A Novel, Non-Invasive Approach to Diagnosing Urinary Tract Obstruction Using CFD.

Abstract

Aims: Urinary tract obstruction is a common clinical problem involving narrowing anywhere along the ureters or urethra. Current diagnostic methods are invasive and costly, and urologists are constantly seeking new, inexpensive, non-invasive measures to diagnose obstruction. The present study investigates diagnostic applications of computational fluid dynamics (CFD) to urinary tract obstruction for the first time.

Methods: Various hypothetical models were initially created in Gambit 2.1.6, in which the physics of flow was evaluated based on varying geometries and conditions. These models presented short segments of the tract and possible effects of obstruction. Flow analysis was conducted in Fluent 6.1.22 by comparing contours of velocity, static pressure, dynamic pressure, total pressure, and wall shear stress to results predicted by flow theory. Realistic models of both healthy and obstructed urethras and ureters were then similarly created and simulated.

Results: CFD equations accurately predicted the expected flow characteristics through both hypothetical and realistic models. Comparison of modeled urethral outlet velocity to human uroflowmetry data shows that the simulated conditions are almost identical to realistic human flow.

Conclusions: The accuracy of the models suggests clinical potential of using CFD with current techniques in human tract analysis, secondary flow effects, disease prevention, and non-invasive diagnosis.