In our latest paper we start to unravel the mechanisms of "unexplained" sudden cardiac arrest. Referral link for free access to the paper
Looking back, we often understand what happened when somebody had sudden cardiac arrest (SCA). Sometimes, we don’t know what happened, even after extensive diagnostics. Especially in young, apparently healthy individuals, unexplained SCA has a major impact, despite being rare. We employed electrocardiographic imaging (ECGI) in survivors of unexplained SCA to get more insight in the arrhythmia substrate. ECGI extends the clinical electrocardiogram by using many more electrodes and imaging. We used it to study electrical recovery that happens after each heartbeat. In survivors of SCA in Maastricht UMC+, we found (clinically concealed) abnormalities in the electrical recovery of their hearts. In particular, these SCA survivors often have regions of early recovery next to regions of late recovery, with steep recovery gradients in between, and premature beats originating from the early recovery region. In experiments with explanted hearts at IHU LIRYC and in computer models (with support of Philips) we show that these premature beats may interact with the recovery gradients and lead to life-threatening arrhythmias. A tl/dr summary can be found in this Twitter thread.
These findings may help to provide targets for early diagnosis and improved therapy for sudden cardiac arrest, which we will need to study with future work.

I am excited to share the first results of my work at the interface of academia and industry from a collaboration between Maastricht University Medical Centre and Philips. At the Computing in Cardiology 2019 conference in Singapore we shared the first steps towards a robust, clinically applicable pipeline for personalized electrophysiology modeling. The corresponding paper can be found here and will form a corner stone for future collaborative projects on personalized medicine in cardiac electrophysiology.
Lau, K., Groth, A., Waechter-stehle, I., Nguyen, U. C., Volders, P. G., Heijman, J., Weese, J., Cluitmans, M. J. (2019). Personalized Ventricular Arrhythmia Simulation Framework to Study Vulnerable Trigger Locations on Top of Scar Substrate. Computing in Cardiology, In press.