Characterizing Intraventricular Flow Patterns via Modal Decomposition Techniques in Idealized Left Ventricle Models

TL;DR

This study uses modal decomposition techniques to analyze vortex ring dynamics in idealized left ventricle models, revealing how geometry influences flow patterns and potential implications for cardiovascular diagnostics.

Contribution

First application of POD and HODMD to idealized LV models to understand vortex dynamics and geometry effects on intraventricular flow.

Findings

Geometry affects vortex interaction with ventricular walls.

Different geometries lead to distinct vortex propagation and dissipation patterns.

Flow analysis methods reveal structure and complexity of vortex evolution.

Abstract

Understanding the formation, propagation, and breakdown of the main vortex ring (VR) is essential for characterizing left ventricular (LV) hemodynamics, as its dynamics have been linked to the onset and progression of cardiovascular diseases. In this study, two idealized LV geometries, a semi-ellipsoidal chamber and a more rounded configuration, are analyzed using computational fluid dynamics (CFD) simulations under physiological conditions, with the aim of investigating the fluid mechanisms that govern VR evolution during diastole. Modal decomposition techniques, specifically proper orthogonal decomposition (POD) and higher order dynamic mode decomposition (HODMD), are employed to identify dominant coherent structures and track their temporal behavior. To the authors' knowledge, this is the first time such an analysis is conducted with the explicit goal of unraveling the physics of vortex ring dynamics in idealized ventricular chambers. The comparative approach reveals that geometric morphology plays a central role in modulating the flow: in one case, early interaction between the VR and the ventricular wall, driven by the chamber's shape, triggers strong nonlinear interactions and a more intricate dynamic evolution. In the other, the vortex ring propagates more freely toward the apex before dissipating, resulting in a more organized flow pattern and simpler spectral content. These findings advance the understanding of flow-based indicators relevant to early diagnosis and treatment planning in cardiovascular disease. Moreover, they illustrate how the choice of ventricular geometry can influence not only the simulated hemodynamics, but also the effectiveness of data-driven analysis tools, depending on the clinical context under study.