Developing an Open-Source Framework for the Quantitative Simulation of Blood Flow and Tissue Motion for Ultrafast...

Ultrafast power Doppler imaging (uPDI) has become a powerful tool for both research and clinical applications. However, existing simulation tools are insufficient for generating quantitatively accurate 3-D flow fields with tissue motion mimicking in vivo conditions, often compromising physical realism by relying on steady-flow assumptions. In this study, we present an open-source framework-3D-Fully Quantitative Flow (3D-FQFlow)-to overcome these limitations by uniquely integrating stochastic vascular network generation, transient Navier-Stokes fluid dynamics and explicit perivascular tissue motion modeling. By explicitly solving for pulsatile hemodynamics under time-varying boundary conditions, the framework generates highly realistic spatiotemporal flow fields. Furthermore, 3D-FQFlow incorporates a custom, high-precision Lagrangian particle tracker and a memory-efficient, GPU-accelerated acoustic reconstruction module capable of efficiently rendering 3-D sequences with up to millions of scatterers. Here we demonstrate the quantitative accuracy and robust performance of the framework using synthetic vascular architectures, simulated perivascular motion and clinical datasets. By providing physiologically faithful ground truth hemodynamics and tissue motion, 3D-FQFlow serves as a comprehensive platform to support the development, validation and machine-learning benchmarking of advanced uPDI techniques. The source code is freely available online at https://github.com/FortuneOU/3D-FQFlow.