Imaging-based simulations for predicting sudden death and guiding ablation
Simulation-driven engineering has put rockets in space, aeroplanes in the sky, and self-driving cars on the road. Computational approaches, however, have rarely been applied to human health. In the arena of cardiac care, this reality is slowly changing. The recent emphasis on personalised medicine has provided a significant impetus for the development of predictive approaches combining clinical imaging and computational modelling that can be applied to the diagnosis and treatment of heart rhythm disorders.
A major avenue in this direction is the creation and translation into clinical practice of novel imaging- and simulation-based strategies for predicting an individual’s risk of sudden cardiac death (SCD) and for the non-invasive planning of optimal personalized anti-arrhythmia therapies. Clinical decisions regarding the stratification of patients for SCD risk resulting from arrhythmia and for determining the optimal targets for anti-arrhythmia ablation therapies could greatly benefit from such targeted developments, since current approaches, although life-saving, remain often sub-optimal.