Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models

Abstract

Sudden cardiac death (SCD) from arrhythmias is a leading cause of mortality. For patients at high SCD risk, prophylactic insertion of implantable cardioverter defibrillators (ICDs) reduces mortality. Current approaches to identify patients at risk for arrhythmia are, however, of low sensitivity and specificity, which results in a low rate of appropriate ICD therapy. Here, we develop a personalized approach to assess SCD risk in post-infarction patients based on cardiac imaging and computational modelling. We construct personalized three-dimensional computer models of post-infarction hearts from patients' clinical magnetic resonance imaging data and assess the propensity of each model to develop arrhythmia. In a proof-of-concept retrospective study, the virtual heart test significantly outperformed several existing clinical metrics in predicting future arrhythmic events. The robust and non-invasive personalized virtual heart risk assessment may have the potential to prevent SCD and avoid unnecessary ICD implantations.

Optogenetic defibrillation terminates ventricular arrhythmia in mouse hearts and human simulations

“…Our analysis revealed simultaneous transmural excitation upon illumination, followed by strong diastolic depolarization (~−40 mV) that affected all layers ( Figure 5B) and completely abrogated Na + channel excitability, even in the endocardial layer ( Figure 5C). Therefore, action potential initiation during illumination became purely Ca 2+ current-dependent ( Figure 5C), resulting in a critical decrease in strated the in silico approach to simulate this type of arrhythmia and its predictive power and clinical relevance, by predicting, with high accuracy and reliability, postinfarction risk of sudden cardiac death in a cohort of 41 patients (27). Here, in contrast to our recent modeling of optogenetic defibrillation in structurally normal ventricles (16), we exclusively illuminated the epicardial surface.…”

Myocardial Scar Delineation Using Diffusion Tensor Magnetic Resonance Tractography

“…The integration of DTI and electroanatomic mapping has historically been impeded by the limited availability of in vivo DTI data. Consequently, elegant computational approaches have been developed to integrate electroanatomic data with microstructural atlases of the heart 32. In a clinical setting, the incorporation of LGE into risk models for sudden cardiac death may improve their accuracy by providing an assessment of the arrhythmic substrate 42, 43.…”

Surface Mesh Reconstruction from Cardiac MRI Contours

“…The SSM was fitted to the segmented contours, applying Equation (1). In doing so, we obtained the set of parameters b and transformation T that allowed us to generate the closest possible shape matching the provided contours.…”

“…In recent years, much research has looked at creating personalised 3D anatomical models of the heart [1][2][3][4]. These models usually incorporate a geometrical reconstruction of the anatomy in order to understand better cardiovascular functions as well as predict different processes after a clinical event.…”