Evidence map›Paper›PMID 31822264›Full record

ArticleBMC bioinformatics2019

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

Ruy Freitas Reis, Juliano Lara Fernandes, Thaiz Ruberti Schmal, Bernardo Martins Rocha, Rodrigo Weber Dos Santos, Marcelo Lobosco

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Variability in electrophysiological properties and conducting obstacles controls re-entry risk in heterogeneous ischaemic tissue.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020
    Article
  6. Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Ruy Freitas ReisDepartment of Computer Science, Universidade Federal de Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Brazil. ruyfreitas@ice.ufjf.br.
Juliano Lara FernandesJose Michel Kalaf Research Institute, Radiologia Clinica de Campinas, Avenida Jose de Souza Campos 840, Campinas, Brazil.
Thaiz Ruberti SchmalHospital Universitário, Universidade Federal de Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Brazil.
Bernardo Martins RochaDepartment of Computer Science, Universidade Federal de Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Brazil.
Rodrigo Weber Dos SantosDepartment of Computer Science, Universidade Federal de Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Brazil.
Marcelo LoboscoDepartment of Computer Science, Universidade Federal de Juiz de Fora, Rua José Lourenço Kelmer, Juiz de Fora, Brazil.
Universidade Federal de Juiz de Fora · BRFundação de Amparo à Pesquisa do Estado de São Paulo · BRHospital Universitário - Universidade Federal de Juiz de Fora · BR

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Finance Code 001
6 · The paper itself

Abstract

backgroundMyocarditis 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.

resultsA 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.

conclusionsThis 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.

Indexed as

Computer SimulationEdemaMyocarditisComputational BiologyHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingPrecision MedicineBiomechanicsComputational immunologyMathematical modelingMyocarditisPoroelasticity

Identifiers

PMID31822264
PMCPMC6905016
OpenAlexW2995168129

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.