In Silico Optimisation of Regenerative Cell Therapy in the Infarcted Human Ventricles to Mitigate Arrhythmic Burden

Myocardial infarction remains a frequent cause of heart failure and mortality. Cell therapy has been shown promising in pre-clinical trials to regenerate the damaged tissue, but delivered cells may beat spontaneously and produce arrhythmias in the ventricles, particularly in the first weeks after delivery, which hinders clinical application. Previous studies have proposed ionic targets to supress the cells’ automaticity but, so far, the effects of such treatments on the cells’ calcium dynamics, as a key driver of contractile function, have been insufficiently evaluated. Furthermore, effective strategies are needed that can alleviate the injected cells’ pro-arrhythmic action potential phenotypes.

The goal of our study was to identify mechanisms to mitigate arrhythmic pathways following cell delivery in the chronically infarcted human ventricles using multiscale modelling and simulation. First, we demonstrate credibility by simulating experimentally observed transient automaticity-induced ventricular tachycardia arrhythmias with a frequency of up to 140 beats per minute at two weeks post cell injection in three different infarct geometries. Next, our simulations show how the timeframe during which re-entry was inducible increases 1) from before to after cell delivery at day 0 from 0 to 640 ms, 60 to 100 ms, and 60 to 760 ms in the small, medium, and large scar, respectively, and 2) from day 0 to day 14 after virtual cell injection in the large scar by 175%. Finally, we show that a combination of blocking the funny current and upregulating the inward rectifier potassium current, the sodium potassium pump, and the rapid delayed outward rectifier potassium current can reduce both automaticity-induced and re-entrant arrhythmias while maximising calcium amplitudes.

In conclusion, our simulations show that not only automaticity-induced but also re-entrant arrhythmias increase as injected cells mature in the ventricles and depend on the scar size. Furthermore, through modelling and simulation, we identify anti-arrhythmic strategies to improve therapy safety while maximising efficacy.