STUDY OF CARDIAC FLUID DYNAMICS IN THE RIGHT SIDE OF THE HEART WITH AI PIV

Abstract

Particle image velocimetry (PIV), when used to investigate cardiac flows, has been restricted to the exploration of left-heart hemodynamics. Easy phantom modeling, simple geometrical assumptions, and the use of modified ultrahigh-frequency 3-D echocardiographic probes dedicated to the left heart are the main reasons for this restriction. However, hemodynamics of the right heart, due to its complex geometry, is still poorly understood. AI PIV, based on deep learning and convolutional neural networks, offers a super-resolution view of the velocity fields. In this paper, we apply this new technique to agitated saline bubble echocardiographic recordings of the right heart. The obtained higher-resolution results show promising patterns and vortices throughout the cardiac cycle, circumventing the abovementioned obstacles. For instance, the annular tricuspid excursion, which has been used for decades as a marker of systolic function of the right ventricle, seems to be crucial for the formation of two diastolic vortices in the right atrium. A lateral counterclockwise vortex and a medial clockwise vortex that direct flow from the low-pressure right atrium to the middle of the tricuspid valve were noted repeatedly throughout different cardiac cycles within the same patients and between different patients.