Study on ultrasound color flow imaging of renal artery stenosis using computational hemodynamics

Imaging of renal artery stenosis (RAS) has great clinical importance to reduce the risk of renal disorders. The hemodynamical information is crucial for stenosis detection. In this study, realistic computational models of RAS have been designed to investigate hemodisturbances and collect spatio-temporal locations of blood particles for simulating and validating ultrasound color flow images of RAS considering different levels of stenosis and viscosity. Flow images have been formed using autocorrelation based phase estimation from multi-excited radiofrequency (RF) echoes of moving blood particles. A median pre-processed Gaussian filter has been used to suppress impulsive and speckle noises. The ultrasound simulated flow characteristics have been investigated and compared with computed flow behavior and found a good agreement. It also observed that consideration of viscosity change effect during serial examinations or examinations with hemodilution treatment can be helpful. The outcomes of this study might be useful to diagnosis the present conditions and predict the future progressions of RAS.