A personalized mitral valve closure simulator

P. Burlina, R. Mukherjee, C. Sprouse

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

We describe a method for performing modeling and simulation to predict the closure of the Mitral Valve (MV) using patient specific anatomical information derived from 3D Transesophageal Echocardiography (3D TEE). The ability to predict the MV closure behavior is an important step along the way of developing personalized simulation tools that would allow a surgeon to perform preoperative planning and decide between various MV repair options. While the MV is an important use case because of its relevance and prevalence among reconstructive cardiac interventions, the study described here can provide a blueprint to perform pre-operative planning for other cardiac surgical interventions. The method reported here exploits the Saint Venant-Kirchhoff elasticity model that is tuned to match empirical observations of the MV strainstress behavior. Using intraoperative 3D TEE data, the proposed simulator was evaluated over 10 test cases and resulted in mean prediction absolute error values of 1.81 mm.

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages6636-6640
Number of pages5
DOIs
StatePublished - Dec 14 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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