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Effects of Levator Ani Muscle Morphology on the Mechanics of Vaginal Childbirth

  • Xiani Yan
  • Jennifer A. Kruger
  • Martyn P. Nash
  • Poul M. F. Nielsen
Conference paper

Abstract

Childbirth-induced trauma is one of the leading factors that cause pelvic floor (PF) muscle dysfunction. There is preliminary evidence to suggest that the morphology of the levator ani (LA) muscles influences the progress of the second stage of labour. Three-dimensional modelling of the LA muscle shape variations can help to identify structures that are potentially susceptible to labour-induced injuries. The first aim of this study was to use finite element modelling to study the geometrical variations of the normal PF muscles, using sets of magnetic resonance images from 12 normal nulliparous women. The effects of PF muscle shape variation on the mechanics of vaginal childbirth was then investigated using biomechanics simulations. During construction of the individual-specific PF models, point-to-point correspondence of anatomical features was achieved through a series of mathematical transformations. A principal component analysis (PCA) method was applied to the fitted PF models to compute the PF shape variations. The results were then used to construct the mean PF shape, plus four further PF models derived from the mean model and the first two primary modes of variation. These PCA-derived models were analysed using a biomechanical framework of the second stage of labour. The maximum principal stretch ratios and the forces required for delivery of a foetal head were quantified and analysed with respect to the geometry of each derived mode, to extract features of the PF muscles that are potentially susceptible to childbirth-induced injuries. The statistical shape analysis approach presented here may be extended to extract patterns of PF muscle morphological changes that are involved in PF dysfunction.

Keywords

Pelvic Floor Mode Shape Pelvic Organ Prolapse Pelvic Floor Muscle Pubic Bone 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

X. Yan is financially supported by a University of Auckland Doctoral Scholarship. J. A. Kruger is supported by a Rutherford Foundation Postdoctoral Fellowship funded by the Royal Society of New Zealand. M. P. Nash and P. M. F. Nielsen are supported by James Cook Research Fellowships administered by the Royal Society of New Zealand on behalf of the New Zealand Government.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Xiani Yan
    • 1
  • Jennifer A. Kruger
    • 1
  • Martyn P. Nash
    • 1
    • 2
  • Poul M. F. Nielsen
    • 1
    • 2
  1. 1.Auckland Bioengineering InstituteThe University of AucklandAucklandNew Zealand
  2. 2.Department of Engineering ScienceThe University of AucklandAucklandNew Zealand

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