Share Email Print
cover

Proceedings Paper

Modelling the pelvic floor for investigating difficulties during childbirth
Author(s): Xinshan Li; Jennifer A. Kruger; Jae-Hoon Chung; Martyn P. Nash; Poul M. F. Nielsen
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Research has suggested that athletes involved in high-intensity sports for sustained periods have a higher probability of experiencing prolonged second stage of labour compared to non-athletes. The mechanism responsible for this complication is unknown but may depend on the relative size or tone of the pelvic floor muscles. Prolonged training can result in enlargement and stiffening of these muscles, providing increased resistance as the fetal head descends through the birth canal during a vaginal birth. On the other hand, recent studies have suggested an association between increased muscle bulk in athletes and higher distensibility. This project aims to use mathematical modelling to study the relationship between the size and tone of the pelvic floor muscles and the level of difficulty during childbirth. We obtained sets of magnetic resonance (MR) images of the pelvic floor region for a female athlete and a female non-athlete. Thirteen components of the pelvic floor were segmented and used to generate finite element (FE) models. The fetal head data was obtained by laser scanning a skull replica and a FE model was fitted to these data. We used contact mechanics to simulate the motion of the fetal head moving through the pelvic floor, constructed from the non-athlete data. A maximum stretch ratio of 3.2 was induced in the muscle at the left lateral attachment point to the pubis. We plan to further improve our modelling framework to include active muscle contraction and fetal head rotations in order to address the hypotheses that there is a correlation between the level of difficulty and the size or tone of the pelvic floor muscles.

Paper Details

Date Published: 12 March 2008
PDF: 10 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69160V (12 March 2008); doi: 10.1117/12.769898
Show Author Affiliations
Xinshan Li, The Univ. of Auckland (New Zealand)
Jennifer A. Kruger, The Univ. of Auckland (New Zealand)
Jae-Hoon Chung, The Univ. of Auckland (New Zealand)
Martyn P. Nash, The Univ. of Auckland (New Zealand)
Poul M. F. Nielsen, The Univ. of Auckland (New Zealand)


Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

© SPIE. Terms of Use
Back to Top