Artificial intelligence-powered quantification of coronary physiology and vulnerable plaque: opportunities for novel treatment options

Sponsored by Pulse Medical

Anchorperson: M. Haude

Spokesperson: W. Wijns

Summary

In this session, uncover new data on Murray-law based quantitative flow ratio (muFR) assessment, providing a comprehensive understanding of PCI outcomes from a single angiographic view, explore the innovative application of artificial intelligence in identifying vulnerable plaque and assessing hemodynamic stenosis significance through the analysis of radial wall strain (RWS) from coronary angiograms, and review the impact of resorbable magnesium scaffold (RMS) implantation on vulnerable plaque composition and evolution, revealing promising advancements in cardiovascular intervention techniques.

Learning Objectives

To share new data on Murray-law based quantitative flow ratio (muFR) pre-during-post PCI from a single angiographic view
To illustrate how vulnerable plaque and hemodynamic stenosis significance can be identified from artificial intelligence-based analysis of radial wall strain (RWS) from coronary angiogram
To review the effect of resorbable magnesium scaffold (RMS) implantation on vulnerable plaque composition and evolution