3D Myocardial Scar Prediction Model Derived from Multimodality Analysis of Electromechanical Mapping and Magnetic Resonance Imaging

Autor: Pieter A. Doevendans, Hans T. van den Broek, Rutger R. van de Leur, René van Es, Steven Wenker, Frebus J. van Slochteren, Steven A. J. Chamuleau
Jazyk: angličtina
Rok vydání: 2019
Předmět:
0301 basic medicine
Sus scrofa
Infarction
Action Potentials
Pharmaceutical Science
030204 cardiovascular system & hematology
Logistic regression
Late gadolinium–enhanced MRI
0302 clinical medicine
Genetics(clinical)
Myocardial infarction
Genetics (clinical)
medicine.diagnostic_test
Signal Processing
Computer-Assisted
Electromechanical mapping
Cardiology
cardiovascular system
Molecular Medicine
Original Article
Electrophysiologic Techniques
Cardiac
Cardiology and Cardiovascular Medicine
MRI
medicine.medical_specialty
Magnetic Resonance Imaging
Cine
Heart failure
03 medical and health sciences
Cicatrix
Imaging
Three-Dimensional
NOGA
stomatognathic system
Predictive Value of Tests
Internal medicine
Cardiac procedures
medicine
otorhinolaryngologic diseases
Genetics
Journal Article
Animals
cardiovascular diseases
Tissue Survival
Models
Statistical
business.industry
Myocardium
Magnetic resonance imaging
Gold standard (test)
medicine.disease
Disease Models
Animal
stomatognathic diseases
Feature tracking
030104 developmental biology
Late gadolinium-enhanced MRI
business
Zdroj: Journal of Cardiovascular Translational Research, 12(6), 517. Springer New York
Journal of Cardiovascular Translational Research
ISSN: 1937-5387
Popis: Many cardiac catheter interventions require accurate discrimination between healthy and infarcted myocardia. The gold standard for infarct imaging is late gadolinium–enhanced MRI (LGE-MRI), but during cardiac procedures electroanatomical or electromechanical mapping (EAM or EMM, respectively) is usually employed. We aimed to improve the ability of EMM to identify myocardial infarction by combining multiple EMM parameters in a statistical model. From a porcine infarction model, 3D electromechanical maps were 3D registered to LGE-MRI. A multivariable mixed-effects logistic regression model was fitted to predict the presence of infarct based on EMM parameters. Furthermore, we correlated feature-tracking strain parameters to EMM measures of local mechanical deformation. We registered 787 EMM points from 13 animals to the corresponding MRI locations. The mean registration error was 2.5 ± 1.16 mm. Our model showed a strong ability to predict the presence of infarction (C-statistic = 0.85). Strain parameters were only weakly correlated to EMM measures. The model is accurate in discriminating infarcted from healthy myocardium. Unipolar and bipolar voltages were the strongest predictors. Electronic supplementary material The online version of this article (10.1007/s12265-019-09899-w) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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