title: Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation.
abstract: A closed-loop lumped parameter model of blood circulation is considered for single-ventricle shunt physiology. Its parameters are estimated by an inverse problem based on patient-specific haemodynamics measurements. As opposed to a black-box approach, maximizing the number of parameters that are related to physically measurable quantities motivates the present model. Heart chambers are described by a single-fibre mechanics model, and valve function is modelled with smooth opening and closure. A model for valve prolapse leading to valve regurgitation is proposed. The method of data assimilation, in particular the unscented Kalman filter, is used to estimate the model parameters from time-varying clinical measurements. This method takes into account both the uncertainty in prior knowledge related to the parameters and the uncertainty associated with the clinical measurements. Two patient-specific cases - one without regurgitation and one with atrioventricular valve regurgitation - are presented. Pulmonary and systemic circulation parameters are successfully estimated, without assumptions on their relationships. Parameters governing the behaviour of heart chambers and valves are either fixed based on biomechanics, or estimated. Results of the inverse problem are validated qualitatively through clinical measurements or clinical estimates that were not included in the parameter estimation procedure. The model and the estimation method are shown to successfully capture patient-specific clinical observations, even with regurgitation, such as the double peaked nature of valvular flows and anomalies in electrocardiogram readings. Lastly, biomechanical implications of the results are discussed.
authors.affiliation: Inria Paris-Rocquencourt & Sorbonne Universités UPMC Paris 6, Laboratoire Jacques-Louis Lions, France. Electronic address: Sanjay.Pant@inria.fr.
authors.forename: Sanjay
authors.initials: S
authors.lastname: Pant
authors.affiliation: Laboratory of Biological Structure Mechanics, Department of Chemistry, Materials and Chemical Engineering 'Giulio Natta', Politecnico di Milano, Italy.
authors.forename: Chiara
authors.initials: C
authors.lastname: Corsini
authors.affiliation: Cardiac Unit, UCL Institute of Cardiovascular Science, and Great Ormond Street Hospital for Children, London, UK.
authors.forename: Catriona
authors.initials: C
authors.lastname: Baker
authors.affiliation: Cardiac Unit, UCL Institute of Cardiovascular Science, and Great Ormond Street Hospital for Children, London, UK.
authors.forename: Tain-Yen
authors.initials: TY
authors.lastname: Hsia
authors.affiliation: Laboratory of Biological Structure Mechanics, Department of Chemistry, Materials and Chemical Engineering 'Giulio Natta', Politecnico di Milano, Italy.
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Pennati
authors.affiliation: Inria Paris-Rocquencourt & Sorbonne Universités UPMC Paris 6, Laboratoire Jacques-Louis Lions, France. Electronic address: irene.vignon-clementel@inria.fr.
authors.forename: Irene E
authors.initials: IE
authors.lastname: Vignon-Clementel
mesh_terms: D006349:Heart Valve Diseases / Q000503:physiopathology*; D006352:Heart Ventricles / Q000503:physiopathology*; D006801:Humans; D066230:Patient-Specific Modeling; D016276:Ventricular Function
keywords: Data assimilation; Patient-specific modelling; Single-fibre heart model; Single-ventricle physiology; Unscented Kalman filter; Valve regurgitation