An integrated approach to patient-specific predictive modeling for single ventricle heart palliation
Identifieur interne : 001D66 ( Main/Curation ); précédent : 001D65; suivant : 001D67An integrated approach to patient-specific predictive modeling for single ventricle heart palliation
Auteurs : Chiara Corsini [Italie] ; Catriona Baker [Royaume-Uni] ; Ethan Kung [États-Unis] ; Silvia Schievano [Royaume-Uni] ; Gregory Arbia [France] ; Alessia Baretta [Italie] ; Giovanni Biglino [Royaume-Uni] ; Francesco Migliavacca [Italie] ; Gabriele Dubini [Italie] ; Giancarlo Pennati [Italie] ; Alison Marsden [États-Unis] ; Irene Vignon-Clementel [France] ; Andrew Taylor [Royaume-Uni] ; Tain-Yen Hsia [Royaume-Uni] ; Adam Dorfman [États-Unis]Source :
- Computer methods in biomechanics and biomedical engineering [ 1025-5842 ] ; 2013.
Abstract
In patients with congenital heart disease and a single ventricle (SV), ventricular support of the circulation is inadequate, and staged palliative surgery (usually 3 stages) is needed for treatment. In the various palliative surgical stages individual differences in the circulation are important and patient-specific surgical planning is ideal. In this study, an integrated approach between clinicians and engineers has been developed, based on patient-specific multi-scale models, and is here applied to predict stage 2 surgical outcomes. This approach involves four distinct steps: (1) collection of pre-operative clinical data from a patient presenting for SV palliation, (2) construction of the pre-operative model, (3) creation of feasible virtual surgical options which couple a three-dimensional model of the surgical anatomy with a lumped parameter model (LPM) of the remainder of the circulation and (4) performance of post-operative simulations to aid clinical decision making. The pre-operative model is described, agreeing well with clinical flow tracings and mean pressures. Two surgical options (bi-directional Glenn and hemi-Fontan operations) are virtually performed and coupled to the pre-operative LPM, with the hemodynamics of both options reported. Results are validated against postoperative clinical data. Ultimately, this work represents the first patient-specific predictive modeling of stage 2 palliation using virtual surgery and closed-loop multi-scale modeling.
Url:
DOI: 10.1080/10255842.2012.758254
PubMed: 23343002
PubMed Central: 4242799
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PMC:4242799Le document en format XML
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<author><name sortKey="Biglino, Giovanni" sort="Biglino, Giovanni" uniqKey="Biglino G" first="Giovanni" last="Biglino">Giovanni Biglino</name>
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<author><name sortKey="Marsden, Alison" sort="Marsden, Alison" uniqKey="Marsden A" first="Alison" last="Marsden">Alison Marsden</name>
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<author><name sortKey="Dorfman, Adam" sort="Dorfman, Adam" uniqKey="Dorfman A" first="Adam" last="Dorfman">Adam Dorfman</name>
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<country xml:lang="fr">États-Unis</country>
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<front><div type="abstract" xml:lang="en"><p id="P3">In patients with congenital heart disease and a single ventricle (SV), ventricular support of the circulation is inadequate, and staged palliative surgery (usually 3 stages) is needed for treatment. In the various palliative surgical stages individual differences in the circulation are important and patient-specific surgical planning is ideal. In this study, an integrated approach between clinicians and engineers has been developed, based on patient-specific multi-scale models, and is here applied to predict stage 2 surgical outcomes. This approach involves four distinct steps: (1) collection of pre-operative clinical data from a patient presenting for SV palliation, (2) construction of the pre-operative model, (3) creation of feasible virtual surgical options which couple a three-dimensional model of the surgical anatomy with a lumped parameter model (LPM) of the remainder of the circulation and (4) performance of post-operative simulations to aid clinical decision making. The pre-operative model is described, agreeing well with clinical flow tracings and mean pressures. Two surgical options (bi-directional Glenn and hemi-Fontan operations) are virtually performed and coupled to the pre-operative LPM, with the hemodynamics of both options reported. Results are validated against postoperative clinical data. Ultimately, this work represents the first patient-specific predictive modeling of stage 2 palliation using virtual surgery and closed-loop multi-scale modeling.</p>
</div>
</front>
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