Personalized Perioperative Multi-scale, Multi-physics Heart Simulation of Double Outlet Right Ventricle

For treatment of complex congenital heart disease, computer simulation using a three-dimensional heart model may help to improve outcomes by enabling detailed preoperative evaluations. However, no highly integrated model that accurately reproduces a patient’s pathophysiology, which is required for t...

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Bibliographic Details
Published in:Annals of biomedical engineering 2020-06, Vol.48 (6), p.1740-1750
Main Authors: Kariya, Taro, Washio, Takumi, Okada, Jun-ichi, Nakagawa, Machiko, Watanabe, Masahiro, Kadooka, Yoshimasa, Sano, Shunji, Nagai, Ryozo, Sugiura, Seiryo, Hisada, Toshiaki
Format: Article
Language:English
Subjects:
Biochemistry
Biological and Medical Physics
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Cardiovascular disease
Cardiovascular diseases
Classical Mechanics
Computed tomography
Computer simulation
Congenital diseases
Coronary artery disease
Decision making
Double Outlet Right Ventricle - diagnostic imaging
Double Outlet Right Ventricle - physiopathology
EKG
Electrocardiography
Electrophysiology
Heart
Heart diseases
Hemodynamics
Humans
Mathematical models
Medical treatment
Models, Cardiovascular
Molecular modelling
Original Article
Pathophysiology
Patient-Specific Modeling
Patients
Perioperative Period
Surgery
Three dimensional models
Tomography, X-Ray Computed
Torso
Ventricle
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Summary:For treatment of complex congenital heart disease, computer simulation using a three-dimensional heart model may help to improve outcomes by enabling detailed preoperative evaluations. However, no highly integrated model that accurately reproduces a patient’s pathophysiology, which is required for this simulation has been reported. We modelled a case of complex congenital heart disease, double outlet right ventricle with ventricular septal defect and atrial septal defect. From preoperative computed tomography images, finite element meshes of the heart and torso were created, and cell model of cardiac electrophysiology and sarcomere dynamics was implemented. The parameter values of the heart model were adjusted to reproduce the patient’s electrocardiogram and haemodynamics recorded preoperatively. Two options of in silico surgery were performed using this heart model, and the resulting changes in performance were examined. Preoperative and postoperative simulations showed good agreement with clinical records including haemodynamics and measured oxyhaemoglobin saturations. The use of a detailed sarcomere model also enabled comparison of energetic efficiency between the two surgical options. A novel in silico model of congenital heart disease that integrates molecular models of cardiac function successfully reproduces the observed pathophysiology. The simulation of postoperative state by in silico surgeries can help guide clinical decision-making.
ISSN:0090-6964
1573-9686
DOI:10.1007/s10439-020-02488-y