Optimizing PCI by simplified coronary physiology techniques & intravascular imaging

Over the past decades, numerous innovations in the field of interventional cardiology helped to improve the outcome of patients with coronary artery disease undergoing PCI. Yet, a considerable amount of these patients still experience recurrent angina and target vessel failure, indicating that there is still room for improvement. Coronary physiology and intravascular imaging have emerged as safe and effective tools to support PCI decision making and to further improve patient outcome. However, despite strong guideline recommendations and due to local restrictions, financial limitations, as well as personal preferences, these valuable techniques remain underutilized.

The purpose of this thesis was to evaluate and implement novel coronary physiology and intravascular imaging technologies in clinical algorithms. We found that vFFR has the potential to replace pressure-wire based physiology and to simplify PCI decision-making. We also proposed an IVUS-based automated calcium detection algorithm using AI and linked the burden of calcification to stent expansion and cardiovascular events. Finally, by restricting additional IVUS evaluation to patients with suboptimal post-PCI physiology, we found that subsequent PCI optimization significantly lowered the rate of target vessel and target lesion revascularization. The results of this thesis contribute to a more widespread adoption of coronary physiology and intravascular imaging in clinical practice to further improve PCI outcomes and may strengthen their role in future myocardial revascularization guidelines.