Computational Fluid Dynamics Modeling of Ureteroscopy Irrigation

Ureteroscopy irrigation is a process in kidney stone removal where the kidney is pressurized with saline solution in order to improve camera field of view, aid in the removal of small particles from the stone, and to reduce heat buildup during laser lithotripsy. There is a minimal understanding in the field of urology regarding how the fluid moves inside the kidney during this process. This project focused on the use of CFD (Computational Fluid Dynamics) to model fluid flow through a 3D scan of a patient’s kidney with three kidney stones. This geometry allowed for the visualization of various important features of the flow, such as pressures, velocity streamlines and flow regime. In tandem with the CFD model, a physical lab model was created with hydrogel based on the same scans. Trials were run through both the CFD model and the hydrogel model at different pressures with and without the presence of stones, at various different ureteroscope positions. Currently, the CFD model matches calculated velocity values based on ureteroscope research, and the data suggest accurate and realistic flow patterns. Compared to pressure data from the lab model, our CFD data matches well in the trials where no stone is present but has issues modeling the presence of the large stone in the specific ureteroscope position that has been tested. This is likely due to what is called a ball-valve effect in urology (Younis, A. and Radharikrishnan, S. (2011), Kidney stone disease. Trends in Urology & Men's Health, 2: 15-20,) where pressure build up inside the kidney as seen in the CFD model causes the stone to move and obstruct the connection between the ureter and the kidney. In our CFD model, the stone is not able to move, and consequently, a much higher pressure is observed compared to the lab data in all scenarios tested thus far. In the future the CFD model will be compared to different scope positions where the ball-valve effect will not have as much of an impact, presumably leading to much more accurate in pressure data.