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A multiscale model for the study of cardiac biomechanics in single-ventricle surgeries: a clinical case
Author(s) -
Alessio Meoli,
Elena Cutrì,
Adarsh Krishnamurthy,
Gabriele Dubini,
Francesco Migliavacca,
TainYen Hsia,
Giancarlo Pennati,
Andrew M. Taylor,
Anna Giardini,
Sachin Khambadkone,
Silvia Schievano,
Marc De Leval,
Tian-Yen Hsia,
Edward L. Bove,
Adam L. Dorfman,
Gavin Baker,
Anthony M. Hlavacek,
Alison L. Marsden,
Jeffrey A. Feinstein,
Irène Vig-Clémentel,
Richard Figliola,
John L. McGregor
Publication year - 2015
Publication title -
interface focus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 49
eISSN - 2042-8901
pISSN - 2042-8898
DOI - 10.1098/rsfs.2014.0079
Subject(s) - ventricle , finite element method , computer science , stage (stratigraphy) , ventricular function , multiscale modeling , medicine , surgical planning , set (abstract data type) , cardiology , surgery , bioinformatics , physics , paleontology , biology , thermodynamics , programming language
Complex congenital heart disease characterized by the underdevelopment of one ventricular chamber (single ventricle (SV) circulation) is normally treated with a three-stage surgical repair. This study aims at developing a multiscale computational framework able to couple a patient-specific three-dimensional finite-element model of the SV to a patient-specific lumped parameter (LP) model of thewhole circulation, in a closed-loop fashion. A sequential approach was carried out: (i) cardiocirculatory parameters were estimated by using a fully LP model; (ii) ventricular material parameters and unloaded geometry were identified by means of the stand-alone, three-dimensional model of the SV; and (iii) the three-dimensional model of SV was coupled to the LP model of the circulation, thus closing the loop and creating a multiscale model. Once the patient-specific multiscale model was set using pre-operative clinical data, the virtual surgery was performed, and the post-operative conditions were simulated. This approach allows the analysis of local information on ventricular function aswell as global parameters of the cardiovascular system. This methodology is generally applicable to patients suffering from SV disease for surgical planning at different stages of treatment. As an example, a clinical case from stage 1 to stage 2 is considered here

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