Temporal Interpolation of 4D PC-MRI Blood-flow Measurements Using Bidirectional Physics-based Fluid Simulation

Abstract

Magnetic Resonance Imaging (MRI) enables volumetric and time-varying measurements of blood-flow data. Such data have shown potential to improve diagnosis and risk assessment of various cardiovascular diseases. Hereby, a unique way of analysing patient-specific haemodynamics becomes possible. However, these measurements are susceptible to artifacts, noise and a coarse spatio-temporal resolution. Furthermore, typical flow visualization techniques rely on interpolation. For example, using pathlines requires a high quality temporal resolution. While numerical simulations, based on mathematical flow models, address some of these limitations, the involved modelling assumptions (e.g., regarding the inflow and mesh) do not provide patientspecific data to the degree actual measurements would. To overcome this issue, data assimilation techniques can be applied to use measured data in order to steer a physically-based simulation of the flow, combining the benefits of measured data and simulation. Our work builds upon such an existing solution to increase the temporal resolution of the measured data, but achieves significantly higher fidelity. We avoid the previous damping and interpolation bias towards one of the measurements, by simulating bidrectionally (forwards and backwards through time) and using sources and sinks. Our method is evaluated and compared to the, currently-used, conventional interpolation scheme and forward-only simulation using measured and analytical flow data. It reduces artifacts, noise, and interpolation error, while being closer to laminar flow, as is expected for flow in vessels.