Simultaneous 3D Quantification of Fluid–Structure Interaction in a Patient-Averaged Left Ventricle: A Lagrangian Experimental Framework

Experimental validation of dynamic left-ventricular (LV) models remains limited due to the difficulty of simultaneously resolving three-dimensional (3D) wall kinematics and volumetric intraventricular transport. We present a novel experimental framework that provides co-registered, time-resolved 3D reconstructions of both ventricular wall motion and Lagrangian flow in a compliant LV model. By integrating deep-learning object identification and segmentation (SAM2) with 3D Particle Tracking Velocimetry (3D-PTV) and multi-media ray tracing, we establish a high-fidelity "physical twin" capable of capturing fluid-structure interaction (FSI) across physiological heart rates. Using this framework, we quantify the spatial distributions of wall shear stress (WSS) based on FSI metrics, including time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT). We observe a moderate inverse relationship between regional wall acceleration and TAWSS. In addition, RRT shows weak correspondence with directly measured Lagrangian residence time (LRT) derived from particle trajectories, indicating that surface-based Eulerian proxies may not reliably reflect volumetric transport in deforming chambers. The physical trends revealed in this experiment provide a benchmark for assessing computational FSI simulations and highlight the value of Lagrangian descriptors for characterizing intraventricular transport relevant to thrombogenic risk.