Articles techniques et présentations

Bladder outlet obstruction (BOO) is a prevalent condition that characterises increased urethral resistance and gives rise to a myriad of lower urinary tract symptoms. Over time, BOO can significantly affect bladder functionality and lower quality of life. Furthermore, surgical interventions that reduce the obstruction are often unsuccessful, with approximately one-third of patients remaining symptomatic after surgery.

From a biomechanical perspective, smooth muscle (SM) in the bladder wall must now generate greater pressures to overcome the increased resistance and void. This initiates a mechanobiological response that drives the BOO bladder through three stages of remodelling: Hypertrophy; Compensation; Decompensation. However, the relationship between increased bladder pressure, remodelling-driven wall changes and bladder dysfunction are poorly understood.

We develop a digital twin of bladder outlet obstruction mechanobiology (BOOM), informed by an experimental model of rat bladder obstruction using an integrative in vivo - in vitro - in silico approach. A finite element (FE) model for the bladder is built in COMSOL Multiphysics® (Nonlinear Structural Materials Module), with the bladder wall modelled as a hyperelastic multi-layered, fibre-reinforced, constrained mixture. The mechanical model utilises multiple time scales, a shorter time scale over which the active mechanics of voiding are considered, and a longer time scale at which bladder constituents undergo growth and remodelling (using a rate-based approach to evolve the constrained mixture). The model is calibrated to a healthy rat bladder and predictions of evolving structure and function are compared with in vivo/in vitro observations of an obstructed bladder. In this study, we explore the impact of different SM growth hypotheses on maintaining bladder functionality by including transversely anisotropic, volumetric growth models for the smooth muscle layer. Furthermore, by coupling biochemical signalling into our digital twin, we explore possible avenues for pharmacological treatment.