A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images

Abstract Background Myocarditis is defined as the inflammation of the myocardium, i.e. the cardiac muscle. Among the reasons that lead to this disease, we may include infections caused by a virus, bacteria, protozoa, fungus, and others. One of the signs of the inflammation is the formation of edema,...

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Main Authors: Ruy Freitas Reis, Juliano Lara Fernandes, Thaiz Ruberti Schmal, Bernardo Martins Rocha, Rodrigo Weber dos Santos, Marcelo Lobosco
Format: Article
Language:English
Published: BMC 2019-12-01
Series:BMC Bioinformatics
Subjects:
Online Access:https://doi.org/10.1186/s12859-019-3139-0
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spelling doaj-4e01962cc35a474db81deb53a15f3d982020-12-13T12:41:46ZengBMCBMC Bioinformatics1471-21052019-12-0120S611110.1186/s12859-019-3139-0A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI imagesRuy Freitas Reis0Juliano Lara Fernandes1Thaiz Ruberti Schmal2Bernardo Martins Rocha3Rodrigo Weber dos Santos4Marcelo Lobosco5Department of Computer Science, Universidade Federal de Juiz de ForaJose Michel Kalaf Research InstituteHospital Universitário, Universidade Federal de Juiz de ForaDepartment of Computer Science, Universidade Federal de Juiz de ForaDepartment of Computer Science, Universidade Federal de Juiz de ForaDepartment of Computer Science, Universidade Federal de Juiz de ForaAbstract Background Myocarditis is defined as the inflammation of the myocardium, i.e. the cardiac muscle. Among the reasons that lead to this disease, we may include infections caused by a virus, bacteria, protozoa, fungus, and others. One of the signs of the inflammation is the formation of edema, which may be a consequence of the interaction between interstitial fluid dynamics and immune response. This complex physiological process was mathematically modeled using a nonlinear system of partial differential equations (PDE) based on porous media approach. By combing a model based on Biot’s poroelasticity theory with a model for the immune response we developed a new hydro-mechanical model for inflammatory edema. To verify this new computational model, T2 parametric mapping obtained by Magnetic Resonance (MR) imaging was used to identify the region of edema in a patient diagnosed with unspecific myocarditis. Results A patient-specific geometrical model was created using MRI images from the patient with myocarditis. With this model, edema formation was simulated using the proposed hydro-mechanical mathematical model in a two-dimensional domain. The computer simulations allowed us to correlate spatiotemporal dynamics of representative cells of the immune systems, such as leucocytes and the pathogen, with fluid accumulation and cardiac tissue deformation. Conclusions This study demonstrates that the proposed mathematical model is a very promising tool to better understand edema formation in myocarditis. Simulations obtained from a patient-specific model reproduced important aspects related to the formation of cardiac edema, its area, position, and shape, and how these features are related to immune response.https://doi.org/10.1186/s12859-019-3139-0Computational immunologyMyocarditisPoroelasticityMathematical modelingBiomechanics
collection DOAJ
language English
format Article
sources DOAJ
author Ruy Freitas Reis
Juliano Lara Fernandes
Thaiz Ruberti Schmal
Bernardo Martins Rocha
Rodrigo Weber dos Santos
Marcelo Lobosco
spellingShingle Ruy Freitas Reis
Juliano Lara Fernandes
Thaiz Ruberti Schmal
Bernardo Martins Rocha
Rodrigo Weber dos Santos
Marcelo Lobosco
A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images
BMC Bioinformatics
Computational immunology
Myocarditis
Poroelasticity
Mathematical modeling
Biomechanics
author_facet Ruy Freitas Reis
Juliano Lara Fernandes
Thaiz Ruberti Schmal
Bernardo Martins Rocha
Rodrigo Weber dos Santos
Marcelo Lobosco
author_sort Ruy Freitas Reis
title A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images
title_short A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images
title_full A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images
title_fullStr A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images
title_full_unstemmed A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images
title_sort personalized computational model of edema formation in myocarditis based on long-axis biventricular mri images
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2019-12-01
description Abstract Background Myocarditis is defined as the inflammation of the myocardium, i.e. the cardiac muscle. Among the reasons that lead to this disease, we may include infections caused by a virus, bacteria, protozoa, fungus, and others. One of the signs of the inflammation is the formation of edema, which may be a consequence of the interaction between interstitial fluid dynamics and immune response. This complex physiological process was mathematically modeled using a nonlinear system of partial differential equations (PDE) based on porous media approach. By combing a model based on Biot’s poroelasticity theory with a model for the immune response we developed a new hydro-mechanical model for inflammatory edema. To verify this new computational model, T2 parametric mapping obtained by Magnetic Resonance (MR) imaging was used to identify the region of edema in a patient diagnosed with unspecific myocarditis. Results A patient-specific geometrical model was created using MRI images from the patient with myocarditis. With this model, edema formation was simulated using the proposed hydro-mechanical mathematical model in a two-dimensional domain. The computer simulations allowed us to correlate spatiotemporal dynamics of representative cells of the immune systems, such as leucocytes and the pathogen, with fluid accumulation and cardiac tissue deformation. Conclusions This study demonstrates that the proposed mathematical model is a very promising tool to better understand edema formation in myocarditis. Simulations obtained from a patient-specific model reproduced important aspects related to the formation of cardiac edema, its area, position, and shape, and how these features are related to immune response.
topic Computational immunology
Myocarditis
Poroelasticity
Mathematical modeling
Biomechanics
url https://doi.org/10.1186/s12859-019-3139-0
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