Image-based simulation of urethral distensibility and flow resistance as a function of pelvic floor anatomy. Academic Article uri icon

Overview

abstract

  • AIMS: The goal of this study is to develop an image-based model of urethral distention and resistance in women with and without SUI. METHODS: A biomechanical vector force model was created to simulate the mechanical deformation of pelvic floor structures during cough and Valsalva in order to measure urethral distension and predict flow resistance patterns. Dynamic MRI images were used to create a spatial model to construct an accurate representation of tissue thickness and location, which was combined with tissue property values (MATLAB 2011a, MathWorks, Natick, MA). Spatial profiles were created to demonstrate the effects of hypermobility and tissue property variability on distensibility and flow resistance along the urethra. Sensitivity analyses were conducted to demonstrate the relationship between flow resistance and various tissue properties. RESULTS: The average distension for incontinent cases (3.8 mm) was significantly greater than that of continent cases (2.6 mm) (t = 3.3083, df = 8, P < 0.01), corresponding to a 70% drop in average resistance to urine flow. Sensitivity analyses demonstrated that the stiffness and contractility of the vagina and urethra had the greatest effect on continence. CONCLUSIONS: We present a novel, 2-dimensional biomechanical model of female stress urinary incontinence (SUI) that relates the effects of various factors such as tissue elasticity, pelvic floor structure, and muscle activation. A better understanding of the pathophysiology underlying SUI has potential implications for the creation of novel targeted treatments.

publication date

  • May 3, 2014

Research

keywords

  • Image Interpretation, Computer-Assisted
  • Magnetic Resonance Imaging
  • Models, Biological
  • Pelvic Floor
  • Urethra
  • Urinary Incontinence, Stress
  • Urodynamics

Identity

Scopus Document Identifier

  • 84939153415

Digital Object Identifier (DOI)

  • 10.1002/nau.22624

PubMed ID

  • 24796854

Additional Document Info

volume

  • 34

issue

  • 7