Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.
In this paper, we present a framework to estimate local ventricular 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. Finally, a data assimilation procedure is described, and applied to this model. Data assimilation makes it possible to estimate local contractility from given displacements. Presented results on fitting to patient-specific anatomy and assimilation with simulated data are very promising. Current work on model calibration and estimation of patient parameters opens up possibilities to apply this framework in a clinical environment.
Sermesant
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INRIA, team ASCLEPIOS, 2004 route des Lucioles, 06902 Sophia Antipolis, France.
Moireau
P
P
Camara
O
O
Sainte-Marie
J
J
Andriantsimiavona
R
R
Cimrman
R
R
Hill
D L G
DL
Chapelle
D
D
Razavi
R
R
D000328:Adult; D016880:Anisotropy; D003198:Computer Simulation; D004548:Elasticity; D020342:Finite Element Analysis; D006352:Heart Ventricles / Q000166:cytology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000639:trends; D008955:Models, Cardiovascular; D018485:Muscle Fibers, Skeletal / Q000166:cytology; D009200:Myocardial Contraction / Q000502:physiology*; D033081:Shear Strength; D013314:Stress, Mechanical; D016276:Ventricular Function; D016277:Ventricular Function, Left / Q000502:physiology*