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Updated: Sep 17, 2025

An In Vitro Bladder Model of Catheter-Associated Urinary Tract Infection
Published on: June 24, 2025
Experimental and CFD analysis of flow impediments and encrustation in ureteral stents using in vitro urinary tract
Md Didarul Islam1,2, Hyo Jeong Kang3, Sung Jin Tae3
1Department of Mechanical Engineering, Graduate School of Engineering, Gyeongsang National University, Jinju, South Korea.
Abstract:
A significant challenge for urological treatment is caused by encrustation that can obstruct urinary drainage. We analyzed the rate of encrustation formation for the initial three weeks in Conventional Double J Stent (CDJS), Renovated Double J Stent (RDJS), and Single J Stent (SJS) under patient-specific control conditions (37 °C, pH 7.8, 60 mL/hr., 50% stenosis). A conceptually designed in vitro urinary tract model representing the kidney, ureter and bladder model is used where the inlet flow rate is controlled with a peristaltic pump, and when the bladder is filled with artificial urine (AU), it is emptied manually, and the time is measured to calculate flow impediments. Stents have been removed from the tract after 21 days to measure mass and scanning electron microscope (SEM) analysis. A Computational Fluid Dynamics (CFD) analysis has been done to show the velocity profile and wall shear stress (WSS) of stents. RDJS has shown the highest flow rate and stable flow performance from the experiment, and SJS exhibited the lowest encrustation with a mass increase of 0.025 g compared to RDJS (0.053 g) and CDJS (0.057 g). The SEM image showed encrustation covered 10.37% of the SJS significantly lower than RDJS (13.04%) and CDJS (13.52%) near the stenosis side holes. The research evidence on SJS demonstrates the least encrustation of SJS stenosis region is further validated through the simulation result which showed a higher wall shear stress (10.4 mPa) for SJS at that location. SJS should be used for short durations for high-risk patients and RDJS for better flow maintenance, which indicates that stent selection should focus on improving the patient's outcomes.

