Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties

Authors:
M. Sermesant;P. Moireau;O. Camara;J. Sainte-Marie;R. Andriantsimiavona;R. Cimrman;D. L. G. Hill;D. Chapelle;R. Razavi
Affiliations:
Cardiac MR Research Group, King’s College London, London, UK;MACS project, INRIA Rocquencourt, France;Cardiac MR Research Group, King’s College London, London, UK;MACS project, INRIA Rocquencourt, France;Cardiac MR Research Group, King’s College London, London, UK;New Technologies Research Centre, Západočeská univerzita v Plzni, Plzeň, Czech Republic;Cardiac MR Research Group, King’s College London, London, UK;MACS project, INRIA Rocquencourt, France;Cardiac MR Research Group, King’s College London, London, UK
Venue:
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Year:
2005

Citing 5
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Abstract

In this article, we present a framework to estimate local myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is deformed to fit a clinical MRI, using a semi-automatic fuzzy segmentation, an affine registration method and a local deformable biomechanical model. An electromechanical model of the heart is then presented and simulated. Data assimilation makes it possible to estimate local contractility from given displacements. Presented results on adjustment to clinical data and on assimilation with simulated data are very promising. Current work on model calibration and estimation of patient parameters open up possibilities to apply this framework in a clinical environment.