, −87.07 to −30.84]; P =0.020). CONCLUSIONS: MiNN-Echo in echocardiograms elucidates unique myocardial relaxation kinematics to characterize TTS-associated diastolic mechanics.
