Takotsubo Syndrome - Predictable from brain imaging data

Abstract

Takotsubo syndrome (TTS) is characterized by acute left ventricular dysfunction, with a hospital-mortality rate similar to acute coronary syndrome (ACS). However, the aetiology of TTS is still unknown. In the present study, a multivariate pattern analysis using machine learning with multimodal magnetic resonance imaging (MRI) data of the human brain of TTS patients and age- and gender-matched healthy control subjects was performed. We found consistent structural and functional alterations in TTS patients compared to the control group. In particular, anatomical and neurophysiological measures from brain regions constituting the emotional-autonomic control system contributed to a prediction accuracy of more than 82%. Thus, our findings demonstrate homogeneous neuronal alterations in TTS patients and substantiate the importance of the concept of a brain-heart interaction in TTS.

Figure 1

Model weights (colour bar) obtained with the support vector machine algorithm displayed for the brain regions with the highest weights for group classification based on FA (averaged across all cross-validation folds): Left parahippocampal gyrus (A), left paracentral lobe (B), left amygdala (C), right paracentral lobe (D), left hippocampus (E), left (F) and right (G) supplementary motor areal, right precentral gyrus (H), left fusiform gyrus (I), and right parahippocampal gyrus (J).

Figure 2

Prediction values (A) and the Receiver Operating Characteristic (ROC) curve (B) of group classification based on FA (averaged across all folds).