Vortex Dynamics and Energy Dissipation in Left Ventricular Diastolic Filling Across Diastolic Function Inflow Patterns: An In Vitro Quantitative Flow Analysis

Diastolic dysfunction is a central driver of heart failure, yet the fluid-dynamic mechanisms underlying altered left ventricular (LV) filling are not fully understood. In this study, we characterize intraventricular vortex dynamics and hemodynamic performance across diastolic function inflow patterns using a physiologically accurate in vitro LV simulator. Diastolic function inflow patterns (impaired relaxation, normal, restrictive filling) were modeled by independently varying the E/A ratio (ratio of the early and late diastolic peak inflows), diastasis duration (0–20% of the cardiac cycle), heart rate (60–90 bpm), and stroke volume while maintaining clinically relevant inflow velocities (0.5–0.9 m/s). Quantitative flow analysis was performed using phase-locked particle image velocimetry. Hemodynamic metrics of two-dimensional viscous energy dissipation (VED), shear rate, and turbulent kinetic energy (TKE) were calculated from planar velocity field measurements. Abnormal inflow patterns exhibited higher energy losses than normal inflow patterns. Restrictive filling inflow patterns produced the highest peak VED (50% greater than normal) and increased TKE (38% greater), whereas impaired relaxation inflow patterns led to pronounced vortex pair merging, yielding the highest peak TKE (57% greater than normal). A moderate diastasis duration minimized VED across E/A ratios, identifying a local energetic optimum at 3.3 L/min, which was not observed under low-cardiac output conditions. In impaired relaxation inflow patterns, diastole-averaged VED scaled nonlinearly with stroke volume and linearly with heart rate at a constant cardiac output. These results characterize how the E/A ratio and diastasis independently govern LV vortex interactions and energetic efficiency, providing insights into the hemodynamic mechanisms of diastolic dysfunction, and may motivate future clinical studies to identify potential markers of disease severity.