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research-article

Characterising the Biomechanical Properties of Pubovisceralis Muscle using a Genetic Algorithm and the Finite Element Method

[+] Author and Article Information
Elisabete Silva

LAETA, INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias s/n; 4200 – 465 Porto, Portugal
silva.elisabete3@gmail.com

Marco Parente

LAETA, INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias s/n; 4200 – 465 Porto, Portugal
mparente@fe.up.pt

Sofia Brandão

Dep. of Radiology, CHSJ-EPE / Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200 – 319 Porto, Portugal
sofia.brand@gmail.com

Teresa Mascarenhas

Dep. of Obstetrics and Gynecology, CHSJ-EPE / Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200 – 319 Porto, Portugal
tqc@sapo.pt

Renato Natal Jorge

LAETA, INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias s/n; 4200 – 465 Porto, Portugal
rnatal@fe.up.pt

1Corresponding author.

ASME doi:10.1115/1.4041524 History: Received December 15, 2017; Revised August 28, 2018

Abstract

To better understand disorders in the pelvic cavity associated to the pelvic floor muscles using computational models, it is fundamental to identify the biomechanical properties of these muscles. For this purpose, we implemented an optimization scheme, involving a Genetic algorithm (GA) and an inverse finite element analysis (FEA), in order to estimate the material properties of the pubovisceralis muscle (PVM). The datasets of five women were included in this non-invasive analysis. The numerical models of the PVM were built from static axial magnetic resonance (MR) images, and the hyperplastic Mooney-Rivlin constitutive model was used. The material constants obtained were compared with the ones established through a similar optimization scheme, using the Powell´s algorithm. To validate the values of the material constants that characterize the passive behavior of the PVM, the displacements obtained via the numerical models with both methods were compared with dynamic MR images acquired during Valsalva maneuver. The material constants (c1 and c2) were higher for the GA than for the Powell's algorithm, but when comparing the magnitude of the displacements [mm] of the PVM there was only a 5% difference, and 4% for the principal logarithmic strain. The GA allowed estimating the in vivo biomechanical properties of the PVM of different subjects, requiring a lower number of simulations when compared to the Powell's algorithm. Keywords: Pubovisceralis Muscle, Biomechanical Properties, Magnetic Resonance Imaging, Genetic Algorithm, Computational Models.

Copyright (c) 2018 by ASME
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