Automated personalised human left ventricular FE models to investigate heart failure mechanics

Vicky Y. Wang*, Corné Hoogendoorn, Alejandro F. Frangi, B. R. Cowan, Peter J. Hunter, Alistair A. Young, Martyn P. Nash

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

We have developed finite element modelling techniques to semi-automatically generate personalised biomechanical models of the human left ventricle (LV) based on cardiac magnetic resonance images. Geometric information of the LV throughout the cardiac cycle was derived via semi-automatic segmentation using non-rigid image registration with a pre-segmented image. A reference finite element mechanics model was automatically fitted to the segmented LV endocardial and epicardial surface data at diastasis. Passive and contractile myocardial mechanical properties were then tuned to best match the segmented surface data at end-diastole and end-systole, respectively. Global and regional indices of myocardial mechanics, including muscle fibre stress and extension ratio were then quantified and analysed. This mechanics modelling framework was applied to a healthy human subject and a patient with non-ischaemic heart failure. Comparison of the estimated passive stiffness and maximum activation level between the normal and diseased cases provided some preliminary insight into the changes in myocardial mechanical properties during heart failure. This automated approach enables minimally invasive personalised characterisation of cardiac mechanical function in health and disease. It also has the potential to elucidate the mechanisms of heart failure, and provide new quantitative diagnostic markers and therapeutic strategies for heart failure.

Original languageEnglish
Title of host publicationStatistical Atlases and Computational Models of the Heart
Subtitle of host publicationImaging and Modelling Challenges - Third International Workshop, STACOM 2012, Held in Conjunction with MICCAI 2012, Revised Selected Papers
Pages307-316
Number of pages10
DOIs
Publication statusPublished - 2013
Event3rd International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2012 - Nice, France
Duration: 5 Oct 20125 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7746 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2012
Country/TerritoryFrance
CityNice
Period5/10/125/10/12

Keywords

  • heart failure
  • in vivo myocardial mechanics
  • left ventricle
  • maximum activation level
  • myocardial stiffness
  • Personalised FE modelling

Fingerprint

Dive into the research topics of 'Automated personalised human left ventricular FE models to investigate heart failure mechanics'. Together they form a unique fingerprint.

Cite this