Andrew J Cohen1, Nima Baradaran1, Jorge Mena1, Daniel Krsmanovich2, Benjamin N Breyer1,3. 1. Department of Urology, University of California-San Francisco , San Francisco , California. 2. CardioMed Technology Consultants , San Francisco , California. 3. Department of Biostatistics and Epidemiology, University of California-San Francisco , San Francisco , California.
Abstract
PURPOSE: Computational fluid dynamics have paradigm shifting potential in understanding the physiological flow of fluids in the human body. This translational branch of engineering has already made an important clinical impact on the study of cardiovascular disease. We evaluated the feasibility and applicability of computational fluid dynamics to model urine flow. MATERIALS AND METHODS: We prepared a computational fluid dynamics model using an idealized male genitourinary system. We created 16 hypothetical urethral stricture scenarios as a test bed. Standard parameters of urine such as pressure, temperature and viscosity were applied as well as typical assumptions germane to fluid dynamic modeling. We used ABAQUS/CAE 6.14 (Dassault Systèmes®) with a direct unsymmetrical solver with standard (FC3D8) 3D brick 8Node elements for model generation. RESULTS: The average flow rate in urethral stricture disease as measured by our model was 5.97 ml per second (IQR 2.2-10.9). The model predicted a flow rate of 2.88 ml per second for a single 5Fr stricture in the mid bulbar urethra when assuming all other variables constant. The model demonstrated that increasing stricture diameter and bladder pressure strongly impacted urine flow while stricture location and length, and the sequence of multiple strictures had a weaker impact. CONCLUSIONS: We successfully created a computational fluid dynamics model of an idealized male urethra with varied types of urethral strictures. The resultant flow rates were consistent with the literature. The accuracy of modeling increasing bladder pressure should be improved by future iterations. This technology has vast research and clinical potential.
PURPOSE: Computational fluid dynamics have paradigm shifting potential in understanding the physiological flow of fluids in the human body. This translational branch of engineering has already made an important clinical impact on the study of cardiovascular disease. We evaluated the feasibility and applicability of computational fluid dynamics to model urine flow. MATERIALS AND METHODS: We prepared a computational fluid dynamics model using an idealized male genitourinary system. We created 16 hypothetical urethral stricture scenarios as a test bed. Standard parameters of urine such as pressure, temperature and viscosity were applied as well as typical assumptions germane to fluid dynamic modeling. We used ABAQUS/CAE 6.14 (Dassault Systèmes®) with a direct unsymmetrical solver with standard (FC3D8) 3D brick 8Node elements for model generation. RESULTS: The average flow rate in urethral stricture disease as measured by our model was 5.97 ml per second (IQR 2.2-10.9). The model predicted a flow rate of 2.88 ml per second for a single 5Fr stricture in the mid bulbar urethra when assuming all other variables constant. The model demonstrated that increasing stricture diameter and bladder pressure strongly impacted urine flow while stricture location and length, and the sequence of multiple strictures had a weaker impact. CONCLUSIONS: We successfully created a computational fluid dynamics model of an idealized male urethra with varied types of urethral strictures. The resultant flow rates were consistent with the literature. The accuracy of modeling increasing bladder pressure should be improved by future iterations. This technology has vast research and clinical potential.
Authors: Andrew J Cohen; German Patino; Mehran Mirramezani; Sudarshan Srirangapatanam; Anas Tresh; Bhagat Cheema; Jenny Tai; Dylan Romero; Anthony Enriquez; Laurence S Baskin; Shawn C Shadden; Benjamin N Breyer Journal: PLoS One Date: 2020-11-11 Impact factor: 3.240