Pelvic floor morphometry: a predictor of success of pelvic floor muscle training for women with stress and mixed urinary incontinence Journal Articles uri icon

  • Overview
  • Research
  • Identity
  • Additional Document Info
  • View All


  • INTRODUCTION AND HYPOTHESIS: The aim of this study was to determine if pelvic floor muscle (PFM) morphometry at baseline, as measured by MRI, can predict response to PFM training in women with stress or mixed urinary incontinence (UI). METHODS: This study was a prospective quasi-experimental pre-test, post-test cohort study of women with UI, aged 60 years and older. All participants completed a baseline assessment of UI severity and impact, using the 72-h bladder diary and the Incontinence Impact Questionnaire. They underwent a pelvic MRI examination to assess the PFM anatomy. Women then participated in a 12-week PFM training program. Finally, they attended a post intervention assessment of UI severity and impact. The association between morphometry and PFM training response was assessed by univariate analysis, multivariate analysis, and receiver operating characteristic (ROC) curve analysis. RESULTS: The urethro-vesical junction height at rest, as measured by MRI before treatment, was associated with response to PFM training both on univariate (p ≤ 0.005) and multivariate analyses (p = 0.007). The area under the ROC curve was 0.82 (95% confidence interval [CI]: 0.67-0.96). Using a cut-off point of 11.4 mm, participants' response to PFM training was predicted with a sensitivity of 77% and a specificity of 83%. Incontinent women with a urethro-vesical junction height above this threshold were 35% more likely to respond to PFM training (OR 1.35; 95% CI: 1.08-1.67). CONCLUSION: In older women with UI, a urethro-vesical junction height at rest of at least 11.4 mm appears to be predictive of PFM training response.


  • Skelly, Jennifer
  • Dumoulin, Chantale
  • Tang, An
  • Pontbriand-Drolet, Stéphanie
  • Madill, Stephanie J
  • Morin, Mélanie

publication date

  • August 2017

has subject area