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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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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